Wireless and Emerging Technologies to Meet E-Government Demands: Applications, Benefits, and Challenges

Abstract

The rapid digitization of public services has positioned e-government as a cornerstone of modern governance, relying increasingly on advanced wireless and emerging technologies to support scalable, resilient, and data-driven operations. Despite extensive adoption efforts, a comprehensive investigation and systematic analysis of how emerging technologies collectively serve e-government across key domains remains limited. In particular, existing studies often address technologies in isolation, leaving gaps in understanding their integrated roles in smart cities, sustainability initiatives, cybersecurity frameworks, and evolving energy paradigms. This paper investigates the use of wireless and emerging technologies within e-government ecosystems and examines their employment and benefits across diverse public-sector applications. The study analyzes how these technologies contribute to service delivery, operational coordination, and policy execution, while critically discussing the technical, organizational, and regulatory challenges associated with their deployment. Furthermore, the impacts of these challenges on performance, security, and long-term viability are assessed and provided to guide researchers, system designers, and policymakers. By consolidating fragmented research and highlighting cross-domain interactions, this work offers a structured perspective on the role of wireless and emerging technologies in shaping the next generation of e-government systems.

1. Introduction

In the last ten years, governments around the world have improved their information and communication technologies (ICTs) to facilitate seamless public services for citizens. Currently, governments worldwide are increasingly striving to improve accessibility, openness, and efficiency in public services while fostering significant citizen participation [1]. E-government seeks to enhance accountability, transparency, and accessibility in governance by digitizing administrative processes, enabling real-time data interchange, and empowering individuals to make informed decisions. Emerging technologies [2,3] such as Internet of Things (IoT), blockchain, and Artificial Intelligent (AI) have accelerated the global adoption of e-government. Meanwhile, underdeveloped nations commonly encounter illiteracy and infrastructural deficiencies, rendering them vulnerable to an expanding digital divide. Conversely, wealthy nations reap the advantages of chatbots and AI-driven systems for citizen questions.

Global indices have been established to assess governments’ digital and technological preparedness, which in turn informs the implementation of new citizen-oriented policies. These initiatives enhance institutional confidence and foster technological innovation in public service delivery. Citizen participation in governance processes such as social services, economic growth, education, health care, poverty reduction, justice, institutions, environmental challenges, and digital participation in the e-government sector has increased [4].

Rapid breakthroughs in computer and digital technology are transforming public administration operations in many nations. The integration of data analysis and advanced technologies enhances decision-making and enables multiple solution pathways. Systems with complicated objectives might function in the physical or digital domain, perceiving their environments through the acquisition and reasoning of structured and unstructured data to determine optimal actions [5].

The fourth industrial revolution has engendered swift technical advancement and transformations across many sectors. Among these developments, electronic government (e-government) has arisen as a digital instrument for augmenting governance, boosting service delivery, and fostering transparency in technology innovation. It has assumed a crucial role in promoting sustainable development. Recent studies illustrate the application of AI [5], IoT [6], and blockchain [7] to enhance service delivery, citizen engagement, and transparency in several aspects.

For the effective acceptance of new technology at the governmental level [8,9,10], it is essential to recognize and comprehend the elements that drive this adoption. E-government technologies are now employed to enhance smart cities [4], facilitating IoT urban planning, waste management, transportation efficiency, and environmental sustainability. To enhance transparency, the governance acquisition system may be digitized, and an e-citizen portal can provide real-time reporting of service problems, therefore increasing accountability.

Many studies discussed and investigated the use of one or more technologies, including wireless technologies such as 5G/6G [2] and emerging technologies [3,11] such as AI [12]. However, limited research has examined the adoption of emerging technologies in e-government, particularly regarding applications, benefits, and challenges related to smart cities, cybersecurity, and energy systems. This study aims to discuss and investigate the use of wireless and emerging technologies in e-government and their characteristics and applications. The objectives were established as follows:

• To present a comprehensive analysis of the usage of wireless and emerging technologies across diverse e-government sectors.
• To identify and assess the theories applied within the framework of diverse technologies in e-government.
• To examine technological applications in e-government with respect to smart city development, sustainability assessment, cybersecurity, and energy efficiency.
• To examine the difficulties related to the evaluated technology in each situation.
• To present a practical example of a collaborative methodology utilizing selected technology for diverse objectives.

To achieve these aims and contextualize this research within current knowledge, the following questions were posed:

• RQ1: What is the current state of adoption and utilization of wireless and emerging technologies in e-government?
• RQ2: Which theories, models, and conceptual frameworks are used to analyze and understand emerging technologies in e-government?
• RQ3: How are emerging technologies applied in e-government across smart cities, sustainability, cybersecurity, and energy management domains?
• RQ4: What are the key technical, organizational, and operational challenges affecting the adoption of emerging technologies in e-government?
• RQ5: How can a collaborative technological methodology be designed and implemented to integrate multiple emerging technologies for achieving diverse e-government objectives?

This study enables academics to better understand the deployment of emerging and wireless technology in e-government. This contribution can improve managerial decision-making and expand scholarly discussions on technology adoption, with implications for managing government innovations and offering a comprehensive understanding of societal challenges and strategies.

To ensure methodological rigor and transparency, this study adopts a structured narrative review approach rather than a formal systematic literature review protocol. Relevant studies published within the last ten years were retrieved from major scientific databases, including IEEE Xplore, ScienceDirect, and Web of Science (WoS), with Google Scholar used as a complementary source. The search query ((wireless) OR (technology)) AND ((“e-government”) OR (“e-governance”)) was applied to titles, abstracts, and keywords. The initial search yielded 1446 records from IEEE Xplore, 5421 from ScienceDirect, and 3141 from Web of Science. Only peer-reviewed journal articles were considered, while books, book chapters, conference summaries, magazines, editorials, and other non–peer-reviewed sources were excluded. After removing duplicates, the records were screened based on predefined inclusion criteria emphasizing relevance, technical contribution, and alignment with the study objectives. The review was further restricted to publications addressing the specific technologies examined in this paper, particularly those related to smart city applications, sustainability, cybersecurity, and energy within the context of e-government; studies focusing on unrelated technologies were excluded. Following full-text assessment and quality evaluation, the final corpus consisted of approximately 180–200 articles.

The paper is organized as follows: Section 1 presents the introduction. Section 2 focuses on the e-government and smart cities relationships, including concept and applications. Section 3 discusses environmental and long-term sustainability. Section 4 is dedicated to the use of technologies for cybersecurity purposes in e-government. Section 5 presents the energy trends and the role of technologies within them. Section 6 concludes the work.

2. E-Government and Smart Cities

As urban processes become increasingly complex, cities prioritize efficient resource usage and smart city transformation while fulfilling development goals. Traditional networks and services in smart cities are efficient due to digital and communications technology, benefiting residents and companies [2,3]. The implementation of smart cities will enhance quality of life and address environmental concerns for current and future generations. Rapid urbanization is characterized by significant concentrations of economic activity and wealth. Building sustainable cities becomes more challenging as the global population urbanizes. Social disparities in urban areas pose a challenge for sustainable and smart city development. Creating sustainable cities requires using systems thinking and cybernetics [13].

While smart cities primarily address urban prosperity and sustainability through technology, conceptual frameworks can help cities and public institutions grasp this urban growth perspective [14]. Promoting community engagement is crucial for smart city development, since social interactions should be prioritized in city design [15]. E-government access is crucial for all residents, promoting social inclusion through free and rapid access to public services. Good practice models are crucial for support effective policymaking in smart cities. Due to aging populations, congestion, and rising youth and adult unemployment, e-government is essential in cities. Public service efficiency through e-government frees up resources for urban development. This section assesses e-government’s progress. It will also examine how education, particularly digital skills, and access to ICTs affect these sectors and society.

2.1. Smart Cities Understanding

Urban regions must incorporate technology innovations to adapt to population growth and shifting global production patterns in a globalized world. The global city development paradigm must be transformed to be environmentally friendly, productive, and livable. To address new challenges and possibilities, initiatives for future growth should go beyond size, industry profile, or administrative appeal [16]. Identifying and exploiting competitive advantages is crucial, specifically to reduce risks related to contemporary societal developments.

Smart technologies automate monotonous chores and increase quality, efficiency, and equality in interactions through monitoring, analysis, and understanding. Smart cities should address new concerns such as developing communication and dissemination technologies, efficiently connecting and coordinating them, using data across time and space, and proactively identifying risks, uncertainties, and hazards [17]. Fortunately, human-centered AI is gaining popularity [18,19]. Figure 1 shows smart city elements including smart entities like parking, education, buildings, traffic.

Instrumented and networked smart cities employ operational data where web connected sensors, video surveillance cameras, smartphones, and public wireless networks enable city data collection. In urban areas, IoT systems are being utilized to monitor instrumentation. Artificial intelligence is used to evaluate data, detect trends and patterns, and anticipate results to find efficient solutions to enhance production value, system structure, or procedure results [20].

An intelligent city prioritizes economic growth, quality of life, and resource sustainability by investing in people and social capital, infrastructure, and technology. The integration of technology in cities may convert them into smart cities by utilizing data, influencing citizen behavior [21], and enhance people’s lives [22]. An intelligent city must have one of the six pillars [23], as shown in Figure 2.

A challenge in smart city development is the financial risk due to a lack of proven best practices, despite potential returns on investments. Public authorities may be hesitant to participate in smart city technology development due to high initial costs, despite potential future benefits [24]. Another issue with smart city adoption is the requirement to prioritize physical infrastructure improvements, which might limit funding for smart initiatives [25]. A third issue with smart city growth, particularly in service delivery, is the potential for increased citizen inequality [26].

The economic and social benefits of smart city transformation will increasingly become apparent as technologies improve and automation reduces human contact. Innovative and technologically advanced smart cities play a key role in societal development due to their large concentration of people, ideas, and resources [27].

Table 1. A summary of recent contributions of technologies for in smart cities.

Ref.	Year	Journal	Technology	Description
[28]	2023	Sensors	5G IoT, Fog, Cloud computing	To enhance resource management, businesses can employ network slicing, which divides the physical network into logical slices based on the Quality of Service (QoS) requirements. This study proposes an IoT-fog-cloud architecture for e-Health services. The framework comprises three interrelated systems: a cloud radio access network, fog computing system, and cloud computing system. A queuing network models the proposed system.
[29]	2020	Journal of Parallel and Distributed Computing	Cloud, edge computing, 5G	The rapid rise of energy cloud systems necessitates a major paradigm shift in energy asset management and optimization to meet consumer demands. This study presents and assesses an edge computing architecture to efficiently manage and optimize energy cloud systems while improving dependability, safety, and security. The suggested framework uses edge computing and 5G technology’s growing computing capabilities.
[30]	2023	Future Generation Computer Systems	IoT, cloud, fog, and edge	Building infrastructures and reducing costs requires using a simulation platform to model and analyze their behavior (power consumption, CPU utilization, bandwidth, etc.). Simulations must be scalable to add components and simulate big infrastructures without affecting performance. A scalable Edge, Fog, and Cloud computing infrastructure simulator, ENIGMA can simulate many devices and elements and assess their features.
[31]	2020	Future Generation Computer Systems	Blockchain, IoT, AI	AI powers real-time, scalable, and accurate large data analysis. Although AI-based big data analysis tools are valuable, centralized architecture, security, privacy, resource limits, and a shortage of training data present obstacles. The major objective is to build and create a blockchain-AI IoT infrastructure for large data processing.
[32]	2023	Sensors	Blockchain, deep learning	Blockchain can provide data integrity, privacy, and interoperability in healthcare systems without centralized authority. Blockchain and hybrid deep learning enable healthcare data analysis and decision-making. Combining deep learning algorithms with classic Machine Learning (ML) methods, hybrid deep learning processes complicated healthcare data including medical records, pictures, and sensor data accurately and efficiently. Hybrid deep learning models are used to create a permissions-based blockchain architecture for scalable and secure healthcare systems. The framework protects patient privacy by restricting access to and modification of sensitive health data while enabling healthcare provider data sharing and cooperation.
[33]	2024	Energy Reports	IoT, deep learning	The research details a novel approach to improving smart city energy consumption through the use of deep learning algorithms in conjunction with the IoT. It enables smart judgments on energy efficiency and savings by using real-time data from several sources, such as sensors, devices, and smart grids.
[34]	2022	IEEE Access	Light Fidelity (LiFi), deep learning	Geometrical designs and user behavior impacts were addressed for an indoor LiFi system with realistic channel models. Two learning-based techniques were subsequently proposed to improve signal identification and resource allocation with these channel models. Downlink (DL)-based methods achieve high performance even in irregular system environments, unlike conventional methods. In partial Channel State Information (CSI) and with furniture, the suggested DL approaches indirectly estimated the channel and improved signal identification and resource allocation by treating it as a black box.
[35]	2014	IEEE Systems Journal	Radio Frequency Identification (RFID), IoT	The IoT’s latest Real-time locating systems (RTLS), iLocate, uses active RFID to find items with high precision up to 30 cm and ultralong distance transmission. ILocate uses virtual reference tags for fine-grained localization. Routing RFID communication using frequency-hopping helps iLocate overcome signal multipath. iLocate uses ZigBee for massive RFID networks.
[36]	2020	Sustainability	Digital twin (DT)	They demonstrated an urban DT prototype for Herrenberg, Germany, a 30,000-person municipality. Urban DTs are advanced data models for collaboration. The prototype includes a 3D model of the built environment, a space syntax-based street network model, an urban mobility simulation, a wind flow simulation, and empirical quantitative and qualitative data from volunteered geographic information.
[37]	2022	Procedia Computer Science	Augmented reality (AR)/ Virtual Reality (VR)	This article examines how sector 4.0 might incorporate smart glasses and mobile device users into the augmented reality sector to speed up labor and data transfers in US manufacturing, warehousing, and transportation organizations. The paper demonstrated the potential of AR/VR technology and contemporary IT systems that are being used globally in TSL industries.

presents recent contributions related to smart cities that can support e-government.

2.2. Information and Communication Technologies as a Catalyst for Smart City E-Government Development

The development of smart cities relies on intricate interactions between citizens, governments, and stakeholders, making e-government a subject of scientific and political interest [38]. There is mutual relationship between e-government and smart cities. Public authorities are improving their services via the use of ICTs in e-government, while innovative data collection, processing, and analysis are the main focus of smart cities. They are working together to improve decision-making [39], educate citizens, and provide high-quality public services. As part of its mission to “make cities smarter”, e-government has faced the formidable obstacle of moving from a relatively isolated innovation to an integral part of government operations. Table 2 presents various aspects related to e-government in smart cities.

Local governments are best positioned to understand and harness smart city potential and address community challenges, while national governments play a growing role in coordinating the growth. Cities need a variety of technologies to be well-equipped. Smart city applications use IoT systems and wireless technology.

Smart city technologies can support several potential uses that will emerge when these technologies achieve mainstream utilization. The provision of municipal government services can potentially increase happiness and wellness of society. Local governments can comprehend and respond to region-specific issues and opportunities to enhance responsiveness [40]. E-government is the use of ICTs by government authorities to change relations with individuals and enterprises. Integrating ICTs into citizen engagement initiatives for public services and policy can lead to smarter cities [41].

Table 2. Smart governance in various cities.

Ref.	City	Model	Main Technology	Preservation	Participation
[42]	Singapore	Intelligent nation scheme	AI, IoT, blockchain	Optimized service provision, augmented urban transportation, sustainable urban development	Public participation through digital platforms
[43]	Johannesburg	Aspirations for spatial change and urban governance	Digital platforms, geographic information system (GIS)	Concentrates on mitigating urban fragmentation and promoting sustainable development.	Community-based public engagement, local councils (baraza and indaba)
[44]	Leuven City	Intelligent nation scheme	Digital platforms, AI	Optimized company operations, streamlined public services	Active participation via electronic platforms
[45]	Kenya	Augmenting civic engagement in government	ICT, AI	Augmented public involvement, improved decision-making, and increased transparency	Community engagement, digital services for underrepresented populations
[46]	Tallinn	Integrated smart city framework	e-government platforms, AI	Enhanced efficacy in the provision of public services	Public engagement via e-governance platforms
[47]	Istanbul	Knowledge-driven urban development	Digital platforms, AI, urban analytics	Enhanced competitiveness and sustained economic advancement	Engagement within the community via digital platforms

Table 2. Smart governance in various cities.

Ref.	City	Model	Main Technology	Preservation	Participation
[42]	Singapore	Intelligent nation scheme	AI, IoT, blockchain	Optimized service provision, augmented urban transportation, sustainable urban development	Public participation through digital platforms
[43]	Johannesburg	Aspirations for spatial change and urban governance	Digital platforms, geographic information system (GIS)	Concentrates on mitigating urban fragmentation and promoting sustainable development.	Community-based public engagement, local councils (baraza and indaba)
[44]	Leuven City	Intelligent nation scheme	Digital platforms, AI	Optimized company operations, streamlined public services	Active participation via electronic platforms
[45]	Kenya	Augmenting civic engagement in government	ICT, AI	Augmented public involvement, improved decision-making, and increased transparency	Community engagement, digital services for underrepresented populations
[46]	Tallinn	Integrated smart city framework	e-government platforms, AI	Enhanced efficacy in the provision of public services	Public engagement via e-governance platforms
[47]	Istanbul	Knowledge-driven urban development	Digital platforms, AI, urban analytics	Enhanced competitiveness and sustained economic advancement	Engagement within the community via digital platforms

For e-government to succeed, it must utilize all parts of ICT systems and infrastructure [48]. When compared to commercial information systems, e-government systems aim for social and political goals such as trust, social inclusion, community wellness, sustainability, in addition to efficiency and effectiveness [49]. However, e-government is encountering economic and technological obstacles similar to those encountered in the corporate world. These may force government agencies to be creative and in sync with new ideas.

Effective e-government depends on the strategic use of cutting-edge ICTs to improve operational efficiency. Due to financial limitations, the delivery of services by e-government must be economically feasible and delivered in a timely manner while making use of suitable technology to obtain desired results [50]. In such a setting, informatics and digitization play a part as either inputs or facilitators of government modernization. Online policymaking centers on creative, user-focused, and public assistance. Figure 3 shows various technologies that can make a significant contribution to e-government. This research examines these technologies, and their role in smart cities and other aspects will be presented and discussed.

Recent years have seen the emergence of numerous disruptive technologies with wide-ranging potential applications for smart city e-government. These technologies are discussed in the following sub-sections.

2.2.1. 5G/6G Wireless Networks

Smart infrastructure powered by 6G has been touted as a game-changer in terms of sustainability, thanks to its capacity to facilitate energy-efficient public services and real-time control of vital metropolitan infrastructure [51]. The 6G network will enable the integrated utilization of mobile communication, intelligent awareness, and computational activities through advanced convergence and collaborative enhancement. Server administration may enhance data center efficiency through methods such as smart load allocation, flexible voltage expansion, and server reduction [52]. Shifting from human-centric to human-machine-centric models, smart terminals will enable communication and interaction through multiple modalities, including fingers, voice, eyes, and neurological impulses. Critical services like public safety communications, real-time traffic control, and linked citizen portals benefit greatly from low latency of 6G and high bandwidth [28]. With 5G technology, smartphones may be utilized as a resource for processing queries locally or via mobile edge computing [53]. A conventional 5G mmWave deployment provides sufficient UAV coverage at (200 m intersite distance (ISD)) [29]. Preventing interference can be achieved by developing a coordination system that tracks UAV trajectory, allowing for dynamic resource sharing without compromising reliability [54].

2.2.2. IoT

One example of how the IoT is being integrated with 6G to boost capacity and reliability in next-gen networks is the proposed IoT-oriented 6G Multiple-Input Multiple-Output (MIMO) system, which can handle large-scale smart city deployments with better bit-error-rate (BER) performance. Sub-GHz bands offer broad coverage for IoT devices due to signal attenuation features [55,56,57]. Low Earth Orbit (LEO) is ideal for IoT satellites due to modest distances (500–2000 km) to the ground. Functionally, IoT enhances human–thing interactions, allowing smart cities, infrastructures, services and improving quality of life and resource use. Using several software architectures, IoT enable smart things and humans to communicate with each other globally and ubiquitously [55].

2.2.3. Edge and Fog Computing

Edge and fog computing architectures not only improve response times but also enhance data privacy, as sensitive information does not always need to be transmitted to distant data centers [58]. Different strategies have been presented in edge computing to minimize resource use in the edge layer [30]. Safe edge computing requires cryptographic security in system design and network architecture. In federated learning, the model is trained on many edge devices using a portion of training data. When edge servers are down, task transfer is critical for maximum performance. However, task allocation and scheduling should be fault-tolerant to minimize system defects and reduce repair costs [59].

2.2.4. Blockchain and Distributed Ledger Technologies (DLT)

Digital identity management, secure land registries, voting systems, and tamper-resistant public procurement are some of the smart-city applications. To ensure the security of smart-city transactions even in the era of quantum computing, one design incorporates identification systems and lightweight quantum-resistant consensus [31]. Blockchain uses decentralized storage for massive amounts of data connected by smart contract code linking each block to the preceding block [60]. Decentralized cloud blockchain IoT networks execute smart contracts peer-to-peer, enhancing resilience and resistance against cyber-attacks. This offers safe, rapid, and reliable communication for both parties [32]. Limitations of blockchain technology include relying on high energy consumption for data confidentiality and security. Smart contract testing with an Ethereum simulator, addresses data verification and security issues by using formal verification and searching of information [61].

2.2.5. AI and ML

Smart city predictive and autonomous government is made possible in large part by AI and ML. Some examples of possible uses include government transaction fraud detection, chatbots for citizen interaction, public system anomaly detection (such as utilities), and real-time traffic forecasts. In order to increase the data transmission rate, the intelligent network necessitates a network connection with low latency [62,63]. Improving consumers’ Quality of Experience (QoE) necessitates integrating AI with 6G connection [64]. In addition, intelligent cars, smart devices, smart human services, smart automation, and many more areas necessitate an ever-improving QoE. This allows intelligent devices to anticipate, choose, and collaborate [33,65]. AI approaches can improve wireless connection by predicting mobility and providing appropriate handover solutions [66].

2.2.6. Optical Wireless Communication (OWC)/LiFi

Some types of OWC, such as LiFi [67] (light-based communication), send data using visible or infrared light. Due to the fact that light cannot readily pass through barriers, this technology provides not just increased physical protection but also extremely high bandwidth. LiFi may reach peak data speeds of 10 Gbps [68]. LiFi has several advantages over RF [69], such as a license-free optical spectrum, use in RF-restricted areas like hospitals and underwater, and secure wireless communication because light cannot pass through opaque objects. Trade-offs exist between energy efficiency and spectral efficiency, with better spectral efficiency requiring more energy per bit [70]. Applications with varying quality of service needs will likely be able to use future indoor wireless networks [71].

2.2.7. Drones (UAVs)

Smart cities are making more and more use of UAVs for e-government tasks. Their services include gathering data from above to aid in city planning, building and bridge inspections, pollution and green space monitoring, and disaster damage assessment. Government control centers may access real-time video and geographical data sent by these drones via wireless connectivity. This allows for informed decision-making and speedy response [72,73]. The deployment of UAVs dramatically impacts network performance since relay coordinates determine channel quality and connection capacity to and from the UAV. Multiobjective combinatorial optimization of network resources for various goals, such as reduced latency, is difficult in real time, especially for small networks.

2.2.8. RFID, Near-Field Communication (NFC) and Smart Tagging

RFID and NFC technology enable contactless identification, control of access, and tracking of assets. Smart public transportation tickets, digital identification cards, protected facility access, and public asset inventory management are some of their many applications in e-government. RFID tags can be passive, active, or battery-assisted passive [35]. Active readers may operate from 1 m to tens of meters, providing asset oversight and management flexibility. The covered area is equipped with reference tags for accuracy, while item tags provide RFID locations to readers. Moreover, RFID tags are less prevalent than WiFi or Bluetooth devices. RFID tags come in several varieties, some of which are easily copied. Consequently, RFID systems are vulnerable to counterfeit tags [3].

2.2.9. Low-Power Wide-Area Networks (LPWAN)

Water meters, garbage can sensors, parking lot monitors, and environmental trackers are all examples of smart-city IoT devices that LPWAN is used for by governments. They provide permanent data streaming without periodic maintenance and have low energy consumption, making them cost-effective for city-wide deployments. In some applications, greater data volumes, fluctuating bandwidth, lower coverage, and cost compromises are acceptable [74,75]. Measurements of humidity, temperature, pollution, and noise, enhanced metering infrastructure, intelligent roads and transit, street lighting, and dwellings are examples. Smart city applications require a high-capacity, scalable LPWAN. Smart city apps may not prioritize finances in urban areas.

2.2.10. Vehicle-to-Everything (V2X) Communication

Intelligent transport management, including data-driven mobility policies, adaptive traffic signals, accident avoidance, and emergency-vehicle prioritizing, is all aided by V2X for e-government. Intelligent transportation systems have come a long way since the advent of cellular V2X communication (C-V2X) [76]. C-V2X can improve autonomous cars’ decision-making by giving them real-time situational awareness via connectivity with infrastructure and other road users. More significantly, this system will deliver sustainable transportation and can cut travel delays [77]. By using cellular network architecture and spectrum, C-V2X can maximize resources without causing congestion. Scalability and reliability are improved via Evolved Packet Core (EPC)-backed LTE-based V2X connectivity.

2.2.11. Terahertz (THz) Communication

Post-6G networks are expected to rely on terahertz transmission, which provides exceptionally high bandwidth. Applications that rely heavily on data, such as holographic government meetings, remote robotic inspections of infrastructure, and real-time 3D city mapping, can be made possible with this capacity. At the front end, THz multibeam antennas and front-end chips are crucial, while THz baseband signal processing and resource management are crucial for THz communication system performance [78]. Environmental changes or delayed transceiver movement cause time-domain nonstationarity. Contemporary solid-state THz sources and amplifiers have limited output power, resulting in low equivalent isotropic radiated power [52]. Due to UAV mobility and line-of-sight limits, THz UAV communication poses challenges. To optimize THz UAV potential, research must address specific communication obstacles such as short distances, strict LOS requirements, and mobility-induced signal fluctuations.

2.2.12. Quantum Communication

To secure smart city devices and control systems, one example is the QESIF architecture, which suggests a lightweight framework for IoT security by incorporating QKD at edge gateways [79,80]. Classical digital computers cannot tackle complicated optimization problems in real time due to processing time and energy consumption constraints. Combining radio networks’ advantages with optical transmission systems’ limitless capacity will make THz systems essential in the future. Studying quantum computers, algorithms, networks, and applications is important for safe quantum computing in smart cities.

2.2.13. DTs of Cities

By combining information from the IoT, historical databases, and simulation engines, DT technology may create a virtual replica of a city that can be updated in real time. Governments may utilize this twin for testing policies, optimizing infrastructure, and scenario preparation (e.g., disaster response). With DTs, administrators may test out the outcomes of actions in a simulated environment before committing to them in the actual world, enabling evidence-based governance [36]. In reality, DTs incorporate data from several sources, including collection methods, geodatabases, real-time sensor data, actuators, and crowdsourcing [81]. To meet mobility, flood, and air quality requirements, DTs must incorporate multi-source data into a single system. Data transfer from virtual to the physical world is facilitated by AI and actuators [82].

2.2.14. Metaverse and XR for E-Government

Augmented and virtual reality (AR/VR) as well as the new metaverse provide immersive platforms for digital public-service centers, virtual public meetings, digital urban planning visualization, and citizen participation. Extended reality (XR) has several potential uses for governments, including replicating infrastructure construction, improving public servant training, and expanding virtual access to services. It is commonly utilized to realistically depict human body anatomy, pathophysiology, and clinical scenarios. Mixed reality (MR), a mixture of AR and VR, combines the physical and digital worlds, addressing VR’s exclusion of the real world and AR’s inability to interact with 3D data packets. MR technology in spine care enables surgeons to view intraoperative patient anatomy and overlay virtual holographic features on the operating table for real-time navigation [37,83,84].

2.2.15. Satellite IoT and Satellite 5G/6G

Remote asset monitoring, environmental surveillance, emergency communication continuity, and rural e-government service delivery are some of the ways governments utilize satellite IoT [85]. Hybrid connection, regardless of location, is made possible by the integration of satellite 5G/6G networks [86]. This is crucial for IoT systems covering wide areas or regions without terrestrial network access. New and traditional communication service providers are considering terrestrial wireless long-range ground-to-satellite connectivity. The success of these initiatives depends on industry, standards bodies, and space agencies collaborating to create complementary solutions [87].

Key applications in e-governments for the above technologies and their reported advantages, challenges, and examples in a smart city are summarized in Figure 4. The figure shows how advanced communication networks (e.g., 5G/6G, satellite, LPWAN, THz, LiFi), sensing and cyber-physical technologies (IoT, RFID/NFC, UAVs, DTs), intelligent computing (edge/fog and AI/ML), and secure infrastructures (blockchain and quantum communication) collectively support integrated, data-driven, and citizen-centric governance. For each technology, the diagram outlines four main aspects: applications, benefits, challenges, and example use cases, offering a structured overview of their roles within smart city-enabled e-government ecosystems.

It is necessary to assess the potential costs, risks, and advantages of these technologies as they pertain to e-government. A growing number of public services are now available online, thanks to the internet-savvy populace. A crucial component of the single market’s success can be the utilization of the internet, wide area networks, and mobile computing to facilitate faster, more efficient, and transparent interactions with authorities [88]. Governments are expected to perform public services and create public value in a different way as a result of the rising use of new technology. With the rise of digital technology, citizens are becoming more involved since they can more easily access information, make better decisions with more complete and timely data, and voice their opinions through online forums, petitions, and voting [89].

This section shows how e-government and smart city development are changing society. Cloud computing, AI, and wireless connectivity are among the emerging digital technologies transforming government, innovation, and equitable economic growth. Internet access, digital literacy, and online engagement affect e-government effectiveness, while smart cities and villages can improve public services. E-government service usage is positively correlated with GDP per capita, suggesting these technologies boost economic growth. Although inclusive designs and accompanying regulations are important, numerous challenges remain, especially for persons with low digital aptitude or weak connectivity. Smart city research must be socially focused to enable real digital transformation for modern communities and governments. Key lessons from Section 2 are illustrated in Figure 5.

3. E-Government and Sustainability Metrics

Robust and innovative digital and intelligent technologies will furnish a crucial scientific and technical drive for the modernization of the governance system and its capabilities. The information-driven ecological environment represents a shift from the conventional economic development model to a composite ecological development model that considers the sustainable advancement of people, society, economy, and environment.

The information-centric ecological environment emphasizes the advancement and transformation of comprehensive ecological benefits to achieve overall coordination within the natural-economic-social composite ecological system of urban information-based environments, facilitating stable and orderly evolution. The rapid iterative enhancement of the internet and applications, alongside the widespread adoption of mobile smart technologies like smartphones, not only fosters the ongoing optimization of the information technology landscape but also underscores the pivotal role of data, thereby expediting the digital transformation of conventional governmental governance concepts and frameworks [90].

The swift advancement and extensive use of digital and intelligent technologies have enhanced the efficiency of production, operations, management, logistics, and other sectors, facilitated the transformation of economic growth models, and significantly lowered development costs [91]. Digital government, as an innovative approach to national administration, is encountering unparalleled historical potential and is at a critical stage of development with unprecedented potential. It is essential to consider the evolution of information civilization within the context of an information-centric ecological environment through an ecological cycle perspective, beginning with a holistic, balanced, and dynamic viewpoint. This approach aims to regulate and harmonize the interplay between information and various urban elements, as well as within the information system, thereby enhancing the quality and efficacy of the information-driven ecological environment and augmenting the developmental potential of information.

3.1. Environmental Performance

Overconsumption of natural resources, climate change, biodiversity loss, and other rising environmental concerns have added additional hurdles to the already-concurring global consensus on green development [92]. Globally, nations have adopted green technology innovations in reaction to environmental concerns [93], energy efficiency [94], sustainable energy utilization and advocacy [95], with other initiatives that have yielded impressive outcomes and had a favorable influence on the environmental performance of the nation. Moreover, as one of the variables influencing environmental performance, increasing the digital level can boost environmental performance, according to certain research. But whereas many studies have looked at how companies’ and industries’ digital levels affect green innovation and environmental performance, very few have examined how e-government development affects these same metrics.

Previous studies have shown that variables connected to economic growth, including gross domestic product (GDP) and foreign direct investment (FDI), have improved along with environmental performance through the optimization of industrial structure [96].

Furthermore, environmental performance has been discovered to be correlated with social variables including gender equality and country culture. Innovations in technology, such as digitization, the IoTs, and green innovation, are also important elements that impact environmental performance, according to previous research.

When taking into account the significant impact of governmental acts, environmental performance is affected by national environmental policies, investments, legislation, and regulations [97]. Environmental performance may be enhanced by, among other things, enforcing stricter environmental laws, improving environmental monitoring and management, and pressuring polluters to implement environmental measures [98]. Moreover, it was discovered by [99] that China’s environmental performance was greatly enhanced after the introduction of government environmental subsidy programs by taking part in initiatives to safeguard the environment.

There has been a dearth of research on the relationship between e-government level (EGDI) and environmental performance (EPI), despite the fact that the government, as the primary institution and a key advocate for environmental preservation on a national level, has substantial influence over several facets of environmental protection [100,101]. The electronic government platform may integrate operations including applications for environmental impact assessments and processing for pollutant discharge permits, creating a one-stop environmental service. Because of this, businesses are more likely to embrace green manufacturing technology because the time and money needed to comply are reduced. A good example of a change that has simplified administrative procedures is the “one-stop online service” and “approval without meeting” in China. Businesses’ interest in protecting the environment is piqued by this change in environmental monitoring from command and control to service. Our view is that the extent to which government agencies use the internet could have an effect on ecological outcomes [102].

Table 3. A summary of recent contributions of technologies for long-term sustainability.

Ref.	Year	Journal	Technology	Description
[103]	2023	Wireless networks	Blockchain	Blockchain technology securely stores existing and new data in a ledger distributed throughout the network. In blockchain technology, data are encrypted and disseminated around the network, improving security and privacy. Using blockchain technology, this article offers a decentralized e-government peer-to-peer (P2P) system that protects data and builds public sector confidence.
[104]	2022	Measurement: Sensors	AI, IoT	To increase benefits, efficiency, and effectiveness, governments must understand the primary impediments to complete government transformation and design and offer e-government services utilizing AI and the IoT. For this, a reference model independent of technology platforms and organizational structure is needed to understand the framework and rules for deploying, analyzing, and simplifying e-government services for citizens. The internet is the backbone of e-governance. This article proposes using AI and IoT approaches to assess and improve e-government services for all stakeholders.
[105]	2024	Frontiers in Climate	OWC,	OWC networks can promote climate resilience and sustainable development but face challenges for integration into climate change mitigation. Along with economic concerns, the constraints include hurdles and complex legal structures. This article examines how OWC might mitigate and adapt to climate change.
[106]	2025	Procedia Computer Science	UAV	This study involved pilot and inventory research. It sought to establish whether municipalities use UAVs, why, and under what conditions. Municipalities’ legislative duties guided application evaluation. The study assessed whether UAVs enable basic data collecting or sophisticated roles including informing, analysis and control, planning support, or decision-making. The UAV Maturity Model for Local Government (UMMfLG) aids evaluation. Twenty-two Polish municipalities in the northern Silesian Voivodeship provided data.
[107]	2025	Cybernetics and Systems	IoT-based RFID	Finding a more accurate way to keep track of attendance (i.e., % of attendance) and finding a way to replace the current manual method with an automated one are the primary goals of this project. This project’s suggested approach is to enhance an RFID attendance system that is based on the internet of things.
[108]	2020	IEEE access	V2X	Highlighted V2X communications’ problems and commercial approaches. They presented methods to possibly tackle 5G network difficulties and a high-level hierarchy of a 5G-based V2X ecosystem business model. They also summarized V2X communication laws worldwide.
[109]	2023	Journal of Science and Technology Policy Management	DT	This study addresses a DT-enabled e-government knowledge gap and explores DTs in e-government innovation management. It used exploratory research to discuss a dynamic and interpretative model of DT development for the Fourth Industrial Revolution’s e-government integration. This study was conducted to understand how the DT will affect public service delivery in the future.
[110]	2024	Journal of Science and Technology Policy Management	Metaverse	The paper examines how the metaverse could transform governance, particularly e-government, and highlights the limitations, suggesting future research. An inductive research technique used book content analysis to uncover patterns and generalize them into topics and approaches. Creating a conceptual framework organizes metaverse government knowledge and explains how it improves e-government maturity models.

shows recent contributions to sustainability that can support e-government.

3.2. The Goal of ICTs in E-Government’s Environmental and Long-Term Sustainability

Modern public administration relies on e-government to provide quicker, more transparent, and more accessible services due to rapid worldwide digitization. As nations rely more on digital platforms, the environmental impacts of the underlying technology grow. Cloud computing, AI, optical wireless communication, and IoT sensors may minimize carbon emissions, optimize resource usage, and promote greener infrastructure. However, energy-intensive data centers, electronic trash, and unequal access to digital resources poses further sustainability challenges. Figure 6 displays a diagram of smart city applications and technology for long-term sustainability [103,106,107,111,112,113,114,115,116,117].

As seen in the above figure, data collection, real-time analytics, automation, and secure information transmission are supported by these technologies. The outer application domains show how these technologies may be used to create sustainable public services in several fields, such as smart urban planning, environmental monitoring, climate action, transparent and secure governance, and resource management including the circular economy. Smart water and energy grids, optimized waste recycling, digital identity systems, disaster resilience, biodiversity monitoring, and public records enabled by blockchain are just a few examples of the ways in which ICTs are improving sustainability, efficiency, and transparency in various sectors. Supported by trusted identification layers and decentralized security mechanisms, the architecture prioritizes continuous data and control flows to guarantee resilience, scalability, and long-term sustainability. In order to address energy efficiency, environmental protection, cybersecurity, and governance modernization, the suggested design integrates intelligent sensors, autonomous systems, and sophisticated analytics to show how e-government platforms can promote sustainable growth.

Designing sustainable e-government ecosystems requires understanding each technology’s environmental impact. Governments embrace technologies that increase administrative efficiency and promote national environmental goals by assessing their advantages, hazards, and policy actions. This section focuses only on the environmental impacts, difficulties, and policies needed to sustain the core digital technologies underpinning e-government. The environmental benefits and challenges, risks, and policy implications are summarized in the following

Table 4. Environmental benefits, risks, and challenges of various technologies for e-government.

Technology	Environmental Benefits	Environmental Challenges	Sustainability Risks	Policy Implications
5G/6G	• Enables real-time environmental monitoring and adaptive control (traffic, grids). • Facilitates remote services, reducing travel-related emissions.	• Dense site deployments increase operational energy demand. • Manufacturing and replacement of radio sites and antennas.	• Rising network energy consumption and embodied carbon. • Risk of lock-in to non-renewable energy sources.	• Require green-network renewable energy targets. • Mandate energy efficiency metrics and circular procurement.
IoT	• Continuous, fine-grained sensing of air, water, waste and biodiversity. • Enables automated, optimized resource use (smart lighting, meters).	• Battery disposal and e-waste from massive device volumes. • Device manufacturing requires raw materials and energy.	• Toxic e-waste accumulation and resource depletion. • Energy use from constant connectivity.	• Standards for recyclable/repairable devices and battery take-back. • Minimum device lifetime and energy budgets.
Edge and Fog Computing	• Reduces long-haul data transfer energy by local processing. • Enables real-time environmental controls with lower latency energy.	• Distributed hardware increases embodied environmental impact. • Local cooling and power management complexity.	• Shifts energy footprint from cloud to many edge nodes. • Hardware proliferation and shorter refresh cycles.	• Lifecycle procurement rules and energy caps. • Incentives for efficient, shared multi-tenant edge sites.
Blockchain/DLT	• Immutable traceability for carbon accounting and sustainable supply chains. • Enhances environmental compliance transparency.	• Some consensus mechanisms are energy-intensive. • Redundant storage increases resource use.	• High carbon footprint if using PoW-like systems. • Greenwashing risks when data quality is poor.	• Prefer PoS/permissioned low-energy consensus. • Certification for low-impact ledgers and data integrity.
AI/ML	• Optimizes energy, water and waste flows. • Enables automated detection of pollution incidents.	• High compute demand for model training and inference. • Data center cooling and hardware lifecycle impacts.	• Large carbon footprint at scale. • Concentration of compute in few data hubs increases vulnerability.	• Require energy reporting for AI workloads. • Promote lightweight/edge AI and shared training models.
OWC/LiFi	• Uses LED infrastructure (dual lighting + comms). • High spectral efficiency reduces need for RF hardware.	• Requires line-of-sight and indoor retrofitting. • Risk of higher lighting energy use if mismanaged.	• Increased emissions if lighting relies on non-renewables. • Waste from non-repairable or short-lived fixtures.	• Integrate with efficient LED standards. • Hybrid RF–LiFi planning for energy savings.
UAVs	• Replace many inspection vehicle trips → lower emissions. • Enable targeted surveys and rapid disaster assessment.	• Battery production and disposal issues. • Potential disturbance to wildlife.	• Battery waste and toxic materials. • Habitat disruption from unregulated deployments.	• Ecological impact zone regulations. • Battery recycling and low-impact UAV guidelines.
RFID, NFC and Smart Tagging	• Improves waste and asset tracking → higher recycling rates. • Reduces paper use.	• Mass production of tags adds to e-waste. • Low-cost tags often unrecyclable.	• Accumulation of low-value electronic waste. • Resource use for large tagging programs.	• Require recyclable/biodegradable tags. • Tag take-back and circular procurement.
LPWAN	• Ultra-low-power sensors with multi-year life. • Wide coverage for remote environmental monitoring.	• Battery replacement across many nodes creates waste. • Low data rates limit some sensing applications.	• Long-lived but non-recyclable batteries accumulate. • Overemployment increases waste.	• Battery recycling mandates. • Encourage energy-harvesting and hybrid sensor designs.
V2X	• Reduces congestion and emissions via real-time coordination. • Supports low-emission zones.	• Embodied emissions from vehicles and roadside units. • Short product cycles for on-board units.	• Electronic waste from vehicular modules. • Risk of uneven adoption shifting emissions.	• Modular and upgradeable unit standards. • Circular end-of-life plans and shared infrastructure.
THz Communication	• Enables ultra-detailed sensing and DTs. • Reduces need for physical inspection trips.	• Short ranges require many nodes. • High-power transmitters and cooling demand.	• Large embodied energy in dense deployments. • High operational energy if inefficient.	• Reserve THz for high-value use cases. • Strong energy-efficiency and reuse requirements.
Quantum Communication	• Protects environmental data integrity with low operational energy. • Enables secure environmental monitoring networks.	• High manufacturing footprint for specialized hardware. • Range limits lead to infrastructure concentration.	• Significant upfront environmental cost. • High embodied footprint for critical links.	• Targeted QKD deployment only. • Combine with post-quantum cryptography for scalability.
City DTs	• Simulates and optimizes environmental policies. • Supports lifecycle optimization of infrastructure.	• High compute and storage demand. • Expensive data pipelines and maintenance.	• High operational energy for real-time twins. • Dependence on high-quality sensor networks.	• Renewable-powered hosting requirements. • Standards for model efficiency and data minimization.
Metaverse/XR	• Reduces travel through virtual engagement. • Enables low-impact training and collaboration.	• High rendering/server energy. • Device manufacturing footprint.	• Energy use may offset travel savings. • Headset lifecycle waste and rare-earth materials.	• Promote lightweight XR and renewable hosting. • Enforce device recycling programs.
Satellite IoT and Satellite 5G/6G	• Enables remote/ocean environmental monitoring. • Ensures disaster-response service continuity.	• High launch emissions and hardware footprint. • Orbital debris and disposal challenges.	• Carbon and particulate emissions from launches. • Ground terminal energy demand.	• Reusable/low-impact launch tech. • De-orbit plans and efficient shared constellations.

[103,104,105,106,107,108,109,110] for the technologies.

4. Technology Adoption and Cybersecurity for E-Government

Modern urban management must address cybersecurity in smart cities. In addition to managing infrastructure, e-governments must secure digital systems and citizen data. E-governments often lack robust cybersecurity measures to combat rising cyber threats, even though robust cybersecurity is crucial. Because of this gap, we must understand the barriers to effective cybersecurity in e-government.

While modern technology has undoubtedly improved our lives in countless ways, it has also introduced serious dangers to both individuals and society at large. Due to public scrutiny, regulatory pressure, and concerns about reputation and long-term sustainability, the research [118] presented a conceptual responsible innovation and technology (RIT) evaluation framework for technology organizations. This policy analysis examines internet giants’ RIT guidelines to participate in the responsible practices debate, as shown in Figure 7. This RIT [118] provides a close look at the factors that enable the adoption and success of technologies in order to understand various important aspects before diving deep into security risks of the use and deployment of technologies and their effect on e-government.

Almost all public institutions face cybersecurity as a key socio-technological problem [116]. Local governments, crucial in urban governance, face cybersecurity concerns owing to limited IT expenditures and inconsistencies in security procedures [119]. Current limitations result in antiquated systems and inadequate staff cyber training, increasing data breaches and undermining public trust. As smart city initiatives advance, the interconnectedness of urban digital systems increases their vulnerability.

Cybersecurity risks are becoming more prevalent as a result of municipal governments’ digital transformation. Recent years have seen an increase in the frequency and intensity of cyber-attacks, according to many studies, making cybersecurity a major worry for municipal governments [117]. There is a huge information vacuum about the unique problems and solutions, attack kinds and methodologies, resources, and existing frameworks and standards for cybersecurity at the local level, even though the danger environment in governments is on the rise [120]. Many publications on cyberthreats focus on their significance and landscape, without offering theoretical frameworks or practical ways to address cybersecurity challenges.

Critical challenges and research gaps have been identified in the limited studies on this topic. Ref. [121] found that over 40% of US municipal governments faced daily cyber-attacks, with one-third unsure of their cybersecurity status and two-thirds uncertain about prospective breaches. There is a significant lack of readiness for cybersecurity, including insufficient funds and resources for effective solutions. Researchers recommend addressing the lack of comprehensive governance structures, including policies, standard practices, cybersecurity training, and recovery strategies, to establish a resilient cybersecurity posture in local governments [122,123].

Cybersecurity is essential for organizations to safeguard networks, computers, programs, and data from attacks and unauthorized access. The National Institute of Standards and Technology defines cybersecurity as preventing, detecting, and responding to attacks. The ISO defines cybersecurity as safety for society, people, organizations, and networks. Cyber risk is the impact of uncertainty on cybersecurity goals. NIST offered a detailed description of cyber risk. NIST defines cyber risk as the danger of relying on cyber resources, such as systems or elements in cyberspace. Cybersecurity manages hazards associated with digital data storage, transmission, and processing in computer systems, storage devices, and networks. Traditionally, the notion of organizational cybersecurity centers on the triad of confidentiality, integrity, and availability, commonly referred to as the CIA Triad [124]. The CIA Triad [124,125], depicted in Figure 8, is a commonly utilized conceptual framework that functions as a guiding principle for safeguarding the security of diverse systems and organizations. Confidentiality refers to the characteristic of information that remains undisclosed to unauthorized persons, whereas integrity denotes the attribute of correctness and completeness, and availability signifies the quality of being available and useable upon request [126].

For a number of reasons [119,127,128,129], cybersecurity is a major worry for regional administrations. They are summarized as follows:

• The first thing they do is keep private information that cybercriminals can exploit to steal personal information or money.
• Secondly, it is difficult for federal governments to guarantee cybersecurity due to the large number of local governments, whether they are urban or rural.
• Third, local administrations are unable to execute adequate cybersecurity measures due to restricted funding and staffing. Large, well-funded companies like Google, Yahoo!, Home Depot, and Target have all been the victims of cyberattacks.
• As a fourth point, fraudsters may easily gain access to sensitive records shared by local governments with other federal agencies.
• Finally, local governments face new security vulnerabilities and hazards due to the increasing use of the IoT in the quest to build “smart cities,” which brings advanced ways for managing assets but also exposes them to new threats.

It is critical for local government to have a good awareness of cybersecurity-related issues due to the serious risks and losses that cyberattacks may entail. One of the biggest cybersecurity issues that e-governments face is the lack of thorough regulations and procedures. Cybersecurity training for staff, regular security testing and operations, and the management of sensitive information access are all areas in which municipalities with defined cybersecurity policies excel [123]. It is critical to address these cybersecurity issues thoroughly because effective e-government is dependent on the safe administration of digital infrastructures that are under the purview of local governments. The current lack of research makes it difficult for e-governments to plan and implement adequate cybersecurity measures, which is a major problem for urban administration.

Table 5. Summary of recent contributions of technologies for cybersecurity.

Ref.	Year	Journal	Technology	Description
[129]	2023	Journal of Systems Architecture	IoT	An authentication and authorization-based service security architecture for constrained contexts was described for SDN and smart contract-enabled municipal smart cities. Multichain blockchain networks are testing the collaborative service security architecture. Smart contracts on multichain blockchains were used to propose a new data security strategy for smart city municipal architectural collaboration. Smart contracts are used to securely govern and regulate all interactions and transactions across heterogeneous IoT networks.
[130]	2023	IEEE Access	6G	Based on growing threats, this article provides an intelligent cybersecurity model with 6G-based technologies. The model’s innovative architecture uses algorithms to make rapid, proactive judgments with intelligent cybersecurity based on 6G (IC6G) regulations when AVs are cyberattacked. This concept uses applied cryptography to construct intelligent network security methods.
[131]	2022	Applied Sciences	IoT, edge computing and deep learning	By sending massive volumes of data from Industrial Internet of Things (IIoT) traffic in smart factories to edge servers for deep learning processing, this study suggests a malware detection system that uses edge computing to effectively identify different types of intrusions. Utilizing four significant functions—model training and testing, model deployment, model inference, and training data transmission—for edge-based deep learning, the proposed malware detection system is tri-layered (edge device, edge, and cloud layers).
[132]	2025	Energies	----	In this research, they focused on Supervisory Control and Data Acquisition (SCADA)-based models for deploying phasor measurement units (PMU) and Wide-Area Measurement Systems (WAMS) to traditional grids in order to transform them into smart grids. Cybersecurity helps cyber-physical frameworks and grid stability and efficiency, as seen in poor country examples. By enhancing WAMS capabilities through the integration of ML, multi-level optimization, and predictive analytics, enhanced fault prediction, automated response, and multilayer cybersecurity may be achieved.
[133]	2025	Cyber Security and Applications	Quantum communication	This research examines quantum networks, communication, quantum states, QKD, and quantum cryptography algorithms, focusing on photon polarization states and entangled qubits as quantum information building blocks. BB84 and E91, two well-established quantum cryptography protocols, are also examined for their secure communication benefits. Long-distance quantum information transmission is hindered by quantum state loss in communication channels. To address these issues, error detection, measurement, and correction methods are investigated, with quantum error correction methods important for mitigating noise and imperfections, ensuring accurate quantum information transmission and improving quantum communication system efficiency.

shows recent contributions of technologies for cybersecurity that can support e-government.

4.1. Cybersecurity Roles of Key Emerging Technologies in E-Government

The convergence of various new digital technologies across intelligence, sensing, computing, and communication is transforming cybersecurity in modern e-government systems. Technology collaboration creates a complex and interconnected cyber ecology. These components offer ultra-reliable and secure connection, trusted identity and access management, low-latency resilient processing, proactive threat detection and response, and data integrity and non-repudiation. These technologies, paired with DTs, metaverse/XR environments, and quantum-ready communications, can improve public digital service availability, secrecy, integrity, and trustworthiness. Thus, understanding their cybersecurity roles is crucial to building scalable, secure, and future-proof national e-government platforms. Figure 9 demonstrates how these technologies can help e-government cybersecurity [121,128,130,134,135,136,137,138,139,140,141,142,143,144].

Various sophisticated digital technologies improve security, trust, integrity, and resilience of government services in modern e-government ecosystems. From secure connection and encrypted communication to trustworthy identification, tamper-proof documents, robust compute architectures, and intelligent threat detection, each technology offers cybersecurity benefits. Each component’s security contribution must be understood to create layered, national-scale cyber-resilient public service systems.

4.1.1. 5G/6G Wireless Networks

Built-in encryption, mutual authentication, and network slicing enable isolated secure channels for critical government applications (public safety, emergency response, digital identity). As security needs increase, the need for 6G safety and intelligence of Autonomous Vehicles (AVs) will rise. A 6G-based intelligent cybersecurity approach may effectively address assaults like phishing. Numerous hackers exploit opportunities to launch attacks when users or passengers of AVs conduct monetary transactions with legitimate senders or suppliers. Intelligent and automated networks, underpinned by 6G communication technologies, augment cybersecurity measures when transactions are conducted between two authorized nodes (sender and receiver) [130].

4.1.2. IoT

When properly secured (identity, firmware validation, encryption), IoT provides trusted, tamper-resistant telemetry. However, it can also become a cyber-attack surface, making secure provisioning, updates, and authentication essential. Traditional security techniques are inadequate because of restricted scalability, integrity, and compatibility of existing technologies. More connected devices heighten risks to individuals, networks, and global infrastructure [141]. The U.S., China, and U.K. face the most IoT cybersecurity threats, especially smart home attacks. The sensing layer has four main cybersecurity issues:

(i)

wireless signal strength;

(ii)

IoT sensor node vulnerability;

(iii)

IoT architecture fluidity; and

(iv)

communication, computation, storage, and memory capacity.

4.1.3. Edge and Fog Computing

Edge and fog computing enhance cybersecurity by localizing data processing close to the source, reducing exposure to long-distance transmission attacks. Edge architectures allow faster isolation of compromised nodes [131,145]. The rise in cyberattacks targeting supervisory control and data acquisition (SCADA) systems, programmable logic controllers (PLC), human–machine interfaces (HMI), remote terminal units (RTU), distributed control systems (DCS), and intelligent electronic devices (IEDs) on Shodan, which indexes Internet-connected IIoT devices, confirms that IIoT devices in the manufacturing sector are prime targets for hackers. Security threats are growing because of management targets including software defects, hardware malfunctions, open Internet protocols, shared networks, many parties participating in production processing, and accessible field equipment.

4.1.4. Blockchain/DLT

Smart contracts enforce automated policy compliance. Permissioned blockchains enhance access control, encryption, and governance oversight. Cyberattacks targeting availability can disrupt data flows, resulting in delays, obstructions, or corruption of control signals, so severely affecting the stability, efficiency, and security of smart grid operations. The blockchain is a decentralized database utilizing a P2P network, secured by various cryptographic methods [135]. The selection of various blockchain types for distinct applications within the smart grid must take into account node classifications, anonymity requirements, computational complexity (efficiency), and access restrictions. Hashing converts variable-length inputs into fixed-length encoded output. For optimal security, the hash function should be puzzle-friendly and collision-free [135,138].

4.1.5. AI/ML

AI reinforces national cyber-defense strategies by rapidly analyzing large volumes of logs and behavioral data to identify attacks faster than human operators. Insufficient protection puts assets at risk of hacking efforts, which may go unnoticed and compromise or eliminate sensitive data. AI systems are vulnerable to assaults like other computing systems, and unanticipated modifications might render them ineffectual, giving security experts false confidence [134,146]. Human security analysts struggle to identify non-traditional traffic patterns due to the volume of data delivered and received. Abnormal traffic, wireless signal intensity, biometric authentication attempts, and API calls are network exceptions. Large language models (LLMs) have various uses in generative AI, but their independent utility in cybersecurity is questionable.

4.1.6. OWC/LiFi

LiFi enhances secure communication inside government buildings because light-based transmission is naturally confined to physical spaces (cannot penetrate walls). This reduces external eavesdropping risks and provides secure wireless connectivity for sensitive departments, temporary government field sites, and classified operations. Compared to WiFi, LiFi has inherent security benefits. The user must go closer to intercept signals. LoS path power typically exceeds 80% of the received signal power. This provides LiFi with enhanced physical layer security by making eavesdropping more challenging. However, the transmission connection might lose connectivity owing to intentional or unintentional activity [69,70].

4.1.7. UAVs

Encrypted telemetry, secure command links, and tamper-proof onboard storage help prevent hijacking or spoofing. UAVs can also act as temporary secure communication nodes during emergencies. The fast growth of UAVs and associated technologies has led to security issues including jamming, man-in-the-middle, and bogus message injection attacks. UAV security is a popular study topic. UAVs confront new security dangers from both foreign and internal sources [137,147]. Breach of UAV network and communication data links might cause loss or manipulation of sensitive data. Physical settings and equipment are affected by cyberattacks. Data connections, ground control stations, flight systems, and other support equipment may be exposed. UAVs may be subject to hardware attacks such as purposely created trojans that disable security.

4.1.8. RFID, NFC, and Smart Tagging

These technologies support secure identity, asset tracking, digital access control, border management, and supply-chain verification. RFID-based brain–computer interfaces (BCIs) link the brain and external devices in real time. Researchers and corporations are investigating the potential of BCI to read thoughts [148]. One drawback of BCI devices is the inability to modify or add functionality as needed. NFC transactions use smart devices like smartphones and smartwatches or tap-to-pay cards like EMV credit/debit cards to securely transmit encrypted payment information from customers to retailers [143]. Cards with low-frequency tags, known as “magstripes,” can be used for transactions without extra cryptographic security. However, high-frequency tags transmitting at 13.56 MHz provide distinct transaction security [35].

4.1.9. LPWAN

These networks provide secure low-power connectivity for large-scale public infrastructure sensors. Authentication and AES-based encryption contribute to integrity and protection of remote government telemetry. Their long range and low energy consumption are well suited for secured rural or national-scale monitoring [132].

4.1.10. V2X Communication

V2X systems enable secure data exchange between vehicles and infrastructure, critical for public transport, emergency vehicles, and smart city logistics. Cryptographic signing, misbehavior detection, low-latency secure channels, and secure roadside units (RSUs) reduce risks of spoofing, message tampering, and vehicular cyber-attacks. The rise of IoV and V2X communication platforms poses major cybersecurity risks across all network tiers. Exploiting these weaknesses can result in compromised vehicle safety, user confidentiality, and transportation network reliability [149,150]. Now that cars are mobile computer platforms, secure automotive systems are needed to avoid malicious attacks on safety and data. The strategy limits attack success by forcing attackers to breach physical, network, and device protection.

4.1.11. THz Communication

THz communication offers extremely high-bandwidth secure channels with inherent directional beams, reducing interception probability. This makes it suitable for sensitive government inter-office links, secure sensing, and high-integrity data transfer. Pairing THz with quantum-safe cryptography strengthens future resilience. Cybersecurity worries arise for satellites, since hackers might interrupt key services such as GPS, automobiles, drones, offshore oil and gas activities, and energy grids. Hackers may deorbit and destabilize satellites, creating infrastructure damage and collision hazards. Increased use of ML in communication networks may jeopardize security [139]. Cyberattacks damage data, security secrets, and other vital information.

4.1.12. Quantum Communication

Quantum communication enables ultra-secure communication that is resistant to classical and future quantum attacks. It is ideal for protecting national registries, high-value government secrets, voting systems, and diplomatic or defense communications. Examining error detection, measurement, and correction techniques results in emphasizing the significance of quantum error correction methods in reducing noise and imperfections, thereby ensuring precise quantum information transmission and improving the overall efficiency of quantum communication systems [133]. Traditional symmetric cryptography uses encryption keys for security. If the transmitter and receiver exchange a long string of random secret bits, one-time pad encryption guarantees unconditional security. Safe key exchange between sender and receiver is key distribution’s biggest problem.

4.1.13. DTs

DTs allow simulated testing of cyber-attacks on city infrastructure, enabling proactive resilience planning. They support virtual penetration testing, risk modelling, and scenario-based cyber-incident simulations. Strong interaction between DTs and AI tools can enhance cybersecurity of digital platforms through integration [144]. Latency, reliability, scalability, distribution, and privacy/security are DT quality-of-service necessities. These issues create new challenges and opportunities, making transdisciplinary research more intriguing and important. Medical records, autonomous car data, and smart grid real-time operations data are sensitive DT data categories.

4.1.14. Metaverse/XR

XR technologies provide immersive, secure training environments for cyber-incident response, remote secure collaboration, and digital public service delivery. They require strong identity authentication, encrypted sessions, and secure virtual meeting spaces to prevent impersonation or data leakage. However, the metaverse poses substantial cybersecurity and privacy issues that are still being overlooked. Due to its decentralized and participatory character, the metaverse poses unique security issues [142]. Dynamic virtual worlds, real-time data transport, and device–person interaction comprise the metaverse. Metaverse security research generally addresses user authentication and federated learning without addressing their current state, restrictions, or solutions.

4.1.15. Satellite IoT and Satellite 5G/6G

Satellites extend secure connectivity to remote regions, critical infrastructure, and disaster zones. Technology convergence has created new cybersecurity dangers for traditional and small-satellite infrastructures, notwithstanding its benefits. Satellite transmissions, due to their broadcast nature and wide coverage, are vulnerable to jamming, spoofing, and eavesdropping, making them attractive targets for criminal actors [140]. Developing effective, lightweight security frameworks is crucial to combat attacks across many domains, protocols, and network interaction points. Maintaining satellite security is crucial due to threats such as cyberattacks, physical assaults, and space debris. Satellite security measures include encryption and authentication to prevent unwanted access to communication and control systems [140,151].

To maintain satellite system functionality and security, operators and engineers must monitor satellite security. To prevent cyber threats and security difficulties in traditional Satcom systems, powerful cybersecurity measures are needed due to the distance between Earth and satellites. Key cybersecurity roles in e-government, main security advantages, cybersecurity risks/considerations, and policy and governance implications are summarized in the following Figure 10 [120,132,135,144,147,152,153].

5. Efficiency, Transition, and Consumption (ETC) of Energy in E-Government

In this part, we look at the possibility that government digital transformation is a driving force behind modern energy coordination efficiency gains, energy transition, and consumption. The world’s energy sector is confronted with two unprecedented threats: rising demand and a more severe climate crisis. Total Factor Energy Efficiency (TFEE) has risen to the forefront of global business and government agendas due to these challenges. The unpredictability of fossil fuel prices has intensified recent geopolitical tensions, placing a greater emphasis on the necessity for governments to speed up efficiency improvements and fundamental energy changes [154]. Global efficiency rates remained below 1% in 2020 and showed only slight gains in 2021, indicating that current progress is inadequate. In order to reduce energy prices and greenhouse gas emissions, TFEE augmentation is needed. Doubling these rates is required to achieve net-zero emissions by 2050. The current body of literature delves into TFEE by way of digital transformation, smart city development, and technological innovation [155].

On the other hand, very little is known about how digital transformation in government affects the efficiency of energy allocation. Studies have shown that the ability of the government to provide services impacts TFEE optimization [156], and that the efficacy of resource distribution is determined by the quality of the institution [157]. Moreover, there has not been sufficient research into the specific processes that link digital governance to results in energy efficiency. Energy inefficiencies are associated with low-quality government services, which is why this gap is important. When it comes to management efficiency and policy efficacy, digital governance outperforms traditional administration [9].

From the vantage point of public service provision, academics have started to analyze the monetary effects of digital transformation in government. Government digital transformation optimizes the business climate, streamlines customs clearance and international commerce, and lowers systemic financial risks, all of which contribute to macroeconomic development [158]. Reduced systemic transaction costs are one way in which digital transformation in government affects enterprise productivity at the microeconomic level [159], management’s ESG results [160], and the effectiveness of business investments [161], as well as invention within businesses [162]. When it comes to the government, digital government construction improves things like administrative efficiency, public satisfaction, government integrity, openness, and citizen involvement [163]. The research on the topic of digital transformation in government and its impact on TFEE at the city level is, however, still somewhat sparse.

Developed nations’ ability to invest in green projects, strong institutions, and advanced technology has led studies to focus on factors influencing their green energy transition [164]. Renewable energy innovation is concentrated in EU nations, according to the report [165]. The importance of political and economic elements in the green energy transition has been confirmed by previous research, particularly that which focuses on EU nations (e.g., Tu et al. [165]). Some studies now include worldwide samples including underdeveloped countries. Chaoyi Chen et al. [166] found that institutional quality, economic development, and energy price influence renewable energy use in 97 countries.

Renewable energy deployment is determined by regulatory, political, economic, environmental, energy, and demographic variables, according to Bourcet [167]. Primary economic aspects include income, energy price, financial development, and international flows; the primary environmental factor is emissions; important energy factors are energy consumption, alternative energy resources, and energy security. Regulations include the Kyoto Protocol and government initiatives. Political considerations include government ideology and institutional quality. Lastly, the demographic aspect is the population count. Most empirical research on the topic of green energy transition points to economic and regulatory considerations as the primary drivers of this shift [168,169]. Government assistance [170] and investment in green initiatives [171] are other significant factors, according to the research.

Certain research indicates that e-government can favorably impact environmental sustainability [9]. E-government is regarded as a beneficial element in enhancing the management of environmental protection and expanding the range of policies and programs that promote environmental performance [172]. According to [173], e-government makes the government more effective. On the other hand, Bourcet [167] draws the conclusion from his literature assessment that renewable energy consumption is stimulated by strong institutional quality, particularly by effective governance and ideology supporting the growth of renewable energy. Consequently, the green energy transition may benefit from e-government’s enhanced efficiency. The expenses of transitioning to green energy can be decreased through e-government since it can increase the efficiency of public service delivery [174] and decrease administrative constraints on companies. An increase in investment in green energy projects, crucial to the green energy transition, may result from a decrease in the cost of doing business made possible by the expansion of e-government [171]. Consequently, by facilitating business operations, e-government may positively impact the green energy transition.

The Innovation Diffusion Theory (IDT) provides an explanation for the connection between digitization and energy efficiency. This theory describes how new technologies are accepted and how they impact changes in behavior and institutions [175]. The available data are inconsistent. Digitization can improve energy efficiency, according to recent research [176], by encouraging smart energy management practices and moving activity away from sectors that use a lot of energy. On the other hand, other research [177] found that digitization actually increases energy consumption due to factors including increased server demand, rebound effects associated with behavioral changes, and growing data traffic. One example is the correlation between increased power use and digital development in high-income, service-dominated areas. The rebound effect, or the Jevons Paradox, provides a theoretical explanation for this paradox by positing that, despite efforts to increase energy efficiency, consumption might actually increase due to a decrease in the effective cost of energy usage.

Internet connectivity enables digital platforms, smart systems, and energy monitoring to reduce residential and industrial energy use. These technologies should boost energy efficiency across all industries. Data access in real time is another way mobile cellular subscriptions aid smart energy management. Remotely controlling appliances and improving demand management enhance energy monitoring and response. These adaptable and scalable technologies could help address efficiency challenges stemming from infrastructural limitations in emerging economies that frequently lag behind industrialized nations. Digitization allows renewable energy integration, which optimizes consumption, balances supply and demand, and promotes sustainability, using analytics, IoT devices, and smart grids. Indonesian smart grid initiatives have improved system dependability, user involvement, and efficiency, enabling renewable energy integration.

Industrial, mining, and construction industries make up much of emerging nations’ GDP and depend largely on energy. Traditional, inefficient energy sources hurt these enterprises’ energy usage and efficiency. This is inversely associated with all quantiles because firms of all sizes prioritize production and economic output over conservation. However, many emerging nations are adopting energy-efficient practices and technologies. Due to the dominance of energy-intensive industries, efficiency is dropping across all energy use quantiles.

Commerce openness hurts all expanding economies because international trade requires more energy. Globalization may promote energy-intensive industries like manufacturing, transportation, and logistics. Commercial operations including export manufacturing, intermediate product processing, and infrastructure boost energy use. Liberalized trade increases economic activity and prioritizes cost efficiency and output maximization over energy efficiency. Rising exports and imports may lead to excessive energy consumption due to inefficient production. Trade-driven industrialization may prioritize cost and speed above sustainability, especially in places with poor environmental standards. Inefficient global supply systems use fossil fuels. Due to global commerce’s energy-intensive manufacturing and logistics, trade openness and energy efficiency are negatively correlated.

Table 6. Summary of recent contributions of technologies for ETC.

Ref.	Year	Journal	Technology	Description
[178]	2023	IEEE Open Journal of the Communications Society	5G/6G	Proposed a cooperative energy-efficient routing protocol (CEEPR) for 5G/6G WSNs to facilitate sustainable communication. In the beginning, the data were collected at the sink node for this study. Using the reinforcement learning (R.L.) approach, the network’s nodes are grouped. To improve data transmission, a cluster head selection technique based on residual energy (RE) is used. CEERP is presented as a collaborative energy-efficient routing protocol. In order to optimize the system and make it more efficient, they utilized a multi-objective improved seagull algorithm (MOISA).
[179]	2025	Energy Informatics	Edge computing and ML	Designed and refined a decentralized energy control system using edge computing and ML. Real-time data processing and analysis on edge devices reduces transmission latency and improves energy allocation. Distributed energy systems get smarter and more sustainable as energy prices drop. This research uses edge computing and ML to minimize computing load and delay, optimize distributed energy system control in real time, and increase data-driven energy management accuracy and flexibility.
[180]	2025	Energy	OWC	Using a parabolic structure can increase wave energy concentration in defined places, improving wave energy converter (WEC) energy collection efficiency. This study examines the wave environment around parabolic structures and the wave energy capture capability of OWC devices connected with them. This study found a vertex concentration mode of wave energy near the parabolic structure’s vertex in the low-frequency range. Significant wave energy concentration around the geometric focal point of the parabolic structure, called focal concentration mode, grows with wave frequency. The results show that an OWC device with a parabolic structure captures wave energy better than in open water. The high wave energy concentration and resonant water-column motion in the chamber maximize wave energy collection.
[181]	2025	IEEE Internet of Things Journal	UAV	The low energy and storage capacity of UAVs makes persistent and diversified multimedia transmission difficult. This work offers a multi-UAV-enabled coded caching technique for energy-efficient data delivery that meets communication coverage and cache hit objectives. Considering user mobility and preferences, they devised an energy minimization problem that optimized coding vectors, caching variables, user grouping, and updated UAV positions. Based on user locations, they deployed UAVs using a limited K-means clustering method and evaluated its efficacy with the silhouette coefficient. Their solution was a multi-UAV-enabled coded caching optimization (MUCCO) technique with a unique projected distance-based user grouping mechanism, semidefinite programming (SDP), and matching theory.
[182]	2022	IEEE Open Journal of the Communications Society	UAV, V2X	V2X networks bypass vehicle sensors’ restricted sensing range and ensure safe driving with flexibly deployed UAVs. This research presents energy-efficient computation offloading for multiple-sensor data fusion in UAV-aided V2X networks with integrated sensing and communication. First, a vehicle–UAV cooperative perception architecture is provided for various traffic scenarios. Second, a computation offloading technique that combined offloading choices with dynamic computing resource allocation is proposed. A sequential convex approximation (SCA) approach turns a non-convex formulation issue into a tractable one.
[183]	2022	IEEE Transactions on Communications	Terahertz comm.	Added downlink non-orthogonal multiple access (NOMA) to THz band small cell networks to maximize performance with the two primary enabling technologies. To reduce energy consumption caused by wireless services, they optimized energy efficiency (EE) and resource allocation in THz-NOMA downlink systems by addressing subchannel assignment and power optimization. First, they use THz-NOMA network properties to exploit a channel model for the downlink system. The resource allocation issue is solved and decomposed into two subproblems using Dinkelbach-style technique. A subchannel assignment technique and an ADMM-based power optimization approach are used to solve the problem.
[184]	2023	IEEE Transactions on Communications,	Satellite-6G	Examines the problem of satellite–terrestrial computing in 6G wireless networks, where Earth-based base stations (BSs) and satellites in LEO work together to supply edge computing services to GUEs and SUEs all over the globe. Using the features of 6G wireless networks as a guide, they developed a comprehensive mechanism for computation and communication between satellites and Earth. An energy-efficient approach for satellite–terrestrial computing is proposed, which optimizes offloading selection, beamforming design, and resource allocation simultaneously to reduce the weighted total energy consumption while ensuring computing workloads’ latency requirements.

shows recent contributions of technologies for ETC that can support e-government.

The Role of Key Emerging Technologies in the ETC of Energy in E-Government

The evolution of e-government is closely coupled with the digital transformation of energy systems, where emerging communication, computing, and intelligence technologies play a pivotal role in enabling energy-aware, efficient, and sustainable public services. Modern e-government platforms increasingly depend on advanced wireless networks, pervasive sensing, distributed computing, and intelligent data analytics to support the ETC of energy across public infrastructure and services.

Technology allows fine-grained energy monitoring, real-time optimization, secure energy transactions, and seamless renewable and low-carbon resource integration. These technologies help governments cut operational energy costs, improve energy resilience, and achieve long-term sustainability goals when combined with DTs, metaverse/XR environments, and next-generation communication paradigms. Designing scalable, energy-efficient, and future-ready e-government ecosystems requires understanding each developing technology’s energy contribution. Figure 11 [62,185,186,187,188,189,190,191,192,193] presents an integrated conceptual framework illustrating the role of key emerging technologies in enabling ETC within e-government platforms and public services. At the core of the framework, e-government platforms orchestrate data-driven policy execution, operational efficiency, and low-carbon energy transition by leveraging advanced communication, computing, and intelligence infrastructures. By combining next-gen wireless networks with new technologies, this design demonstrates how these areas may work together to facilitate safe decentralized energy trading, demand forecasting, load balancing, real-time analytics, predictive maintenance, and fine-grained energy monitoring. In addition, the model shows how satellite connectivity, UAV-based monitoring, and the IoT provide robust and scalable energy management by providing ubiquitous situational awareness across urban and rural infrastructures. DTs and XR environments allow for immersive planning, simulation, and training; blockchain and quantum communication layers provide safe transactions, trustworthy coordination, and tamper-proof data sharing.

E-government is digitizing alongside energy systems. Modern e-government platforms use data-driven technology, advanced computation, and communication to provide scalable, secure, and long-term public services. Integrating these technologies may optimize energy usage, smooth the transition to low-carbon systems, and boost energy efficiency in government operations and public infrastructure. This section discusses how each developing technology boosts e-government energy ETC. Figure 12 [178,182,184,186,192,194,195,196,197,198,199,200,201,202,203] illustrates a comprehensive technology–energy mapping framework, demonstrating how each enabling technology contributes to optimized operations (energy efficiency), renewable and sustainable system integration (energy transition), and demand-side control (energy consumption) in e-government platforms.

6. Comparative Analysis

Table 7. Comparative analysis of technologies including various aspects.

Technology	Technology Maturity	Deployment Readiness in Smart Cities	Cross-Sector Suitability (Governance Domains)
5G	High (commercially deployed)	High (widely deployed in urban areas)	Public safety, transport, healthcare, utilities, citizen portals
6G	Low (research and early standardization)	Low (experimental phase)	Advanced DTs, holographic services, AI-native governance
IoT	High (mature ecosystem)	High (broad smart city adoption)	Utilities, environment, infrastructure, mobility
Edge/Fog Computing	Medium–high (commercial solutions with expanding edge infrastructure)	Medium–high (growing deployment)	Public safety, utilities, AI services, data privacy
AI/ML	High (widely implemented)	High (integrated in many services)	Fraud detection, traffic, urban planning, predictive governance
Blockchain/DLT	Medium (pilot deployments and evolving regulatory frameworks)	Medium (pilot and niche deployments)	Digital identity, land registry, procurement, voting
Quantum Communication	Low (experimental)	Low (limited pilot networks)	Critical infrastructure protection
LiFi/OWC	Medium (commercially available but niche adoption)	Medium (indoor and specialized deployments)	Government buildings, hospitals, secure facilities
UAVs	High (commercially operational with established regulations)	High (operational in many cities)	Surveillance, disaster response, inspection
RFID/NFC	High (standardized, low-cost, mass-market adoption)	High (mature and low cost)	Access control, asset tracking, transport ticketing
LPWAN	High (standardized and widely deployed for IoT networks)	High (large-scale IoT support)	Utilities, waste, environmental sensing
V2X	Medium (early commercial deployment with ongoing standardization)	Medium (expanding in its ecosystems)	Transport management, emergency response
THz Communication	Low (laboratory research and pre-commercial trials)	Low (laboratory/early trials)	Holographic services, high-capacity backhaul
DTs (City-Scale)	Medium (growing municipal adoption with integration challenges)	Medium (growing municipal adoption)	Urban planning, disaster simulation, infrastructure optimization
Metaverse/XR	Medium (emerging platforms with pilot public-sector use cases)	Medium (emerging pilots)	Public consultation, training, virtual services
Satellite IoT/Satellite 5G/6G	Medium (commercial expansion with evolving standards integration)	Medium (expanding global coverage)	Rural governance, disaster recovery, environmental monitoring

presents a comparative analysis across technologies, emphasizing maturity level, deployment readiness, and cross-sector applicability within the framework of smart city-enabled e-government.

When it comes to technological maturity, practical deployment preparedness, and governance-sector compatibility, Table 7 ranks each technology in a comparative manner, going beyond descriptive explanations. All technologies are categorized according to their current level of development and commercialization in the “Technology Maturity” category. The maturity evaluation considers market preparedness, institutional integration, ecosystem stability, and global standards, not just technological capacity. These four main factors form the basis of the classification (High, Medium, Low): (i) the current state of standardization, (ii) the availability for commercial use, (iii) the maturity of the ecosystem and vendors, and (iv) the validation of large-scale operations.

Many smart cities use these technologies to provide e-government services, including traffic control, digital identification, predictive maintenance, and citizen interaction platforms. The estimation given for each technology can be summarized as follows:

(i)

Low Maturity: This includes limited or no commercial deployment, laboratory or controlled pilot validation, incomplete standards and regulatory frameworks, high technical uncertainty, and dependence on future breakthroughs. These innovative technologies are long-term and not yet in use.

(ii)

Medium Maturity: Commercially accessible but developing. Classification shows sector-specific or pilot-heavy deployments rather than widespread acceptance; technical feasibility proved, but scalability, interoperability, or regulatory clarity still emerging, optimizing and growing the ecosystem. Though no longer experimental, they are not fully stable across governance contexts.

(iii)

High Maturity: Known for their worldwide standards and regulatory frameworks, fully marketed goods and services, widespread industry and governmental acceptance, and proven scalability and long-term operating success. Real-world infrastructures use these technologies after pilot testing.

These allow ultra-secure, ultra-high-capacity, and AI-native governance infrastructures but are still in the research or trial phases. This comparative synthesis shows that smart city e-government requires layered integration, integrating established solutions for operational stability with emergent innovations for long-term change.

7. Conclusions

This paper examined the evolving landscape of e-government through the lens of wireless and emerging technologies, emphasizing their collective role in enabling advanced, interconnected public-sector systems. A broad set of technologies was considered, including 5G and 6G networks, IoT, edge and fog computing, blockchain and DLTs, artificial intelligence and ML, OWC and LiFi, unmanned aerial vehicles, RFID, NFC and smart tagging, LPWAN, vehicle-to-everything communication, THz communication, quantum communication, city DTs, metaverse and extended reality, as well as satellite IoT and satellite 5G/6G. Rather than treating these technologies as isolated components, the study highlighted their interaction within e-government environments spanning smart cities, sustainability, cybersecurity, and energy-related applications.

The analysis revealed that the integration of heterogeneous communication, computation, and intelligence layers introduces new technical, organizational, and governance challenges that directly influence system reliability, security, and long-term operability. Issues related to interoperability, scalability, data governance, trust, and regulatory alignment remain critical barriers to effective deployment. At the same time, the findings indicate that coordinated adoption strategies and cross-domain system design are essential to realizing coherent and resilient e-government infrastructures. This study thoroughly addressed the five RQs to provide a complete picture of wireless and developing technologies in e-government, summarized as follows:

• According to the report, few nations have implemented new technology for e-government services and applications. Studies focus on conceptual frameworks, architectural models, and prototype systems, with few large-scale real-world deployments. Recent adoption trends are optimistic; however, many technologies are still in development and underused owing to organizational, legislative, and infrastructural obstacles. Region-specific e-government ecosystem maturity affects technology dissemination and service integration.
• Traditional wireless communication technologies, IoT platforms, and UAV-based systems are the most commonly accepted and theoretically supported due to their technological maturity and practicality. Due to implementation complexity, legal constraints, energy problems, and integration issues, blockchain, AI, and LiFi remain underexplored. This indicates a research void in theoretical and operational models for next-generation e-government systems.
• Despite all developing technologies contributing to smart city growth in e-government ecosystems, some have higher practical impact and implementation readiness. Wireless communication, IoT, and edge–cloud computing suit real-time monitoring, intelligent transportation, and resource optimization well. Artificial intelligence improves data-driven decision-making and automation, notably in sustainability and energy optimization. Blockchain, quantum communication, and LiFi, while promising, are not widely used due to integration complexity, legislative limits, and infrastructure preparedness. These findings show how developing technologies differ in smart city, sustainability, cybersecurity, and energy management.
• The study found that high deployment and operational costs, interoperability issues, data privacy and security risks, regulatory and governance barriers, technical expertise gaps, infrastructure limitations, and energy consumption concerns hinder large-scale adoption. Reduced public trust, organizational resistance to change, and weak policy frameworks aggravate these issues. Strategic proposals include standardizing interoperability frameworks, tightening cybersecurity and privacy rules, investing in workforce training, improving infrastructure preparedness, and using energy-efficient system designs.
• Finally, this work reviews and synthesizes the literature to propose a collaborative technical e-government technique. The framework shows how coordinated technology deployment can support service automation, cybersecurity, sustainable energy management, and smart city development by systematically integrating wireless networks, IoT, AI, edge–cloud computing, blockchain, and advanced communication paradigms. This conceptual technique provides a structured reference model for developing scalable, secure, energy-efficient e-government ecosystems that promote interoperability, resilience, and sustainability.

Future work will focus on (i) incorporating quantitative performance evaluation metrics to assess the effectiveness of the investigated technologies, including latency, scalability, energy efficiency, and security impact, and (ii) investigating which technologies and system architectures are most suitable for specific e-government contexts, along with the underlying factors driving their effectiveness.