Search Results (237)

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT), known as Artificial Intelligence of Things (AIoT), has emerged as a transformative paradigm for enabling intelligent, data-driven, and context-aware decision-making in urban environments to reduce the carbon footprint of mobility and industry. This review examines the conceptual foundations, and state-of-the-art developments of AIoT, with a particular emphasis on its applications in smart cities and its relevance to climate change management. AIoT integrates sensing, connectivity, and intelligent analytics to provide optimized solutions in transportation systems, energy management, waste collection, and environmental monitoring, directly influencing urban sustainability. Beyond urban efficiency, AIoT can play a critical role in addressing the global challenges and management of climate change by (a) precise measurements and autonomously remote monitoring; (b) real-time optimization in renewable energy distribution; and (c) developing prediction models for early warning of climate disasters. This paper performs a literature review and bibliometric analysis to identify the current landscape of AIoT research in smart city contexts. Over 1885 articles from Web of Sciences and over 1854 from Scopus databases, published between 1993 and January 2026, were analyzed. The results reveal a strong and accelerating growth in research activity, with publication output doubling in the most recent two years compared to 2023. Waste management and air quality monitoring have emerged as leading application domains, where AIoT-based optimization and predictive models demonstrate measurable improvements in operational efficiency and environmental impact. Altogether, these support faster and more effective decisions for reducing greenhouse gas emissions and ensuring the sustainable use of resources. The reviewed studies reveal rapid advancements in edge intelligence, federated learning, and secure data sharing through the integration of AIoT with blockchain technologies. However, significant challenges remain regarding scalability, interoperability, privacy, ethical governance, and the effective translation of research outcomes into policy and citizen-oriented tools such as climate applications, insurance models, and disaster alert systems. By synthesizing current research trends, this article highlights the potential of AIoT to support sustainable, resilient, and citizen-centric smart city ecosystems while identifying both critical gaps and promising directions for future investigations. Full article

Fulgides are a class of organic compounds that exhibit photochromic behavior in both the solid state and in solution. These compounds have attracted considerable research interest due to their wide range of potential applications, including photochromic eyewear, smart windows, optical switches, data storage, and chemical and biological sensors. Here, we report the synthesis and crystal structures of fulgides bearing four different para-substituents on the phenyl moiety. All four molecules crystallize in space groups containing an inversion center. The distances between the two carbon atoms that would form the single C–C bond in the cyclized products fall within the range of 3.301–3.475 Å. The observed structural variations are attributed to intermolecular interactions based on Hirshfeld surface analysis. The fulgides exhibit photochromism, but they are not expected to display ferroelectric behavior due to their crystallization in centrosymmetric space groups. Full article

The increasing electrification of mobility within smart cities has accelerated the need for intelligent energy management strategies that jointly address cost, emissions, and battery health. This study develops a health-aware hybrid reinforcement–predictive energy manager (H-RPEM) designed for photovoltaic–electric vehicle (PV-EV) microgrids. The proposed controller unifies model-based predictive optimisation with adaptive reinforcement learning to achieve both short-term operational efficiency and long-term asset preservation. A comprehensive dataset of solar generation, EV charging behaviour, and stochastic load profiles was employed to train and validate the hybrid control framework under realistic operating conditions. Quantitative results indicate that the proposed H-RPEM controller achieves an 18.7% reduction in total operating cost and a 22.5% decrease in carbon emissions, whilst maintaining the battery state-of-health above 0.95 throughout a 24 h operational cycle. When benchmarked against standard predictive control, the hybrid strategy converges 30–40 episodes faster and delivers a 25% improvement in reward stability, demonstrating enhanced robustness and learning efficiency. The results confirm that H-RPEM achieves robust and balanced performance across economic, environmental, and technical domains, establishing it as a scalable and health-conscious control solution for next-generation smart city microgrids. Full article

The continuous advancement of modern weaponry has intensified the pursuit of next-generation ballistic protection systems that integrate lightweight architectures, superior flexibility, and high energy absorption efficiency. This review provides a technological overview of current trends in the design, processing, and performance optimization of metallic, ceramic, polymeric, and composite materials for ballistic applications. Particular emphasis is placed on the role of advanced surface coatings and nanostructured interfaces as enabling technologies for improved impact resistance and multifunctionality. Conventional materials such as high-strength steels, alumina, silicon carbide, boron carbide, Kevlar^®, and ultra-high-molecular-weight polyethylene (UHMWPE) continue to dominate the field due to their outstanding mechanical properties; however, their intrinsic limitations have prompted a transition toward nanotechnology-assisted solutions. Functional coatings incorporating nanosilica, graphene and graphene oxide, carbon nanotubes (CNTs), and zinc oxide nanowires (ZnO NWs) have demonstrated significant enhancement in interfacial adhesion, inter-yarn friction, and energy dissipation. Moreover, multifunctional coatings such as CNT- and laser-induced graphene (LIG)-based layers integrate sensing capability, electromagnetic interference (EMI) shielding, and thermal stability, supporting the development of smart and adaptive protection platforms. By combining experimental evidence with computational modeling and materials informatics, this review highlights the technological impact of coating-assisted strategies in the evolution of lightweight, high-performance, and multifunctional ballistic armor systems for defense and civil protection. Full article

Intelligent Transportation Systems (ITSs) aim to improve mobility and reduce congestion, yet current solutions still struggle with scalability, sensing bottlenecks, and inefficient computational resource usage. These limitations impede the shift towards environmentally responsible mobility. This work introduces ORQCIAM (Orchestrated Reasoning based on Quantum Computing and Intelligence for Advanced Mobility), a modular framework that combines Quantum Computing (QC) and Large Language Models (LLMs) to enable real-time, energy-aware decision-making in ITSs. Unlike conventional ITS or AI-based approaches that focus primarily on traffic performance, ORQCIAM explicitly incorporates sustainability as a design objective, targeting reductions in travel time, fuel or energy consumption, and CO₂ emissions. The framework unifies cognitive, virtual, and federated sensing to enhance data reliability, while a hybrid decision layer dynamically orchestrates QC–LLM interactions to minimize computational overhead. Scenario-based evaluation demonstrates faster incident screening, more efficient routing, and measurable sustainability benefits. Across tested scenarios, ORQCIAM achieved 9–18% reductions in travel time, 6–14% lower estimated CO₂ emissions, and around a 50–75% decrease in quantum-optimization calls by concealing QC activation during non-critical events. These results confirm that dynamic QC–LLM coordination effectively decreases computational overhead while supporting greener and more adaptive mobility patterns. Overall, ORQCIAM illustrates how hybrid QC–LLM architectures can serve as catalysts for efficient, low-carbon, and resilient transportation systems aligned with sustainable smart-city goals. Full article

The transition to electric vehicles (EVs) plays a critical role in reducing global carbon emissions. However, the end-of-life management of electric vehicle batteries (EVBs) presents significant sustainability and operational challenges. This study proposes a blockchain-based framework that enables full lifecycle tracking of EVBs, from production to disposal or reuse, while addressing issues of transparency, efficiency, and regulatory compliance. The framework incorporates a multi-criteria decision model to guide data-driven end-of-life routing—whether for second-life reuse or direct recycling—based on technical, environmental, and economic indicators. By integrating smart contracts with a hybrid web/mobile platform, the system ensures tamper-proof documentation, stakeholder accountability, and compliance with the EU battery passport regulation. A detailed cost analysis of deploying the framework on Ethereum is also presented. The proposed solution aims to enhance the sustainability of EVB management, reduce environmental impact, and promote circular economy practices within the EV industry. Full article

Understanding how carbon is stored and stabilized in temperate agricultural soils is central to addressing one of the defining environmental challenges of our time—climate change. In this review, we bridge quantitative bibliometric insights with a qualitative synthesis of the mechanisms, regional differences, management practices, and models governing soil organic carbon (SOC) dynamics. We systematically analyzed 481 peer-reviewed publications published between 1990 and 2024, retrieved from Scopus and Web of Science, using bibliometric tools such as VOSviewer to map research trends, collaboration networks, and thematic evolution. The bibliometric analysis revealed a marked increase in publications after 2010, coinciding with growing global interest in climate-smart agriculture and carbon sequestration policies. Comparative synthesis across temperate sub-regions—such as the humid temperate plains of Europe, the semi-arid temperate zones, and the temperate black soil region of Northeast China—reveals that the effectiveness of common practices varies with soil mineralogy, texture, moisture regimes, and historical land-use. Reduced tillage (average SOC gain of 0.25 Mg C ha⁻¹ yr⁻¹), cover cropping (0.32 Mg C ha⁻¹ yr⁻¹), and organic amendments such as compost and biochar (up to 1.1 Mg C ha⁻¹ yr⁻¹) consistently enhance SOC accumulation, but with region-specific outcomes driven by these contextual factors. Recognizing such heterogeneity is essential for developing regionally actionable management recommendations. Recent advances in machine learning, remote sensing, and process-based modeling are enabling more accurate and scalable monitoring of SOC stocks, yet challenges remain in integrating micro-scale stabilization processes with regional and global assessments. To address these gaps, this review highlights a multi-method integration pathway—combining field measurements, mechanistic modeling, data-driven approaches, and policy instruments that incentivize adoption of evidence-based practices. By combining quantitative bibliometric analysis with regionally informed mechanistic synthesis, this review provides a holistic understanding of how knowledge about SOC in temperate agroecosystems has evolved and where future opportunities lie. The findings underscore that temperate agricultural soils, when supported by appropriate scientific practices and enabling policy frameworks, represent one of the most accessible natural climate solutions for advancing climate-resilient and sustainable food systems. Full article

Soil degradation and pollution pose significant threats to global agricultural sustainability and food security. Conventional remediation methods are often constrained by low efficiency, high cost, and potential secondary pollution. Nanobiotechnology, an emerging interdisciplinary field, offers innovative solutions by integrating functional nanomaterials with plant–microbe interactions to advance soil remediation and sustainable agriculture. This review systematically elaborates on the mechanisms and applications of nanomaterials in soil remediation and enhanced plant stress resilience. For contaminant removal, nanomaterials such as nano-zero-valent iron (nZVI) and carbon nanotubes effectively immobilize or degrade heavy metals and organic pollutants through adsorption, catalysis, and other reactive mechanisms. In agriculture, nanofertilizers facilitate the regulated release of nutrients, thereby markedly enhancing nutrient use efficiency. Concurrently, certain nanoparticles mitigate a range of abiotic stresses—such as drought, salinity, and heavy metal toxicity—through the regulation of phytohormone balance, augmentation of photosynthetic performance, and reinforcement of antioxidant defenses. However, concerns regarding the environmental behavior, ecotoxicity, and long-term safety of nanomaterials remain. Future research should prioritize the development of smart, responsive nanosystems, elucidate the complex interactions among nanomaterials, plants, and microbes, and establish comprehensive life-cycle assessment and standardized risk evaluation frameworks. These efforts are essential to ensuring the safe and scalable application of nanobiotechnology in environmental remediation and green agriculture. Full article

The increasing complexity of urban energy systems requires decentralized, sustainable, and scalable solutions. The paper presents a new multi-layered framework for smart energy management in microgrids by bringing together advanced forecasting, decentralized decision-making, evolutionary optimization and blockchain-based coordination. Unlike previous research addressing these components separately, the proposed architecture combines five interdependent layers that include forecasting, decision-making, optimization, sustainability modeling, and blockchain implementation. A key innovation is the use of Temporal Fusion Transformer (TFT) for interpretable multi-horizon forecasting of energy demand, renewable generation, and electric vehicle (EV) availability which outperforms conventional LSTM, GRU and RNN models. Another novelty is the hybridization of Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), to simultaneously support discrete and continuous decision variables, allowing for dynamic pricing, efficient energy dispatching and adaptive EV scheduling. Multi-Agent Reinforcement Learning (MARL) which is improved by sustainability shaping by including carbon intensity, renewable utilization ratio, peak to average load ratio and net present value in agent rewards. Finally, Ethereum-based smart contracts add another unique contribution by providing the implementation of transparent and tamper-proof peer-to-peer energy trading and automated sustainability incentives. The proposed framework strengthens resilient infrastructure through decentralized coordination and intelligent optimization while contributing to climate mitigation by reducing carbon intensity and enhancing renewable integration. Experimental results demonstrate that the proposed framework achieves a 14.6% reduction in carbon intensity, a 12.3% increase in renewable utilization ratio, and a 9.7% improvement in peak-to-average load ratio compared with baseline models. The TFT-based forecasting model achieves RMSE = 0.041 kWh and MAE = 0.032 kWh, outperforming LSTM and GRU by 11% and 8%, respectively. Full article

The built environment contributes approximately 25% of the UK’s total greenhouse gas emissions, positioning it as a critical sector in the national net-zero strategy. This review investigates the enabling role of the domestic smart metering infrastructure combined with other IoT systems in accelerating the decarbonisation of residential buildings. Drawing from experience gained from governmental and commercially funded R&D projects, the article demonstrates how smart metering data can be leveraged to assess building energy performance, underpin cost-effective carbon reduction solutions, and enable energy flexibility services for maintaining grid stability. Unlike controlled laboratory studies, this review article focuses on real-world applications where data from publicly available infrastructure is accessed and utilised, enhancing scalability and policy relevance. The integration of smart meter data with complementary IoT data—such as indoor temperature, weather conditions, and occupancy—substantially improves built environment digital energy analytics. This capability was previously unattainable due to the absence of a nationwide digital energy infrastructure. The insights presented in this work highlight the untapped potential of the UK’s multibillion-pound investment in smart metering, offering a scalable pathway for low-carbon innovation for the built environment, thus supporting the broader transition to a net-zero future. Full article

In recent years, the use of Unmanned Aerial Vehicles (UAVs) has been widely investigated, with particular attention to their potential applications within smart city initiatives. In urban areas, UAV-based delivery services are expected to help address the shortage of truck drivers while also contributing to the promotion of carbon neutrality. Furthermore, the use of multiple UAVs as a communication platform through multi-hop UAV relaying has been studied. UAV-based communication platforms are gaining attention as cost-effective solutions in regions where deploying terrestrial base stations is challenging, such as mountainous areas and remote islands, as well as in emergency situations like natural disasters. Among UAV-based communication platforms, multi-hop UAV relaying is attracting attention as an effective means. However, when employing multi-hop UAV relaying, challenges arise in scenarios where the distance between the source and destination is large, including increased costs due to the need for a larger number of UAVs and reduced throughput caused by the increase in hop count. To address these issues, this paper proposes a flight path design for UAVs in a multi-hop communication system utilizing delivery UAVs, aiming to improve throughput between destinations. The proposed method targets communication between a source and multiple destinations by strategically placing relay points (Way Points: WPs) along the flight paths. By routing UAVs through WPs, new communication links are established, enabling the direct construction of networks between destinations. This approach reduces the number of hops and ensures stable communication at a constant speed. For WP placement algorithms, we propose two methods: a centroid-based method and a shortest-communication-distance-based method. Simulation results demonstrate that the proposed approach enhances throughput. Full article

The transition to sustainable urban mobility requires innovative solutions optimising electric vehicle (EV) ecosystems while integrating seamlessly with smart urban grids. This paper proposes a decentralised framework leveraging adaptive algorithms, vehicle-to-grid (V2G) technology, and renewable energy prioritisation to enhance urban sustainability without requiring new infrastructure. By integrating federated learning (FL) for privacy-preserving coordination, multi-objective optimisation for load balancing, and predictive models for renewable energy integration, our approach addresses energy demand, grid stability, and environmental impact in urban areas. Validated through simulations on an IEEE 39-bus urban feeder and real-world urban mobility case studies, the framework achieves a 40% reduction in carbon emissions, improves grid reliability by 20%, and enhances renewable utilisation by 25% compared to an uncoordinated charging baseline. These outcomes support urban planning by informing smart grid design, reducing urban heat island effects, and promoting equitable mobility access. This work provides actionable strategies for policymakers, urban planners, and energy providers to advance more sustainable, electrified urban ecosystems. Full article

The Lake Velence watershed faces increasing challenges driven by local and global factors, including the impacts of climate change, energy resource limitations, and greenhouse gas emissions. These issues, particularly acute in water management, are exacerbated by prolonged droughts, growing population pressures, and shifting land use patterns. Such dynamics strain the region’s scarce water resources, negatively affecting the environment, tourism, recreation, agriculture, and economic prospects. Nadap, a hilly settlement within the watershed, experiences frequent flooding and poor water retention, yet it also boasts the highest solar panel capacity per property in Hungary. This research addresses these interconnected challenges by designing a solar-hydrodynamic network comprising four multi-purpose water reservoirs. By leveraging the settlement’s solar capacity and geographical features, the reservoirs provide numerous benefits to local stakeholders and extend their impact far beyond their borders. These include stormwater management with flash flood mitigation, seasonal green energy storage, water security for agriculture and irrigation, wildlife conservation, recreational opportunities, carbon-smart winery developments, and the creation of sustainable blue-green settlements. Reservoir locations and dimensions were determined by analyzing geographical characteristics, stormwater volume, energy demand, solar panel performance, and rainfall data. The hydrodynamic system, modeled in Matlab, was optimized to ensure efficient water usage for irrigation, animal hydration, and other needs while minimizing evaporation losses and carbon emissions. This research presents a design framework for low-carbon and cost-effective solutions that address water management and energy storage, promoting environmental, social, and economic sustainability. The multi-purpose use of retained rainwater solves various existing problems/challenges, strengthens a community’s self-sustainability, and fosters regional growth. This integrated approach can serve as a model for other municipalities and for developing cost-effective inter-settlement and cross-catchment solutions, with a short payback period, facing similar challenges. Full article

Electromagnetic interference (EMI) represents a growing challenge in the modern era, as electronic systems and wireless technologies become increasingly integrated into daily life. This review provides a comprehensive overview of EMI, beginning with its historical evolution over centuries, from early power transmission systems and industrial machinery to today’s complex environment shaped by IoT, 5G, smart devices, and autonomous technologies. The diverse sources of EMI and their wide-ranging effects are examined, including disruptions in electrical and medical devices, ecological impacts on wildlife, and potential risks to human health. Beyond its technical and societal implications, the economic dimension of EMI is explored, highlighting the rapid expansion of the global shielding materials market and its forecasted growth driven by telecommunications, automotive, aerospace, and healthcare sectors. Preventative strategies against EMI are discussed, with particular emphasis on the role of advanced materials. Carbon-based nanomaterials—such as graphene, carbon nanotubes, and carbon foams—are presented as promising solutions owing to their exceptional conductivity, mechanical strength, tunable structure, and environmental sustainability. By uniting perspectives on EMI’s origins, consequences, market dynamics, and mitigation strategies, this work underscores the urgent need for scalable, high-performance, and eco-friendly shielding approaches. Special attention is given to recent advances in carbon-based nanomaterials, which are poised to play a transformative role in ensuring the safety, reliability, and sustainability of future electronic technologies. Full article

This paper provides a comprehensive review of Type IV hydrogen tanks, with a focus on materials, manufacturing technologies and structural issues related to high-pressure hydrogen storage. Recent advances in the use of advanced composite materials, such as carbon fibers and polyamide liners, useful for improving mechanical strength and permeability, have been reviewed. The present review also discusses solutions to reduce hydrogen blistering and embrittlement, as well as exploring geometric optimization methodologies and manufacturing techniques, such as helical winding. Additionally, emerging technologies, such as integrated smart sensors for real-time monitoring of tank performance, are explored. The review concludes with an assessment of future trends and potential solutions to overcome current technical limitations, with the aim of fostering a wider adoption of Type IV tanks in mobility and stationary applications. Full article