Search Results (89)

This article examines how smart cities can act as catalysts for enterprise development by integrating technological, infrastructural, governance and human capital dimensions into a coherent urban innovation ecosystem. Drawing on an extensive literature review, the study first conceptualizes smart cities as adaptive systems that combine physical infrastructure, digital data layers, and institutional frameworks, creating conditions for knowledge spillovers, entrepreneurial opportunities, and business model innovation. Empirically, the research is based on an expert survey conducted among 54 specialists from academia, business, and public administration, who assessed the importance of technological, infrastructural, governance, innovation ecosystem, and human capital factors for enterprise development in the context of smart cities. The results suggest that advanced digital technologies, smart infrastructure, open data, R&D support, startup programs and talent development are perceived by experts as key, mutually complementary drivers of firms’ innovation, efficiency, sustainable growth, and competitiveness, with notable differences between expert groups. On this basis, the study proposes a synthetic model of relationships and impact pathways linking smart city components with enterprise outcomes. The paper concludes with a discussion of the study’s limitations, related to the expert-based, country-specific, and perceptional character of the data, and outlines directions for further quantitative and qualitative research on the firm-level effects of smart city development. Full article

Digital twins (DTs) enable innovation across industries. While business discourse promotes DTs as catalysts for new business models, the academic literature lacks a cohesive understanding of how DTs enable different types of business innovation and what distinguishes cross-organizational innovation from firm-level innovation. This paper conducts a systematic literature review of 60 articles, analyzing 25 business innovation cases through a typology derived from established frameworks extended to address cross-organizational innovation. Process innovation appeared in nearly all the cases (24 of 25), confirming DTs’ fundamental role as operational technology. Product innovation manifests in two patterns: the twin as offering and the twin enabling offerings. paradigm innovation appeared in over half of cases, taking context-specific forms including business model transformation, governance mechanisms, and organizational restructuring. Beyond-firm innovation clusters in healthcare, smart cities, sustainability transitions, and energy systems where cross-organizational coordination is required. Beyond-firm cases consistently co-occur with paradigm innovation and exhibit higher innovation type diversity than single-firm cases, suggesting that cross-boundary coordination requires accompanying organizational restructuring. The study contributes a Digital Twin Innovation Typology extending established frameworks to capture innovation no single firm can achieve alone. Practical implications address how domain context shapes innovation potential and coordination mechanisms required for beyond-firm innovation. Full article

The Industrial Metaverse (IM) integrates digital twins, IoT, AI, and immersive technologies to create interconnected, data-driven production environments. While its potential for enhancing efficiency and collaboration is widely acknowledged, its operationalization, particularly in alignment with sustainability goals, remains underexplored. This paper investigates how manufacturing firms transition from isolated pilots to strategic adoption of IM technologies, using a Digital Maturity Model as an analytical lens. Drawing on two industrial case studies, a university-based smart production lab, and expert roundtable discussions, we identify key barriers such as interoperability, governance, and skills gaps, alongside opportunities for circular material flows and resource optimization. Based on these insights, we propose three pathways for implementation: (1) digital maturity and Infrastructure Readiness, (2) organizational transformation for metaverse-enabled workflows, and (3) strategic value realization through sustainable business models. The study contributes a roadmap for managers and policymakers seeking to leverage the IM as a catalyst for resilience, circularity, and long-term competitiveness in smart manufacturing ecosystems. Full article

Artificial intelligence (AI) is increasingly embedded in smart city strategies, yet its role in advancing participatory urban planning remains underexamined, particularly in rapidly urbanizing metropolitan contexts of the Global South. This exploratory, governance-centered study investigates how AI can support participatory urban planning for sustainable smart cities, emphasizing institutional mediation and trust dynamics. Using a convergent mixed-methods design, the research combines a purposive stakeholder survey (n = 260) with qualitative thematic analysis to assess AI awareness and use, participation quality, institutional and technical readiness, and public trust in the Dammam Metropolitan Area, Saudi Arabia. The findings reveal a participation paradox: relatively high AI awareness and digital readiness coexist with low perceived influence and limited confidence in participatory outcomes. Institutional coordination gaps, skill constraints, and regulatory ambiguity mediate the translation of AI adoption into meaningful engagement. Stakeholders favor AI applications, such as interactive mapping, predictive analytics, and digital twin visualization, that enhance transparency and deliberation over automated decision systems. Qualitative evidence further indicates that AI is perceived not as a standalone solution, but as a catalyst for institutional reform, capacity development, and sustainability-oriented governance. The study contributes to urban science by empirically validating a socio-technical framework that positions AI as a facilitative governance instrument embedded within institutional and trust-building processes. The findings offer policy-relevant insights for cities seeking to align AI-driven innovation with inclusive, accountable, and sustainable urban development. Full article

In the context of green transition and digital transformation, forestry is becoming a strategic area of application of current modern technologies. The Internet of Things (IoT), artificial intelligence (AI), big data analysis (Big Data) and Digital Twins define the basic infrastructure of smart forestry. By connecting sensors, drones and satellites, IoT allows for continuous monitoring of forest ecosystems, risk anticipation and decision optimization in real-time. The purpose of this study is to perform a comprehensive narrative analysis of the relevant scientific literature from the recent period (2020–2025) regarding the application of IoT in forestry, highlighting the conceptual, technological and institutional developments. Based on a selection of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (29 full-text articles), four major axes are analyzed: (A) forest fire detection and prevention; (B) climate-smart forestry and carbon accounting; (C) forest digitalization through the concepts of Forest 4.0, Forest 5.0 and Digital Twins; (D) sustainability and digital forest policies. The results show that IoT is a catalyst for the sustainable transformation of the forest sector, supporting carbon accounting, climate-risk reduction and data-driven governance. The analysis highlights four major developments: the consolidation of IoT–AI architectures, the integration of IoT and remote sensing, the emergence of Forest 4.0/5.0 and Digital Twins and the growing role of governance and data standards. These findings align with the objectives of the EU Forest Strategy 2030 and the European Green Deal. 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

This article presents the design, synthesis and application of novel C₈/PW₁₂O₄₀³⁻-IL Janus for highly efficient, recyclable catalytic degradation of methyl orange (MO) in wastewater. The catalyst’s innovative asymmetric architecture comprises a hydrophobic C₈ hemisphere that selectively adsorbs and pre-concentrates MO molecules and a catalytic phosphotungstate-based ionic liquid hemisphere that activates oxidants to generate hydroxyl radicals for rapid dye degradation. A magnetic Fe₃O₄ core facilitates instantaneous catalyst recovery. This “collect, degrade, and separate” mechanism synergistically results in exceptional performance, surpassing that of many conventional homogeneous and heterogeneous systems, as validated through comparative analysis. This work establishes a strategic paradigm for designing smart, multifunctional materials that combine targeted interfacial engineering with practical recyclability for advanced environmental remediation. Full article

The sudden increase in global energy demand has prompted the integration of Artificial Intelligence and the Internet of Things into the utility grid. The synergy of Artificial Intelligence and the Internet of Things in renewable energy sources has emerged as a promising solution for the development of smart grids and a transformative catalyst that restructures centralized power systems into resilient and sustainable systems. The state-of-the-art of the Internet of Things and Artificial Intelligence is presented in this paper to support the design, planning, operation, management and optimization of renewable energy-based power systems. This paper outlines the benefits of smart and resilient energy systems and the contributions of the Internet of Things across several applications, devices and networks. Artificial Intelligence can be utilized for predictive maintenance, demand-side management, fault detection, forecasting and scheduling. This paper highlights crucial future research directions aimed at overcoming the challenges that are associated with the adoption of emerging technologies in the power system by focusing on market policy and regulation and the human-centric and ethical aspects of Artificial Intelligence and the Internet of Things. The outcomes of this study can be used by policymakers, researchers and development agencies to improve global access to electricity and accelerate the development of sustainable energy systems. Full article

This empirical investigation explores the complex interdependencies between the concept of the Smart University Campus and the broader ecosystem of Smart City policies, with a particular focus on the New European Bauhaus initiative as a catalyst for educational transformation. The study examines how university campuses can evolve into paradigmatic models of innovation, sustainability, and inclusion through the strategic integration of emerging technologies, circular bioeconomy principles, and holistic ecological strategies. A comprehensive case study, grounded in rigorous quantitative analysis, including Principal Component Analysis (PCA), Importance-Performance Analysis (IPA), and Cluster Analysis (CA), based on questionnaires administered to a sample of 245 high school and university students—primarily from the academic community of the “King Mihai I” University of Life Sciences in Timișoara (USVT)—provides empirical insights into perceptions and expectations regarding the Smart Campus ecosystem and its core components: Smart Learning, Smart Living, Smart Safety and Security, Smart Socialization and Smart Health. The distinctive contribution of this research lies in its empirical demonstration that the strategic alignment between university campuses and Smart City initiatives, guided by the principles of the New European Bauhaus, can enhance educational efficiency by creating integrated learning ecosystems that simultaneously address academic needs, sustainability imperatives, and goals of sustainable urban development. Full article

This article develops a systematic literature review with a focus on the optimization of water harvesting through the use of artificial intelligence (AI) applications. These are framed in the search for sustainable solutions to the growing problem of water scarcity in urban environments. The analysis is oriented towards urban resilience and smart water management, incorporating interdisciplinary approaches such as systems thinking to understand the complex dynamics involved in water governance. The results indicate a growing trend in the utilisation of AI in various domains, including demand forecasting, leak detection, and catchment infrastructure optimization. Additionally, the findings suggest its application in water resilience modelling and adaptive urban planning. The text goes on to examine the challenges associated with the integration of technology in urban contexts, including the critical aspects of governance and regulation of AI, water consumption, energy and carbon emissions from the use of this technology, as well as the regulation of water management in digital transformation scenarios. The study identifies the most representative patents that combat the problem, and in parallel proposes lines of research aimed at strengthening the water resilience and sustainability of cities. The strategic role of AI as a catalyst for innovation in the transition towards smarter, more integrated and adaptive water management systems is also highlighted. Full article

Organic soil pollution poses a persistent threat to environmental sustainability by disrupting nutrient cycling and ecosystem functioning. The biochar-activated persulfate (PS)-based advanced oxidation process (AOP) has emerged as a promising strategy for the sustainable remediation of organic-contaminated soils. This review provides a comprehensive overview of the recent progress in the PS-based degradation of organic pollutants, with a particular focus on the role of biochar as an efficient and environmental activator. This review further summarizes advancements in the design of modified biochars, including metal (Fe, Cu, Co, Mn, Zn, and La), non-metal (N, S, B, P), and functional group modifications, aimed at enhancing the PS activation efficiency while minimizing secondary environmental risks. Importantly, the overlooked contributions of soil microorganisms in PS/biochar systems are discussed, highlighting their potential to complement chemical oxidation and contribute to eco-compatible remediation pathways. This review emphasizes the sustainability-oriented evolution of PS/biochar technology, highlighting the importance of a cost-efficient implementation, ecological compatibility, and the rational engineering of smart, regenerable catalysts. These insights support the advancement of PS/biochar-based AOPs toward scalable, intelligent, and environmentally sustainable soil remediation. Full article

Heterogeneous photocatalysis has emerged as a versatile and sustainable technology for the degradation of emerging contaminants in water. This review highlights recent advancements in photocatalysts design, including band gap engineering, heterojunction formation, and plasmonic enhancement to enable visible-light activation. Various reactor configurations, such as slurry, immobilized, annular, flat plate, and membrane-based systems, are examined in terms of their efficiency, scalability, and operational challenges. Hybrid systems combining photocatalysis with membrane filtration, adsorption, Fenton processes, and biological treatments demonstrate improved removal efficiency and broader applicability. Energy performance metrics such as quantum yield and electrical energy per order are discussed as essential tools for evaluating system feasibility. Special attention is given to solar-driven reactors and smart responsive materials, which enhance adaptability and sustainability. Additionally, artificial intelligence and machine learning approaches are explored as accelerators for catalyst discovery and process optimization. Altogether, these advances position photocatalysis as a key component in future water treatment strategies, particularly in decentralized and low-resource contexts. The integration of material innovation, system design, and data-driven optimization underlines the potential of photocatalysis to contribute to global efforts in environmental protection and sustainable development. Full article

The global plastic crisis, with over 400 million metric tons produced annually and minimal recycling, demands urgent solutions. Photocatalytic plastic photoreforming offers a dual benefit: converting non-recyclable plastics into hydrogen fuel and valuable chemicals using solar energy under mild conditions. This critical review highlights recent advances in photocatalyst design, including semiconductors, MOF-derived materials, and co-catalyst systems, and explores key insights into plastic degradation mechanisms and reactor configurations. Operational factors such as pH, light intensity, and flow dynamics are discussed for their impact on hydrogen yield and product selectivity. Life cycle and techno-economic assessments reveal current challenges in efficiency, scalability, and cost to illuminate the feasibility of implementing the technology at industrial scale. This study suggests that innovations in catalyst engineering, light management, and system integration provide viable paths forward. With its potential to upcycle plastic waste and contribute to low-carbon hydrogen economies, photoreforming represents a promising approach in advancing circular economy goals, especially when coupled with policy support and smart separation strategies. Full article

The photosensitive properties of smart photoactive polymers give them a wide range of potential applications across various fields. This study focuses on designing polymeric systems that incorporate hydrophilic polymers, with the primary goal of adapting these materials for biological applications. Specifically, it aims to contribute to the development of photochromic materials for optical processing, utilizing both molecular and macromolecular components. Additionally, this study evaluates the effectiveness of photoactive polymers in photodynamic therapy (PDT). It details the synthesis and characterization of photoactive copolymers derived from maleic anhydride (MAn) combined with vinyl monomers such as 2-methyl-2-butene (MB) and 1-octadecene (OD), as well as the organic compound 1-(2-hydroxyethyl)-3,3-dimethylindoline-6-nitrobenzopyran (SP). The two novel optically active alternating polymeric systems, poly(maleic anhydride-alt-octadecene) and poly(maleic anhydride-alt-2-methyl-2-butene), were functionalized with SP through an esterification process in a 1:1 monomer feed ratio, using pyridine as a catalyst. This methodology incorporated approximately 100% of the photoactive molecules into the main acrylic chain to prepare the alternating copolymers. These copolymers were characterized by UV-visible, FTIR, and 1H-NMR spectroscopy and analysis of their optical and thermal properties. When exposed to UV light, the photoactive polymer films can develop a deep blue color (566 nm in the absorption spectra). Finally, the study also assesses their capacity for photodynamic antimicrobial action in organic film. Notably, the photoactive P(MAn-alt-2MB)-PS significantly enhances the photodynamic antimicrobial activity of the photosensitizer Ru(bpy) against two bacterial strains of Staphylococcus aureus, reducing the minimum inhibitory concentration (MIC) from 2 µg/mL to 0.5 µg/mL. Therefore, 4 times less photosensitizer is required when mixed with the photoactive polymer to inhibit the growth of antibiotic-sensitive and -resistant bacteria. Full article

The adoption of Industry 4.0 technologies supports the digital transformation of production processes, making them more efficient. This study examines how digital infrastructure, digital skills, and the use of cloud technologies influence labor productivity in European Union countries. Using econometric methods, including linear regressions and fixed-effects panel regressions, the analysis highlights the important role digital skills play in boosting productivity. It also identifies the adoption of cloud solutions as a catalyst for process efficiency, while widespread high-speed internet coverage supports the connectivity of smart systems. However, variations in the development of digital infrastructure and workforce readiness across EU member states present challenges to overall labor productivity. The study concludes that strategic investments in automation and digital infrastructure, along with improving the workforce’s digital skills, are essential to making Industry 4.0 a key pillar of economic competitiveness. By examining how workforce digital skills and certain Industry 4.0 technologies affect labor productivity, this research adds valuable insights to the specialized literature. Full article