The escalating global demand for energy-efficient and sustainable built environments has catalyzed the advancement of Building Energy Management Systems (BEMSs), particularly through their integration with cutting-edge technologies. This review presents a comprehensive and critical synthesis of the convergence between BEMSs and enabling tools such as the Internet of Things (IoT), wireless sensor networks (WSNs), and artificial intelligence (AI)-based decision-making architectures. Drawing upon 89 peer-reviewed publications spanning from 2019 to 2025, the study systematically categorizes recent developments in HVAC optimization, occupancy-driven lighting control, predictive maintenance, and fault detection systems. It further investigates the role of communication protocols (e.g., ZigBee, LoRaWAN), machine learning-based energy forecasting, and multi-agent control mechanisms within residential, commercial, and institutional building contexts. Findings across multiple case studies indicate that hybrid AI–IoT systems have achieved energy efficiency improvements ranging from 20% to 40%, depending on building typology and control granularity. Nevertheless, the widespread adoption of such intelligent BEMSs is hindered by critical challenges, including data security vulnerabilities, lack of standardized interoperability frameworks, and the complexity of integrating heterogeneous legacy infrastructure. Additionally, there remain pronounced gaps in the literature related to real-time adaptive control strategies, trust-aware federated learning, and seamless interoperability with smart grid platforms. By offering a rigorous and forward-looking review of current technologies and implementation barriers, this paper aims to serve as a strategic roadmap for researchers, system designers, and policymakers seeking to deploy the next generation of intelligent, sustainable, and scalable building energy management solutions.

Energy Performance Contracts (EPC) are performance-based financing mechanisms designed to improve energy efficiency and support renewable energy adoption in the public sector. This study examines the economic efficiency of a 1710.72 kWp solar power plant (SPP), implemented under an EPC at Alanya Alaaddin Keykubat University, using a regression-based analysis. The model evaluates the effects of solar radiation, investment cost, and electricity sales price on unit production cost, and its predictions were compared with actual production data. Results show the system exceeded the EPC contract target by 16.2%, producing 2,423,472.28 kWh in its first year and preventing 1168.64 tons of CO₂ emissions. The developed multiple linear regression model achieved a predictive error margin of 14.7%, confirming its validity. This study highlights the technical, economic, and environmental benefits of EPC applications in Türkiye’s public institutions and offers a practical decision-support framework for policymakers. The novelty lies in integrating a regression model with operational data and providing a comparative assessment of planned, predicted, and actual outcomes.

The escalating global demand for energy-efficient and sustainable built environments has catalyzed the advancement of Building Energy Management Systems (BEMS), particularly through their integration with cutting-edge technologies. This review presents a comprehensive and critical synthesis of the convergence between BEMS and enabling tools such as the Internet of Things (IoT), wireless sensor networks (WSNs), and artificial intelligence (AI)-based decision-making architectures. Drawing upon 89 peer-reviewed publications spanning from 2019 to 2025, the study systematically categorizes recent developments in HVAC optimization, occupancy-driven lighting control, predictive maintenance, and fault detection systems. It further investigates the role of communication protocols (e.g., ZigBee, LoRaWAN), machine learning-based energy forecasting, and multi-agent control mechanisms within residential, commercial, and institutional building contexts. Findings across multiple case studies indicate that hybrid AI–IoT systems have achieved energy efficiency improvements ranging from 20% to 40%, depending on building typology and control granularity. Nevertheless, the widespread adoption of such intelligent BEMS is hindered by critical challenges, including data security vulnerabilities, lack of standardized interoperability frameworks, and the complexity of integrating heterogeneous legacy infrastructure. Additionally, there remain pronounced gaps in the literature related to real-time adaptive control strategies, trust-aware federated learning, and seamless interoperability with smart grid platforms. By offering a rigorous and forward-looking review of current technologies and implementation barriers, this paper aims to serve as a strategic roadmap for researchers, system designers, and policymakers seeking to deploy the next generation of intelligent, sustainable, and scalable building energy management solutions.

Energy Performance Contracts (EPC) are performance-based financing mechanisms adopted to increase energy efficiency and encourage renewable energy applications in the public sector. In this study, the economic efficiency of the solar power plant (SPP) established within the scope of EPC on the campus of Alanya Alaaddin Keykubat University was examined with a regression-based analysis. In the model, the effects of parameters such as solar radiation, investment cost and electricity sales price on unit production cost were evaluated; the multiple linear regression model created was tested by comparing with real production data. The model outputs provided the opportunity to evaluate the accuracy of system performance by revealing the difference between the predicted and realized production values. The study reveals the contribution of EPC applications to the economic feasibility of renewable energy investments in public institutions in Türkiye with concrete data; and provides an analytical basis for decision makers to direct energy policies. The novelty of this study lies in integrating a regression-based quantitative model with real operational data to evaluate the technical and economic feasibility of an EPC-based solar power plant in Türkiye's public sector, while also introducing a unique comparative framework for planned, predicted, and actual energy production outcomes.

Energy Performance Contracting (EPC) is increasingly used as a financial mechanism to accelerate renewable energy investments in public infrastructure; however, its effectiveness depends not only on technical performance but also on institutional governance arrangements. This study evaluates a 1.71 MWp grid-connected photovoltaic (PV) system implemented under an EPC model at a public university in Türkiye, examining the interaction between operational performance and institutional governance structures. A mixed-methods research design was applied, combining SCADA-based electricity generation data for the 2024–2025 monitoring period with contract analysis and institutional evaluation. The results indicate that the PV system achieved stable electricity production levels and an average performance ratio of approximately 83%, demonstrating reliable operational performance under real operating conditions. Annual electricity generation reached about 2.13 GWh in 2024 and 2.44 GWh in 2025, corresponding to estimated carbon emission reductions of approximately 895 and 1025 tonnes of CO₂, respectively. Despite these technical achievements, the analysis reveals several governance-related challenges, including fragmented institutional responsibilities and limited transparency in monitoring and verification processes. The findings suggest that the effectiveness of EPC mechanisms depends on the integration of technical performance monitoring with coherent institutional roles and transparent governance structures. When supported by clear policy alignment and systematic monitoring frameworks, EPC-based photovoltaic investments can function as effective instruments for accelerating renewable energy deployment and supporting decarbonization strategies in public sector institutions.

This study investigates the environmental and economic dynamics of sustainable aviation through the perspectives of senior executives in Türkiye’s civil aviation sector. As global aviation continues to face increasing pressure to decarbonize, understanding how industry leaders perceive and respond to carbon emission challenges is critical. The research employs a qualitative methodology based on semi-structured interviews with ten executives across airlines, airports, and aviation authorities. Using Python-based data mining techniques and thematic analysis, three core themes emerged: (1) sustainable aviation experience and economic dimensions; (2) carbon emissions reduction and efficient aviation systems; (3) sustainable energy and alternative fuel technologies. Findings reveal that while environmental sustainability is a growing concern, operational costs, technological constraints, and regulatory uncertainties significantly influence implementation. Stakeholders emphasized the importance of coordinated action among governments, industry, and international organizations, especially in scaling Sustainable Aviation Fuels (SAFs) and enhancing infrastructure for electric and hydrogen-powered aircraft. The study concludes that achieving net-zero aviation by 2050 requires an integrated approach that balances technological innovation, policy incentives, and stakeholder engagement. This multidimensional insight contributes to the ongoing discourse on low-carbon transition strategies in aviation, offering policy-relevant implications for developing countries.