A Systematic Review of Building Energy Management Systems (BEMSs): Sensors, IoT, and AI Integration

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dc.contributor.authorAkbulut, Leyla
dc.contributor.authorTasdelen, Kubilay
dc.contributor.authorAtilgan, Atilgan
dc.contributor.authorMalinowski, Mateusz
dc.contributor.authorCosgun, Ahmet
dc.contributor.authorSenol, Ramazan
dc.contributor.authorAkbulut, Adem
dc.date.accessioned2026-01-24T12:29:32Z
dc.date.available2026-01-24T12:29:32Z
dc.date.issued2025
dc.departmentAlanya Alaaddin Keykubat Üniversitesi
dc.description.abstractThe 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.
dc.description.sponsorshipKrakow University of Economics [026/GGR/2024/POT]; Ministry of Science and Higher Education of the Republic of Poland
dc.description.sponsorshipThis research was funded by Krakow University of Economics, grant number 026/GGR/2024/POT. The APC was funded by the Ministry of Science and Higher Education of the Republic of Poland.
dc.identifier.doi10.3390/en18246522
dc.identifier.issn1996-1073
dc.identifier.issue24
dc.identifier.urihttps://doi.org/10.3390/en18246522
dc.identifier.urihttps://hdl.handle.net/20.500.12868/5431
dc.identifier.volume18
dc.identifier.wosWOS:001646453700001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofEnergies
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WoS_20260121
dc.subjectbuilding energy management systems (BEMS)
dc.subjectinternet of things (IoT)
dc.subjectartificial intelligence (AI)
dc.subjectsmart buildings
dc.subjectHVAC optimization
dc.subjectoccupancy sensing
dc.subjectenergy efficiency
dc.subjectfault detection
dc.subjectwireless sensor networks (WSNs)
dc.subjectsmart grids
dc.titleA Systematic Review of Building Energy Management Systems (BEMSs): Sensors, IoT, and AI Integration
dc.typeReview Article

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