000151651 001__ 151651 000151651 005__ 20250319155217.0 000151651 0247_ $$2doi$$a10.3390/app15041724 000151651 0248_ $$2sideral$$a143234 000151651 037__ $$aART-2025-143234 000151651 041__ $$aeng 000151651 100__ $$0(orcid)0000-0002-2887-2105$$aMartínez Ruiz, Ignacio$$uUniversidad de Zaragoza 000151651 245__ $$aIoB Internet of Things (IoT) for Smart Built Environment (SBE): Understanding the Complexity and Contributing to Energy Efficiency; A Case Study in Mediterranean Climates 000151651 260__ $$c2025 000151651 5060_ $$aAccess copy available to the general public$$fUnrestricted 000151651 5203_ $$aTo meet the 2050 targets about climate change and decarbonization, accomplishing thermal comfort, Internet of Things (IoT) ecosystems are key enabling technologies to move the Built Environment (BE) towards Smart Built Environment (SBE). The first contributions of this paper conceptualise SBE from its dynamic and adaptative perspectives, considering the human habitat, and enunciate SBE as a multidimensional approach through six ways of inhabiting: defensive, projective, scientific, thermodynamic, subjective, and complex. From these premises, to analyse the performance indicators that characterise these multidisciplinary ways of inhabiting, an IoT-driven methodology is proposed: to deploy a sensor infrastructure to acquire experimental measurements; analyse data to convert them into context-aware information; and make knowledge-based decisions. Thus, this work tackles the inefficiency and high energy consumption of public buildings with the challenge of balancing energy efficiency and user comfort in dynamic scenarios. As current systems lack real-time adaptability, this work integrates an IoT-driven approach to enhance energy management and reduce discrepancies between measured temperatures and normative thresholds. Following the energy efficiency directives, the obtained results contribute to the following: understanding the complexity of the SBE by analysing its thermal performance, quantifying the potential of energy saving, and estimating its economic impact. The derived conclusions show that IoT-driven solutions allow the generation of real-data-based models on which to enhance SBE knowledge, by increasing energy efficiency and guaranteeing user comfort while minimising environmental effects and economic impact. 000151651 536__ $$9info:eu-repo/grantAgreement/ES/UZ/EQUZ-2022-TEC-11$$9info:eu-repo/grantAgreement/ES/UZ/SGI-171481$$9info:eu-repo/grantAgreement/ES/UZ/2000-0074 SAMCA 000151651 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/ 000151651 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion 000151651 700__ $$0(orcid)0000-0001-5137-2478$$aCano Suñén, Enrique$$uUniversidad de Zaragoza 000151651 700__ $$0(orcid)0000-0002-7396-7840$$aMarco Marco, Álvaro 000151651 700__ $$0(orcid)0000-0002-0544-0182$$aFernández Cuello, Ángel$$uUniversidad de Zaragoza 000151651 7102_ $$15015$$2110$$aUniversidad de Zaragoza$$bDpto. Arquitectura$$cÁrea Construc. Arquitectónicas 000151651 7102_ $$15004$$2545$$aUniversidad de Zaragoza$$bDpto. Ingeniería Mecánica$$cÁrea Ingeniería Mecánica 000151651 7102_ $$15008$$2560$$aUniversidad de Zaragoza$$bDpto. Ingeniería Electrón.Com.$$cÁrea Ingeniería Telemática 000151651 773__ $$g15, 4 (2025), 1724 [26 pp.]$$pAppl. sci.$$tApplied Sciences (Switzerland)$$x2076-3417 000151651 8564_ $$s6044535$$uhttps://zaguan.unizar.es/record/151651/files/texto_completo.pdf$$yVersión publicada 000151651 8564_ $$s2687734$$uhttps://zaguan.unizar.es/record/151651/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada 000151651 909CO $$ooai:zaguan.unizar.es:151651$$particulos$$pdriver 000151651 951__ $$a2025-03-19-14:20:04 000151651 980__ $$aARTICLE