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Addy, M, Adinyira, E, James Cofie, D and Dadzoe, F (2021) Impediments to the development of the green building market in sub-Saharan Africa: the case of Ghana. Smart and Sustainable Built Environment, 10(2), 193-207.
Aradhana Vikas, G (2021) Studying green consumer behavior through multiple lenses in a developing country. Smart and Sustainable Built Environment, 10(2), 274-92.
Chang, V, Xu, Y K, Zhang, J and Xu, Q (2021) Research on intelligent manufacturing development approach for China's local valve industry. Smart and Sustainable Built Environment, 10(2), 293-321.
Ghaffour, W, Ouissi, M N and Marc André Velay, D (2021) Analysis of urban thermal environments based on the perception and simulation of the microclimate in the historic city of Tlemcen. Smart and Sustainable Built Environment, 10(2), 141-68.
Ghansah, F A, De-Graft, O-M and Ayarkwa, J (2021) Project management processes in the adoption of smart building technologies: a systematic review of constraints. Smart and Sustainable Built Environment, 10(2), 208-26.
Majid Parchami, J, Tayebe Yavari, R, Noorzai, E and Alizadeh, M (2021) A BIM-based construction claim management model for early identification and visualization of claims. Smart and Sustainable Built Environment, 10(2), 227-57.
Sayah, Z, Kazar, O, Lejdel, B, Laouid, A and Ghenabzia, A (2021) An intelligent system for energy management in smart cities based on big data and ontology. Smart and Sustainable Built Environment, 10(2), 169-92.
- Type: Journal Article
- Keywords: big data; multi-agent system; ontology; smart cities; interoperability; social networks; cities; smart buildings; environmental protection; semantics; social organization; sustainability
- ISBN/ISSN:
- URL: http://dx.doi.org/10.1108/SASBE-07-2019-0087
- Abstract:
This research paper aims at proposing a framework based on semantic integration in Big Data for saving energy in smart cities. The presented approach highlights the potential opportunities offered by Big Data and ontologies to reduce energy consumption in smart cities. This study provides an overview of semantics in Big Data and reviews various works that investigate energy saving in smart homes and cities. To reach this end, we propose an efficient architecture based on the cooperation between ontology, Big Data, and Multi-Agent Systems. Furthermore, the proposed approach shows the strength of these technologies to reduce energy consumption in smart cities. Through this research, we seek to clarify and explain both the role of Multi-Agent System and ontology paradigms to improve systems interoperability. Indeed, it is useful to develop the proposed architecture based on Big Data. This study highlights the opportunities offered when they are combined together to provide a reliable system for saving energy in smart cities. The significant advancement of contemporary applications (smart cities, social networks, health care, IoT, etc.) requires a vast emergence of Big Data and semantics technologies in these fields. The obtained results provide an improved vision of energy-saving and environmental protection while keeping the inhabitants' comfort. This work is an efficient contribution that provides more comprehensive solutions to ontology integration in the Big Data environment. We have used all available data to reduce energy consumption, promote the change of inhabitant's behavior, offer the required comfort, and implement an effective long-term energy policy in a smart and sustainable environment.
Yenisetty, P T and Bahadure, P (2021) Spatial accessibility measures to educational facilities from public transit: a case of Indian cities. Smart and Sustainable Built Environment, 10(2), 258-73.