Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability

被引:4
作者
Wang, Wen-Cheng [1 ]
Dwijendra, Ngakan Ketut Acwin [2 ]
Sayed, Biju Theruvil [3 ]
Alvarez, Jose Ricardo Nunez [4 ]
Al-Bahrani, Mohammed [5 ]
Alviz-Meza, Anibal [6 ]
Cardenas-Escrocia, Yulineth [4 ]
机构
[1] Yango Univ, Coll Innovat & Entrepreneurship Educ, Fuzhou 350015, Peoples R China
[2] Udayana Univ, Fac Engn, Denpasar 80361, Indonesia
[3] Dhofar Univ, Dept Comp Sci, POB 2509, Salalah 211, Oman
[4] Univ Costa, Dept Energy, Barranquilla 080001, Colombia
[5] Al Mustaqbal Univ Coll, Chem Engn & Petr Ind Dept, Babylon 51001, Iraq
[6] Univ Senor Sipan, Fac Ingn & Urbanismo, Grp Invest Deterioro Mat Trans Energet & Ciencia D, Km 5 Via Pimentel, Chiclayo 14001, Peru
关键词
Internet of Things; energy consumption; optimization;
D O I
10.3390/su15086475
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The internal components of a smart building interact through a compatible fabric and logic. A smart building integrates systems, structure, services, management, and their interrelationships to create a dynamic and cost-efficient environment. Smart buildings reduce the amount of cooling and heating load required to cool and heat spaces, thereby lowering operating costs and energy consumption without sacrificing occupant comfort. Smart structures are an Internet of Things (IoT) concern. The Internet of Things is a global network that virtualizes commonplace objects. The Internet of Things infuses non-technical objects with technology. IoT development has led to the creation of new protocols based on architectures for wireless sensor networks. Energy conservation extends the life and improves the performance of these networks, while overcoming the limitations of IoT node batteries. This research seeks to develop a data transmission model for routing IoT data in smart buildings. Utilization of intelligent object clustering and particle swarm optimization (PSO), chaotic particle swarm optimization (CPSO), and fractional chaotic order particle swarm optimization (FCPSO) optimization methods. Using the proposed algorithm to minimize energy consumption in the IoT is possible due to the algorithm's ability to mitigate the problem by considering the number of parameters that can have a significant impact on performance, which is the goal of many optimization approaches.
引用
收藏
页数:15
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