Smart City Gnosys

Smart city article details

Title	Simulation Of Low Energy Building Thermal Energy Cycle In Iot Smart City Planning Based On Environmental Sensors And Deep Learning
ID_Doc	48874
Authors	Ting L.
Year	2024
Published	Thermal Science and Engineering Progress, 54
DOI	http://dx.doi.org/10.1016/j.tsep.2024.102809
Abstract	With the intensification of global climate change, the reduction of building energy consumption has become an important goal of smart city development. By optimizing the thermal energy circulation system, low energy buildings can not only reduce energy consumption, but also improve living comfort. In recent years, with the help of environmental sensors and deep learning technology, the intelligent management of building heat energy cycle has become a research hotspot. The research constructs an intelligent thermal energy circulation system that integrates multiple environmental sensors for real-time monitoring of indoor and outdoor temperature, humidity and other key environmental parameters. A deep learning algorithm is used to analyze the collected data to optimize the control strategy of the thermal energy cycle. Through simulation, the energy efficiency performance of the scheme under different climatic conditions and building types was evaluated. The experimental results show that the control strategy based on environmental sensors and deep learning can significantly improve the thermal energy utilization efficiency of low-energy buildings, and the average energy consumption is greatly reduced compared with the traditional management mode. The system shows good adaptability and stability under different climate conditions. Therefore, the application of environmental sensors and deep learning technology in the thermal energy cycle of low-energy buildings can effectively promote the energy efficiency management of smart cities.
Author Keywords	Deep learning; Environmental sensor; Heat energy cycle; Internet of Things; Low-energy buildings; Planning simulation; Smart city

Similar Articles

Id	Similarity	Authors	Title	Published
17962	0.894	Aljohani A.	Deep Learning-Based Optimization Of Energy Utilization In Iot-Enabled Smart Cities: A Pathway To Sustainable Development	Energy Reports, 12 (2024)
42668	0.885	Wang S.; Zawawi E.M.B.A.; Kwong Q.J.; Wang R.; Deng J.	Predication Of Smart Building Energy Consumption Based On Deep Learning Algorithm	Journal of Autonomous Intelligence, 6, 2 (2023)
57240	0.878	Shafiq M.; Bhavani N.P.G.; Venkata Naga Ramesh J.; Veeresha R.K.; Talasila V.; Sulaiman Alfurhood B.	Thermal Modeling And Machine Learning For Optimizing Heat Transfer In Smart City Infrastructure Balancing Energy Efficiency And Climate Impact	Thermal Science and Engineering Progress, 54 (2024)
23537	0.876	Zhang T.; Yang X.	Energy-Saving Design Of Smart City Buildings Based On Deep Learning Algorithms And Remote Sensing Image Scenes	Informatica (Slovenia), 48, 19 (2024)
8433	0.873	Udayakumar R.; Mahesh B.; Sathiyakala R.; Thandapani K.; Choubey A.; Khurramov A.; Alzubaidi L.H.; Sravanthi J.	An Integrated Deep Learning And Edge Computing Framework For Intelligent Energy Management In Iot-Based Smart Cities	International Conference for Technological Engineering and its Applications in Sustainable Development, ICTEASD 2023 (2023)
49207	0.873	Gao Q.; Chu Y.; Peng Z.; Jin Y.; Ji X.; Ji S.; Ping S.; Xie X.; Zhu X.; Yue Y.	Smart Building Management System Based On Digital Twin: A Case Study On Real-Time Environmental Monitoring And Thermal Comfort Prediction	Proceedings - 2024 IEEE International Symposium on Parallel and Distributed Processing with Applications, ISPA 2024 (2024)
50953	0.869	Tripathy N.; Tripathy S.S.	Smart Green Cities Using Iot-Based Deep Reinforcement Learning Energy Management	Internet of Things and Big Data Analytics for a Green Environment (2024)
40629	0.866	Jain R.; Bakare Y.B.; Alaric J.S.; Balam S.K.; Pattanaik B.; Ayele T.B.; Nalagandla R.	Optimization Of Energy Consumption In Smart Homes Using Firefly Algorithm And Deep Neural Networks	Sustainable Engineering and Innovation, 5, 2 (2023)
9337	0.866	Abid Y.M.; Jalil M.A.; Abd S.K.; Sabah H.A.; Bakri B.I.; Jaleel Maktoof M.A.; Mohammed A.; Adile M.; Mustafa Ahmed M.S.; Mohammed M.A.; Alzubaidi L.H.	Analysis Of The Energy Efficiency Of Smart City Buildings Based On Deep Learning Algorithms Using Ai	International Conference on Smart Systems for Electrical, Electronics, Communication and Computer Engineering, ICSSEEC 2024 - Proceedings (2024)
23181	0.862	Lee S.H.; Lee T.; Kim S.; Park S.	Energy Consumption Prediction System Based On Deep Learning With Edge Computing	2019 2nd International Conference on Electronics Technology, ICET 2019 (2019)