Abstract
AbstractThis paper presents a low-cost method for real-time energy management in residences. Light, motion, temperature, and sound sensors are system inputs. Lighting, heating, and cooling output powers are set according to sensor data and consumer conditions. The system is controlled by using three different fuzzy logic inference engines together with a microcontroller, sensors, and Nextion HMI display. The lighting, cooling, and heating can be precisely controlled according to the conditions of the house. This ensures that energy consumption is minimized while maintaining an appropriate level of comfort for the users. This shows that the system is designed as user-friendly and can be operated easily by the consumer. Thus, whether the consumers are at home or not, the consumption of electricity, water, and natural gas is controlled, and unnecessary consumption is prevented. The results show that such systems can effectively reduce energy consumption while maintaining user comfort, and this system could be an essential component of home energy management systems.
Publisher
Springer Science and Business Media LLC
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A secured deep learning based smart home automation system;International Journal of Information Technology;2024-08-29
2. Fuzzy Logic-Based Control Algorithm for Smart Microgrid Energy Management;2024 4th International Conference on Innovative Practices in Technology and Management (ICIPTM);2024-02-21