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Improving Energy Efficiency in Buildings with an IoT-Based Smart Monitoring System

doi: 10.3390/en18051269
With greenhouse gas emissions and climate change continuing to be major global concerns, researchers are increasingly focusing on reducing energy consumption as a key strategy to address these challenges. In recent years, various devices and technologies have been developed for residential buildings to implement energy-saving strategies and enhance energy efficiency. This paper presents a real-time IoT-based smart monitoring system designed to optimize energy consumption and enhance residents’ safety through efficient monitoring of home conditions and appliance usage. The system is built on a Raspberry Pi Model 4B as its core platform, integrating various IoT sensors, including the DS18B20 for temperature monitoring, the BH1750 for measuring light intensity, a passive infrared (PIR) sensor for motion detection, and the MQ7 sensor for carbon monoxide detection. The Adafruit IO platform is used for both data storage and the design of a graphical user interface (GUI), enabling residents to remotely control their home environment. Our solution significantly enhances energy efficiency by monitoring the status of lighting and heating systems and notifying users when these systems are active in unoccupied areas. Additionally, safety is improved through IFTTT notifications, which alert users if the temperature exceeds a set limit or if carbon monoxide is detected. The smart home monitoring device is tested in a university residential building, demonstrating its reliability, accuracy, and efficiency in detecting and monitoring various home conditions.
- University of Surrey United Kingdom
- University of West London United Kingdom
- University of West London United Kingdom
internet of things (IoT), Technology, residential buildings, T, smart monitoring, energy efficiency
internet of things (IoT), Technology, residential buildings, T, smart monitoring, energy efficiency
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
