Collecting Dataset for Machine Learning Using IoT: Based Electricity Consumption in Residential and Commercial Area

Many different tasks can be automated with the help of machine learning. Smart buildings, which connect building operations through the Internet of Things (IoT), make it easier to control tasks like temperature, safety, and maintenance via computers and mobile devices. As the IoT becomes more preval...

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Bibliographic Details
Published in2023 International Conference on Artificial Intelligence and Knowledge Discovery in Concurrent Engineering (ICECONF) pp. 1 - 9
Main Authors Lingaraja, D, Aravind, T, Kumar, S Praveen, Vamsidharreddy, Bollavaram, Rohith, Mannur, Kumar, Thopugunta Pavan
Format Conference Proceeding
LanguageEnglish
Published IEEE 05.01.2023
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Summary:Many different tasks can be automated with the help of machine learning. Smart buildings, which connect building operations through the Internet of Things (IoT), make it easier to control tasks like temperature, safety, and maintenance via computers and mobile devices. As the IoT becomes more prevalent, smart buildings are evolving into core components of larger system integrations. By utilizing efficient technology-based life-saving strategies, the IoT plays a significant part in smart buildings and offers facilities that enhance human security. The majority of the world's energy sources are currently non-renewable, which causes them to be depleting at an alarming rate. A situation like this requires immediate attention. Due to careless usage in residential areas, a significant amount of power is wasted in India each year. By properly monitoring usage, most of this waste can be stopped. Machine learning algorithms are used to determine the electricity consumption of particular appliances. The usage is then contrasted with an appliance threshold value. The readings allow us to determine whether or not the amount of electricity used exceeds or falls short of requirements. In this article, the fundamental components of smart buildings are dissected, and then a variety of machine learning strategies and Internet of Things technologies are outlined as ways to improve the efficiency of smart buildings and make them more environmentally responsible.
ISBN:9798350334357
DOI:10.1109/ICECONF57129.2023.10084277