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September 17, 20250 citations

IoT-Based Optimization of Energy Consumption in Non-Smart Homes

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AAAhmed S. AbdelwahedRTRadwa M. TawfeekGAGhada M. Amer

Key Points

  • Electricity consumption can be reduced by up to 41% in summer and 61.5% in winter using IoT monitoring.
  • In experimental scenarios of energy consumption limits, reductions were observed at 1.5, 2.5, and 3.5 kW/h.
  • The control unit prototype was created using Raspberry Pi and Arduino to manage energy usage effectively.
  • Establishing better energy practices may become essential as demand for electricity continues to rise.

Abstract

Abstract The electricity sector has seen substantial modifications, from generation to consumption, due to the development of intelligent technology. There is a global increase in the need for more energy. With the limitation of energy resources and the pollution due to carbon emissions related to electricity generation and usage, energy-efficient systems are a must. Demand-oriented home management systems are feasible solutions for efficient energy consumption. This research proposes the Internet of Things concept to monitor, optimize, and adapt energy usage in real-time for homes with non-smart traditional devices. A control unit prototype has been implemented using a Raspberry Pi, Arduino, and current sensors. A website is created with a graphical user interface, allowing the user to monitor and set the energy consumption demand limit. A database to store information about any device connected to the prototype is being built. The stored data is the permissible limit of electricity consumption, the consumption of each machine, and its operating time, in addition to calculating the monthly bill according to its tariff rate. When the prototype model is applied to the demand limit of electricity consumption in three scenarios (1.5, 2.5, and 3.5 kW/h), the experimental findings show electricity consumption reduction in real time by up to 41%, 25%, and 10%, respectively, in summer and 61.5%, 53%, and 42.5% in winter.

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Cite This Study

Abdelwahed et al. (2025) studied this question.

synapsesocial.com/papers/68d45e5831b076d99fa5e93chttps://doi.org/10.21203/rs.3.rs-7455277/v1
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