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

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.