Energy–Efficient IoT: Optimizing Consumption for a Sustainable Future
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Abstract
Aiming at energy IoT applications for demand-side automation of electricity usage in residential and commercial buildings, this paper presents systems and methodologies that advance the research objectives. We developed and implemented an intelligent switch system that provides real-time energy feedback, automatic control, and optimisation to monitor the system’s energy performance metrics. Based on 58 households and a six-month field study, the system achieved an average saving of 24.7%, with a maximum saving of 37.2%. We consider the challenges of ubiquitous deployment, interoperability, security, and system cost. Further optimisations can be made toward energy efficiency, such as dynamic load balancing, machine-learning-based predictive models for SLA requirements , and adaptive scheduling algorithms. This paper demonstrates the feasibility of IoT for regulating household energy use through analyses of a prototype and a dataset. The prototype enables households to achieve approximately 412 watt-hours of annual energy savings, thereby illustrating the potential of energy management and the feasibility of the proposed system.
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