Open collaborative smart plugs for energy management

This project tackles the limits of commercial smart plugs. Those plugs often hide raw measurement data, offer only a few energy parameters, and cannot connect to external sensors or machine‑learning models. To solve these problems, we built an open, collaborative smart plug called EnAPlug for advanced energy management and home automation. We demonstrated the system on a household refrigerator, where it measures both electrical and environmental data. By adding machine‑learning algorithms—either running on the plug itself or on a nearby edge device—the system can predict the fridge’s internal humidity and when the motor will turn on up to five minutes ahead. This prediction lets us adjust duty cycles and manage

energy use proactively. The implementation provides a solid framework for open‑source hardware and software in demand‑side management, so researchers and developers can create custom control strategies. With shared data and local predictive models, the plug improves energy efficiency and gives clearer insight into how appliances operate, offering a scalable base for smart‑grid integration and intelligent home automation.

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