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This study presents the design and implementation of an AI and IoT-enabled Home Energy Management System (HEMS) tailored for hybrid renewable energy integration in residential settings, focusing on rural areas of Sindh, Pakistan. Buildings contribute to nearly one-third of global final energy use, highlighting the urgent need for smart solutions that optimise energy consumption. The proposed HEMS incorporates real-time monitoring, supply and demand-side management strategies, and automation to enhance energy efficiency and reduce dependence on conventional grid power. The system architecture includes an ESP8266-based IoT module, cloud integration via ThingSpeak, and an Android application developed using MIT App Inventor for user control. Experimental results from a working prototype, consisting of a 3-kWh solar PV system, battery storage, and connected household loads – demonstrate a 23–28% reduction in grid energy consumption. The system also enhances user comfort through temperature-based appliance control. This research contributes a scalable, low-cost model for under-resourced regions, supporting Pakistan’s energy resilience and global sustainable development goals.

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AI and IoT-Enabled Home Energy Management Systems (HEMS) for Hybrid Renewable Energy Sources

  • 会议论文

  • 发表日期：

    2026年

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  • Abdul Fatah,
  • Ghous Bakhsh Narejo,
  • Lala Rukh,
  • Mahjabeen Memon,
  • Muhammad Mohsin Memon,
  • Sabir Ali Kalhoro

摘要

This study presents the design and implementation of an AI and IoT-enabled Home Energy Management System (HEMS) tailored for hybrid renewable energy integration in residential settings, focusing on rural areas of Sindh, Pakistan. Buildings contribute to nearly one-third of global final energy use, highlighting the urgent need for smart solutions that optimise energy consumption. The proposed HEMS incorporates real-time monitoring, supply and demand-side management strategies, and automation to enhance energy efficiency and reduce dependence on conventional grid power. The system architecture includes an ESP8266-based IoT module, cloud integration via ThingSpeak, and an Android application developed using MIT App Inventor for user control. Experimental results from a working prototype, consisting of a 3-kWh solar PV system, battery storage, and connected household loads – demonstrate a 23–28% reduction in grid energy consumption. The system also enhances user comfort through temperature-based appliance control. This research contributes a scalable, low-cost model for under-resourced regions, supporting Pakistan’s energy resilience and global sustainable development goals.