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This paper presents a novel approach for integrating artificial intelligence into smart homes. The main goal is to design and implement a standalone unit that will be able to process inputs from sensors, specifically the BH1750 light sensor and the motion sensor, and based on them, autonomously control the intensity of the integrated RGB LED. The resulting model can automatically regulate the brightness of the LED from these data, which is a step towards more energy-efficient and user-friendly technologies. The final part of the article discusses the potential of this solution within decentralized smart homes, where individual autonomous units could function as separate elements of a larger system. This approach suggests new possibilities for implementing intelligent systems that increase self-sufficiency and efficiency of modern home applications.

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Use Case of Implementation Backpropagation for Arduino and ESP32 Microcontrollers into Smart Home

  • 会议论文

  • 发表日期：

    2025年

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  • Tomas Sladcik,
  • Hashim Habiballa

摘要

This paper presents a novel approach for integrating artificial intelligence into smart homes. The main goal is to design and implement a standalone unit that will be able to process inputs from sensors, specifically the BH1750 light sensor and the motion sensor, and based on them, autonomously control the intensity of the integrated RGB LED. The resulting model can automatically regulate the brightness of the LED from these data, which is a step towards more energy-efficient and user-friendly technologies. The final part of the article discusses the potential of this solution within decentralized smart homes, where individual autonomous units could function as separate elements of a larger system. This approach suggests new possibilities for implementing intelligent systems that increase self-sufficiency and efficiency of modern home applications.