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Towards Smart Home Automation Using IoT-Enabled Edge-Computing Paradigm.

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Summary
This summary is machine-generated.

This study introduces an affordable smart home system using Raspberry Pi and edge computing for integrated automation, security, and energy efficiency. The system enhances convenience and privacy while reducing costs and bandwidth usage.

Keywords:
cloud computingedge computinghome automationinternet of thingsraspberry pismart home

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Area of Science:

  • Computer Science
  • Electrical Engineering
  • Internet of Things

Background:

  • Smart home technology adoption is rapidly increasing, driven by Internet of Things (IoT) advancements.
  • Existing systems often lack integrated solutions for automation, security, safety, and energy efficiency.
  • Resource constraints in computation, bandwidth, and cost limit the scalability of current smart home applications.

Purpose of the Study:

  • To develop a cost-effective, integrated smart home automation system.
  • To address limitations in existing systems by simultaneously managing automation, security, safety, and energy consumption.
  • To leverage the Internet of Things (IoT) and edge computing on a resource-constrained platform.

Main Methods:

  • Deployment of a smart home automation system utilizing a Raspberry Pi (RPI) as the central control unit.
  • Integration of various home devices and sensors via the Internet, enabled by the RPI.
  • Application of the edge computing paradigm for local data processing and storage on the RPI to reduce bandwidth and costs.

Main Results:

  • The proposed system demonstrates improved performance compared to state-of-the-art solutions.
  • Achieved 5% faster motion detection and significantly quicker relay switching times (5 ms on, 4 ms off).
  • Exhibits 6% greater energy efficiency, indicating a more sustainable smart home solution.

Conclusions:

  • The developed system offers a practical and economical solution for comprehensive smart home management.
  • Edge computing enhances privacy by processing sensitive data locally and reduces operational costs.
  • The system provides a scalable and efficient platform for future smart home innovations.