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Energy-, Cost-, and Resource-Efficient IoT Hazard Detection System with Adaptive Monitoring.

Chiang Liang Kok1, Jovan Bowen Heng1, Yit Yan Koh1

  • 1College of Engineering, Science and Environment, University of Newcastle, Callaghan, NSW 2308, Australia.

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Summary

This study introduces an affordable IoT system using ESP32-CAM and AI for real-time hazard sign detection. It saves energy through adaptive monitoring, offering a cost-effective safety solution.

Keywords:
CNNESP32-CAMIoTadaptive monitoringcost-effective solutionsenergy efficiencyhazard detectionreal-time alerts

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Area of Science:

  • Internet of Things (IoT)
  • Artificial Intelligence (AI)
  • Embedded Systems
  • Safety Engineering

Background:

  • Industrial and public safety compliance necessitates robust hazard detection systems.
  • Existing solutions often involve high costs, complex infrastructure, and subscription fees.
  • There is a need for energy-efficient, cost-effective, and adaptable hazard detection technologies.

Purpose of the Study:

  • To develop and evaluate an energy-efficient, cost-effective IoT-based hazard detection system.
  • To implement real-time classification of various hazard signs using a custom Convolutional Neural Network (CNN).
  • To demonstrate significant energy savings through an adaptive monitoring mechanism.

Main Methods:

  • Utilized an ESP32-CAM microcontroller with temperature (DHT22) and motion (PIR) sensors.
  • Developed a custom CNN model deployed on a Flask server for real-time hazard sign classification.
  • Implemented an adaptive monitoring mechanism to dynamically adjust image capture frequency, optimizing energy consumption.

Main Results:

  • Achieved high classification accuracy with an F1 score of 85.9% for hazard signs.
  • Demonstrated significant energy savings of 31-37% compared to continuous monitoring.
  • The system achieved a low unit cost of approximately USD 28.50, utilizing free Telegram notifications.

Conclusions:

  • The proposed IoT system offers a highly accurate, energy-efficient, and cost-effective solution for hazard detection.
  • The adaptive monitoring and low-cost components make it suitable for resource-constrained environments.
  • The system provides a scalable and adaptable approach for enhancing safety in industrial and public settings.