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TreeHelper: A Wood Transport Authorization and Monitoring System.

Alexandru-Mihai Zvîncă1, Sebastian-Ioan Petruc1, Razvan Bogdan1

  • 1Department of Automation and Computing, Politehnica University Timisoara, 300006 Timisoara, Romania.

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Summary

TreeHelper is an IoT system that uses edge AI and a web platform to monitor tree logging trucks, improving authorization and environmental protection. This solution enables faster action by authorities through real-time alerts for unauthorized transport.

Keywords:
4GEdgeAIIoTRaspberryPiTPUclouddeforestation monitoring

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Area of Science:

  • Internet of Things (IoT)
  • Artificial Intelligence (AI)
  • Environmental Monitoring

Background:

  • Current methods for monitoring timber transport lack efficiency.
  • Unauthorized logging poses a significant threat to environmental conservation efforts.

Purpose of the Study:

  • To develop an IoT solution, TreeHelper, for real-time monitoring and authorization of tree logging trucks.
  • To enhance the speed and effectiveness of environmental authorities' responses to illegal logging activities.

Main Methods:

  • Implementation of a web platform (Spring Boot, React, PostgreSQL) for authorization requests and reviews.
  • Deployment of an edge AI device (Raspberry Pi, YOLOv11n model, Coral USB Accelerator) on logging trucks for real-time detection.
  • Integration with a cloud Automatic License Plate Recognition (ALPR) service and 4G communication for data acquisition and alerts.

Main Results:

  • Edge TPU acceleration significantly improved throughput (doubled) and reduced inference latency (halved) compared to CPU-only execution.
  • The YOLOv11n model achieved high validation performance (precision=0.948, recall=0.944).
  • The system successfully detected unauthorized trucks and alerted authorities with GPS coordinates and license plate information.

Conclusions:

  • TreeHelper provides an effective IoT solution for real-time monitoring of timber transport.
  • The system enhances the ability of authorities to act swiftly against illegal logging, contributing to environmental protection.
  • The integration of edge AI and cloud services offers a scalable and efficient approach to environmental monitoring.