Proceedings of the 8th URSI-NG Annual Conference (URSI-NG 2024)

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Development of an AI-Enabled Raspberry Pi Robot for Monitoring and Combating Illegal Logging Activity

Authors
Ayobami O. Adedokun1, *
1Department of Computer Engineering, Federal University of Technology, PMB 704, Akure, Ondo State, Nigeria
*Corresponding author. Email: aayoadedokun@gmail.com
Corresponding Author
Ayobami O. Adedokun
Available Online 4 February 2025.
DOI
10.2991/978-94-6463-644-4_13How to use a DOI?
Keywords
Artificial Intelligence; Logging; Robot; Forest; Climate Change
Abstract

Preserving natural ecosystems and biodiversity is crucial for fostering a fair and equitable society, promoting economic functionality, and securing a sustainable future. However, illegal logging activities recently in Nigeria have been posing a significant threat to the forests, the natural environment, leading to adverse consequences such as deforestation and loss of biodiversity with great effect on climate change. The surge in illegal logging can be attributed to various factors, including economic hardship, high youth unemployment rates, and corruption among officials. Addressing these challenges requires innovative solutions. This research proposed the development of an Artificial intelligent robot that intelligently sensed and recognize the sounds of chainsaws or tree-cutting activities along a predetermined route. Upon detecting such sound, the robot will promptly alert the forest guards or law enforcement agents and provide them with the GPS coordinates of the source of the noise, facilitating quick identification of the affected area. The AI model for the design is trained through edge impulse and loaded on raspberry pi with microphone as input for sound detector, GPS sensor and GSM module for the alert system and the monitoring is done in real time. Through integration of AI and Robotics, this research aims to combat illegal logging activity, safeguard forest ecosystems and mitigate climate change impacts in Nigeria.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 8th URSI-NG Annual Conference (URSI-NG 2024)
Series
Advances in Physics Research
Publication Date
4 February 2025
ISBN
978-94-6463-644-4
ISSN
2352-541X
DOI
10.2991/978-94-6463-644-4_13How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ayobami O. Adedokun
PY  - 2025
DA  - 2025/02/04
TI  - Development of an AI-Enabled Raspberry Pi Robot for Monitoring and Combating Illegal Logging Activity
BT  - Proceedings of the 8th URSI-NG Annual Conference (URSI-NG 2024)
PB  - Atlantis Press
SP  - 131
EP  - 143
SN  - 2352-541X
UR  - https://doi.org/10.2991/978-94-6463-644-4_13
DO  - 10.2991/978-94-6463-644-4_13
ID  - Adedokun2025
ER  -