Combatting Illegal Logging with AI-powered IoT Devices for Forest Monitoring

Abdullah Khan, Hamza Ali, Maham Jadoon, Zain Ul Abideen, Nasru Minuallah
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Abdullah Khan, Hamza Ali, Maham Jadoon, Zain Ul Abideen, Nasru Minuallah: Computer Systems Engineering University of Engineering and Technology, Peshawar, Pakistan

International Journal of Innovations in Science & Technology, 2024, vol. 6, issue 5, 134-142

Abstract: This research presents a comprehensive strategy for tackling illegal logging by leveraging Artificial Intelligence (AI) and Internet of Things (IoT) technologies. In high-risk forestry areas, sensors-equipped Internet of Things devices are used to continuously monitor and detect the sound of the surroundings. The AI component uses machine learning methods to identify potential unlawful logging activities by accurately detecting and distinguishing sound patterns associated with chainsaw and logging operations such as tree cutting and also detecting natural disasters like wildfires. When such activities are detected by these smart AI-powered IoT devices installed in the forest, real-time notifications are generated after such activity which allows surrounding enforcement agencies, such as the forest department, to intervene promptly. By providing a targeted and prompt solution to the issue of illicit logging, this strategy supports biodiversity preservation and sustainable forest management.

Keywords: Forest Monitoring; AI Against Illegal Logging; Real-time Alerts; Environmental Conservation; IoT for Anti- Logging (search for similar items in EconPapers)
Date: 2024
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