<![CDATA[Illegal tree cutting is a pervasive and destructive global problem that leads to deforestation, loss of biodiversity, habitat destruction, and contributes to climate change. It poses a significant threat to the environment, including fragile ecosystems and the vital services they provide, such as carbon sequestration and clean water supply. Traditional methods of detecting illegal tree cutting often rely on manual patrols, which are costly, time-consuming, and can be ineffective, especially in remote and challenging terrains. By utilizing AI and solar power, the project offers an efficient and scalable alternative to monitor and detect tree cutting activities in areas where human presence may be limited or impractical. TensorFlow Lite, as a lightweight deep learning framework, enables real-time inference on low-power devices like the Raspberry Pi. The functionality of the robot as a tree cutting detector was tested five times with different types of tree cutting tools. Success rate was determined by its functionality; 100% success rates in detecting tree cutting and non-tree cutting activities and sending an SMS message after detection indicates proper functionality. By using a monitor it can display the accuracy of the device’s detection through a message on the top left corner of the camera’s screen. After at least sixty seconds of the device continuously detecting tree cutting activities it sends an SMS to the registered mobile number alerting the recipient of tree cutting activities being detected.]]>
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