Forest auditory surveillance system

Abstract

Deforestation is a serious problem worldwide, with an estimated 10 million hectares of forests lost each year [1]. The loss of forests can have a significant impact on the environment, including climate change, loss of biodiversity, and soil erosion [2]. Illegal logging, often carried out using chainsaws, is a major contributor to deforestation in many areas. The team designed the forest auditory surveillance system (FASS) to provide a cost effective and efficient way to detect illegal logging in forests. FASS takes in sound data as input and produces notifications and analytics as output. The development of FASS involved the utilisation of various tools and technologies like Arduino Nano RP2040 Connect for the edge device, Angular and TypeScript for the web portal, TensorFlow for the Machine Learning model and React Native Expo framework for the Mobile Application. The system was able to undergo different types of testing to make sure it works as intended including functional testing, performance testing, integration testing and regression testing. In terms of service and maintenance for FASS, a comprehensive user manual to guide users in effectively utilising the system will be provided. The responsibility for maintaining the system, rests on the development team to ensure that the system is operating smoothly and that any issues that may arise, are addressed. The successful implementation of such a system requires collaboration among various stakeholders, including the National Forestry Authority, researchers, forest management organisations, and local communities.