A Smart Deforestation Monitoring and Control System Model

One of the greatest challenges facing effective forest management in the world is the increasing rate of illegal logging and encroachment. This ismore rampant in the tropical rainforest ecosystem of Nigeria due to its richness in desirable tropical hardwood timber species and fertile land. Government policies, institutional support in forest management and enlightenment have not succeeded in eliminating this menace. This situation presents real challenges to professionals in forest management that it has become difficult to determine the future of tropical rainforest ecosystem in Nigeria and other developing countries due to the negative impacts of illegal logging include increased incidences of global warming, environmental degradation, biodiversity, loss of revenue to government and so on. Therefore, the need to develop effective intelligent strategies or solutions to combat the menace has become inevitable. This work presents the Model design and implementation of a Deforestation Control and Monitoring System with an intelligent framework for deforestation detection and control system using machine learning algorithm and wireless sensor network, that take proactive and reactive measures to curb deforestation. The proposed system consists of four layers -the physical layer, the communication layer, Knowledge layer, and presentation layer. The system is developed in an environment characterized by Unity 3D incorporated with C# as the front end and MySQL as the backend. Unity 3D simulation tool is used for the experimental test bed and python is used for image processing and classification.