A proposal model using deep learning model integrated with knowledge graph for monitoring human behavior in forest protection

Abstract

In conventional monitoring of human behavior in forest protection, deep learning approaches can be detected human behavior significantly since thousands of visitors’ forest protection is abnormal and normal behaviors coming to national or rural forests. This paper has presented a new approach using a deep learning model integrated with a knowledge graph for the surveillance monitoring system to be activated to confirm human behavior in a real-time video together with its tracking human profile. To confirm the proposed model, the proposed model has been tested with data sets through case studies with real-time video of a forest. The proposed model provides a novel approach using face recognition with its behavioral surveillance of the human profile integrated with the knowledge graph. Experimental results show that the proposed model has demonstrated the model’s effectiveness.