Fog Assisted Tiger Alarming Framework for Saving Endangered Wild Life

Abstract

Real-time monitoring is necessary for saving endangered wildlife. The camera-trapping technology is used to monitor wild animals like tigers, lions, bears etc. in forests. Due to changes in the forest echo system and the expansion of human civilization near the forest, tigers often enter the villages. As a consequence, the Tiger-Human conflict occurs more frequently. Typically, cloud computing technologies are used for storing and processing the image data generated from trap cameras. A wildlife monitoring system is a time-sensitive application, and processing and decision-making using cloud computing are relatively slow. Timeliness and quick response are essential for these types of applications. Highlighting this issue, this article focuses on the design and development of a fog-assisted tiger alarming framework that detects tigers in the corridor. The application also delivers systematic alerts to the villagers. Therefore, the conflict between humans and tigers will reduce. For comparison, we have deployed the same model in a cloud computing environment. The proposed framework is simulated in the iFogSim simulator. The outcome exhibits that the proposed fog-based model successfully reduces latency and network usage compared to the traditional cloud-based model. The comparative analysis also indicates a significant improvement in the execution time over the cloud system.