Design and Development of a Fog-Assisted Elephant Corridor over a Railway Track

Manash Kumar Mondal, Riman Mandal (), Sourav Banerjee, Utpal Biswas, Jerry Chun-Wei Lin, Osama Alfarraj and Amr Tolba
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Manash Kumar Mondal: Department of Computer Science and Engineering, University of Kalyani, Kalyani 741235, India
Riman Mandal: Department of Computer Science and Engineering, University of Kalyani, Kalyani 741235, India
Sourav Banerjee: Department of Computer Science and Engineering, Kalyani Government Engineering College, Kalyani 741235, India
Utpal Biswas: Department of Computer Science and Engineering, University of Kalyani, Kalyani 741235, India
Jerry Chun-Wei Lin: Department of Computer Science Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, 5063 Bergen, Norway
Osama Alfarraj: Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia
Amr Tolba: Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia

Sustainability, 2023, vol. 15, issue 7, 1-20

Abstract: Elephants are one of the largest animals on earth and are found in forests, grasslands and savannahs in the tropical and subtropical regions of Asia and Africa. A country like India, especially the northeastern region, is covered by deep forests and is home to many elephants. Railroads are an effective and inexpensive means of transporting goods and passengers in this region. Due to poor visibility in the forests, collisions between trains and elephants are increasing day by day. In the last ten years, more than 190 elephants died due to train accidents. The most effective solution to this collision problem is to stop the train immediately. To address this sensitive issue, a solution is needed to detect and monitor elephants near railroad tracks and analyze data from the camera trap near the intersection of elephant corridors and railroad tracks. In this paper, we have developed a fog computing-based framework that not only detects and monitors the elephants but also improves the latency, network utilization and execution time. The fog-enabled elephant monitoring system informs the train control system of the existence of elephants in the corridor and a warning light LED flashes near the train tracks. This system is deployed and simulated in the iFogSim simulator and shows improvements in latency, network utilization, and execution time compared to cloud-based infrastructures.

Keywords: fog computing; Internet of Things; cloud computing; train–elephant collision; monitoring framework; latency; network usage (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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