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Original Article

Elephant Detection and Repulsion System using IOT, Drones, and LoRa Technology

  • Paper ID 334
  • Volume 6, Issue 3
  • Pages 166-171
  • Published Online: May-June 2026
  • 26 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Sinchana R1
  • Theertha Prasad2
  • Yogini D R3
  • Dr. M B Anandaraju4
  • Dr. Manoj Kumar S B5

1 2 3 B.E. Students, Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, B. G. Nagara, Bengaluru, India. 4 Professor, Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, B. G. Nagara, Bengaluru, India. 5 Associate Professor, Department of Electronics and Communication Engineering, BGS Institute of Technology, Adichunchanagiri University, B. G. Nagara, Bengaluru, India.

Article Information

Published Online
May-June 2026
Pages
166-171
Article Type
Original Article
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Abstract

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Human–Elephant Conflict (HEC) has become a major challenge in forest-border and agricultural regions due to habitat loss and increasing human activities near wildlife areas. Traditional prevention methods often fail to provide early detection, continuous monitoring, and safe elephant deterrence. This paper presents an intelligent IoT-based Elephant Detection and Repulsion System using LoRa communication, GPS tracking, camera verification, and drone technology for real-time wildlife monitoring and conflict prevention. The proposed system integrates piezoelectric vibration sensors with ESP32 microcontrollers and LoRa SX1278 modules to detect elephant movement and transmit alert information over long distances. An ESP32-CAM module is used for visual verification, while a drone equipped with Bluetooth speakers performs non-lethal elephant repulsion using warning sounds. GPS-based tracking and OpenStreetMap integration support accurate location monitoring and intrusion visualization. Experimental analysis indicates improved detection accuracy, reduced false alerts, low power consumption, and minimized human intervention. The proposed system is cost -effective, scalable, eco-friendly, and suitable for smart wildlife monitoring and forest-border protection applications.

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  • ISSN 2583-1240
  • Open Access
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