Application of Improved YOLO-LSTM with Combined MQTT-LoRaWAN for AI Surveillance in Tea Plantations to Prevent Elephant Intrusion

Elephant-human conflict is a growing problem in tea garden areas of Dooars in North Bengal, resulting in massive cost for crops, infrastructures and sometimes human life as well. Each year, these mild-mannered giants destroy crops, destroy fences and even threaten the locals, which raises the costs of repairs and endangering lives. The conventional deterring methods, such as fences, firecrackers, and patrols are mostly ineffective, unsustainable or cruel to the animals. As a way of addressing this predicament, scholars have designed a non-invasive, intelligent surveillance system named HIS-Hexagonal Intelligent Surveillance. HIS integrates state-of-the-art machine learning with artificial intelligence by combining an improved YOLO-LSTM and MQTT-LoRaWAN, which combines the capabilities of distributed-based agents with predictive analytics and hex-grid mapping scheme. HIS is an effective solution for elephant intrusions detection and deterrence for ecological balance. The system sends specific warnings before the elephants can cause havoc when an intrusion is detected. The hex-grid mapping enables the operators to have accurate spatial knowledge and the predictive analytics forecasts the time and location where the elephants could roam. The virtual simulation of the proposed work shows 98% accuracy on designed-custom dataset of elephants. The paper offers a background of the architecture, theoretical framework, algorithm models, and expected benefits of the proposed framework.

@article{Mullick2025,
  title     = {Application of Improved YOLO-LSTM with Combined MQTT-LoRaWAN for AI Surveillance in Tea Plantations to Prevent Elephant Intrusion},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {16},
  number    = {12},
  year      = {2025},
  publisher = {The Science and Information Organization},
  author    = {Rabin Kumar Mullick and Rakesh Kumar Mandal},
  doi       = {10.14569/IJACSA.2025.0161212},
  url       = {https://doi.org/10.14569/IJACSA.2025.0161212}
}