Geo-Tagging of Plantation in The Catchment Area of Hydro Project

International Journal of Engineering Innovations and Management Strategies 1 (3):1-13 (2024)
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Abstract

This project centers on developing a geo-tagging and monitoring system for plantations within the catchment area of a hydro project. Designed for the forest department, it provides real-time insights into environmental conditions to support the sustainable management of forest resources. The system comprises an Arduino Uno microcontroller that integrates GPS, DHT11 (temperature and humidity sensor), and LoRa modules to track and communicate critical data, such as the geographic location, temperature, and humidity around each plantation site. Powered by a 7.4V Li-ion battery and regulated through an LM7805 voltage regulator for consistent 5V output, the system is optimized for low power consumption to ensure longevity in remote settings. Using the LoRa module, the system transmits data over long distances to a central receiver, which could be stationed at a monitoring hub. This data transmission operates independently of internet connectivity, making it ideal for isolated forest areas where network coverage is limited or non-existent. Each plant or designated plantation area can be geo-tagged and monitored through data collected by the sensors and sent through LoRa communication. The data is then processed and can be visualized on a server or application interface, giving forest officials an overview of the environmental conditions in each monitored area. This innovative system offers a scalable solution for remote environmental monitoring, allowing for expansion with additional sensors or wider deployment across forest areas. Furthermore, it lays a foundation for enhanced forest management through features like environmental alerts and trend monitoring, potentially aiding in conservation efforts by ensuring optimal conditions for plantation growth. By leveraging IoT technology in an eco-friendly, power-efficient setup, this project presents a modern approach to sustainable forestry and plantation monitoring.

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