Implementing IoT for Sustainable Agriculture and Livestock Health Monitoring

Abstract

This project presents the design and implementation of a smart agriculture and livestock health monitoring system based on Internet of Things (IoT) technology, developed to support farmers in rural and semi-urban areas. The system uses various sensors—including the DHT11 for temperature and humidity, MQ135 for detecting air quality, a soil moisture sensor, a rain detector, and the DS18B20 for monitoring animal body temperature—all connected through an ESP32 microcontroller. The data collected from the environment and animals is transmitted to cloud platforms like ThingSpeak and Google Sheets for real-time monitoring and data logging. To assist in timely agricultural decisions, simple forecasting techniques are used in Python (via Google Colab) to predict next-day values of temperature, humidity, soil moisture, rainfall, and gas levels. These predictions are based on recent sensor data and help in making informed decisions regarding irrigation and farming activities. The system includes an automated irrigation control feature that activates the water pump based on both real-time and forecasted soil moisture readings, promoting efficient water use. The system also checks whether current conditions are suitable for cultivating particular crops and identifies possible risks, such as high gas concentration or excessive humidity that could lead to fungal issues. For livestock health, it continuously tracks animal body temperature and sends instant alerts via Telegram to the medical team if any unusual readings are detected, allowing timely action and care. This IoT-based solution offers a low-cost, automated, and practical system that can be easily used by small-scale farmers. It helps improve crop management, save resources like water, and ensure better livestock health, contributing to more sustainable and productive agriculture.