Project Overview: IoT-Based Smart Health Monitoring Belt for Farm Animals The IoT-Based Smart Health Monitoring Belt for Farm Animals is an innovative project designed to enhance the welfare, productivity, and management efficiency of livestock through advanced technology. Livestock management is a critical aspect of modern agriculture, and timely monitoring of animal health can prevent disease outbreaks, reduce mortality rates, and increase overall farm productivity. This project addresses these challenges by integrating Internet of Things (IoT) technology, real-time data monitoring, and predictive analytics into a wearable belt system for farm animals. The core of the system is the ESP32 microcontroller, which serves as the central processing unit for collecting and transmitting data from various sensors. The belt is equipped with multiple sensors, including a temperature sensor to monitor body heat, a pulse rate sensor to track heart activity, a motion sensor for activity and behavior analysis, and an air quality sensor to measure the environmental conditions surrounding the animal. These sensors continuously collect physiological and behavioral data, which is then transmitted via Wi-Fi to a cloud-based dashboard for real-time monitoring. Farmers and veterinarians can access this dashboard through smartphones or computers, allowing them to track animal health remotely and efficiently. An important feature of the belt is its predictive analytics capability. Using embedded machine learning models, the system can detect signs of stress, abnormal behavior, or early symptoms of diseases. This predictive functionality allows farmers to take proactive measures, such as adjusting feed, administering treatment, or consulting a veterinarian, before a minor issue escalates into a serious health problem. The belt’s real-time alerts ensure that farmers are immediately notified of any critical conditions, minimizing livestock losses and reducing manual monitoring effort. The project also focuses on sustainability and scalability. The belt is powered by a solar panel with a rechargeable battery, ensuring uninterrupted operation even in remote farm locations without reliable electricity. Its lightweight and ergonomic design ensures comfort for the animals, making it suitable for long-term usage. The modular nature of the system allows easy addition or replacement of sensors, making the belt adaptable for different types of livestock and farm requirements. Software-wise, the project utilizes Arduino IDE for programming the ESP32, while the cloud dashboard is implemented using platforms like ThingSpeak or Blynk, which allow visualization of historical data, live graphs, and custom alerts. Additionally, the system can integrate with Python-based predictive models for more advanced stress or disease detection analytics. This combination of hardware and software creates a comprehensive solution that bridges traditional livestock management practices with modern data-driven approaches. In summary, the IoT-Based Smart Health Monitoring Belt significantly improves livestock management by providing real-time monitoring, predictive health alerts, and sustainable operation. It reduces veterinary costs, minimizes losses due to undetected diseases, and empowers farmers to make informed decisions regarding animal care. By leveraging IoT and AI, this project exemplifies the potential of technology to transform agriculture into a smarter, more efficient, and more humane industry. The smart belt represents not only a technological innovation but also a practical tool that addresses real-world challenges faced by farmers today, ensuring healthier livestock and improved productivity.