This paper presents a livestock management system that uses IoT technology to monitor the health of cattle in dairy farms. The system includes sensors for temperature, pulse rate, and GPS, which collect data wirelessly and store it in a MongoDB database. The data is then accessed through a web application developed using Flutter. The system aims to improve the health of cattle by enabling continuous monitoring of vital signs such as temperature and heart rate, allowing for early detection of health issues. This reduces the need for frequent health inspections and long-term healthcare costs for the animals. The system is designed to address the challenges of managing large numbers of cattle in dairy farms, where continuous monitoring is essential. The use of sensor technology allows for the early detection of health problems, which is crucial for maintaining the health and productivity of the cattle. The system also includes a communication module based on the ESP8266 Node MCU, which provides wireless connectivity and ensures data transmission to the farmer. The proposed system is segmented into three parts: detectors, connectivity, and applications. The sensors used in the system include a DHT11 temperature sensor, a MAX30100 pulse sensor, and a NEO-6M GPS sensor. These sensors are connected to the Node MCU, which transmits the data to the web application. The software used includes Arduino IDE for programming the sensors, MongoDB for storing the data, and Flutter for developing the web application. The system is designed to provide real-time monitoring of cattle health, enabling timely and accurate treatment. The integration of infrastructure, hardware, and software components ensures that the system is efficient and effective in monitoring the health of cattle. This technology significantly reduces the need for extensive manual health inspections and ultimately cuts down long-term healthcare costs for dairy farmers. By prioritizing the well-being of each animal, the system enhances farm productivity while ensuring the welfare of the cattle population.This paper presents a livestock management system that uses IoT technology to monitor the health of cattle in dairy farms. The system includes sensors for temperature, pulse rate, and GPS, which collect data wirelessly and store it in a MongoDB database. The data is then accessed through a web application developed using Flutter. The system aims to improve the health of cattle by enabling continuous monitoring of vital signs such as temperature and heart rate, allowing for early detection of health issues. This reduces the need for frequent health inspections and long-term healthcare costs for the animals. The system is designed to address the challenges of managing large numbers of cattle in dairy farms, where continuous monitoring is essential. The use of sensor technology allows for the early detection of health problems, which is crucial for maintaining the health and productivity of the cattle. The system also includes a communication module based on the ESP8266 Node MCU, which provides wireless connectivity and ensures data transmission to the farmer. The proposed system is segmented into three parts: detectors, connectivity, and applications. The sensors used in the system include a DHT11 temperature sensor, a MAX30100 pulse sensor, and a NEO-6M GPS sensor. These sensors are connected to the Node MCU, which transmits the data to the web application. The software used includes Arduino IDE for programming the sensors, MongoDB for storing the data, and Flutter for developing the web application. The system is designed to provide real-time monitoring of cattle health, enabling timely and accurate treatment. The integration of infrastructure, hardware, and software components ensures that the system is efficient and effective in monitoring the health of cattle. This technology significantly reduces the need for extensive manual health inspections and ultimately cuts down long-term healthcare costs for dairy farmers. By prioritizing the well-being of each animal, the system enhances farm productivity while ensuring the welfare of the cattle population.