Smart Cattle Health Monitoring and Farming Productivity Management Using IOT and CNN

The agricultural industry plays a pivotal role in supporting global food security and sustaining economies. Within this industry, cattle farming represent a significant sector, providing essential resources like meat, milk, and other dairy products. However, traditional cattle farming practices often face challenges related to monitoring, managing, and predicting various aspects of cattle health and productivity. In recent years, the advent of technology has opened up new possibilities for transforming traditional farming practices into more efficient, data-driven systems. The integration of smart devices, IoT sensors, machine learning algorithms, and real-time data analytics has paved the way for innovative solutions that can address the limitations of conventional cattle farming. The integrated embedded system proposed in this paper aims to revolutionize cattle farming practices by providing a comprehensive solution to enhance cattle well-being and optimize farming efficiency. It encompasses four crucial areas: real-time monitoring and health management, milk production prediction, artificial insemination scheduling, and disease analysis with first aid recommendations. By utilizing cutting-edge IoT, sensors, machine learning algorithms, and image recognition techniques the system enables farmers to monitor cattle health in real-time, predict milk production accurately, schedule artificial insemination effectively, and promptly identify and manage cattle skin diseases. Overall, the system has archived 91% high accuracy through these advancements, also empowers farmers to make data-driven decisions, ensuring proactive measures to prevent health issues, enhance productivity, and fosters a sustainable and profitable agriculture industry.