One of the significant challenges confronting our society today is ensuring the health and productivity of dairy herds which are vital to our food supply. Diseases such as mastitis and lameness pose a continuous threat to the economic viability of dairy farms. In response to these challenges, our project aims to harness the potential of modern Cyber-Physical Systems (CPS), advanced data analytics, AI/Machine Learning technologies to deliver a comprehensive solution for disease control in dairy farming. We aim to develop an innovative, integrated system to manage and improve dairy herd health effectively and sustainably. Our approach leverages state-of-the-art biosensors for real-time disease detection and a unique social network model that monitors animal-environment and animal-animal interactions. We also develop a digital twin platform for the farm to answer what-if questions for disease control decisions. This not only improves our understanding of disease transmission but also empowers dairy farm personnel with timely information for optimized herd management. This project is realized in collaboration with a dairy farm in the state of Tennessee and is anticipated to have nationwide implications.The proposed research engages in several critical areas of data analytics, disease control, and farm management, such as: (1) the development and optimization of innovative biosensors for real-time disease detection, (2) the creation of a farm-wide, real-time cow-based social network to track the mobility patterns of cows and their interactions, (3) the application of AI and big-data analytics to process, interpret and learn from the extensive data generated, and (4) the implementation and validation of the proposed system on real-world dairy farms, facilitating the transition from research to practice. Our close collaboration with farm management facilitates the broader impacts of the proposed work. Our findings will be disseminated across various platforms, targeting the scientific community, precision agriculture researchers, and the general public. Our educational initiatives and community engagement efforts will target the new generation of scientists and researchers, particularly encouraging participation from underrepresented groups, including African-Americans, Native Americans, Hispanics, and female students. The outcomes of our research, as well as all relevant educational resources produced during this project, will be accessible to the public via our project's online website.