Animal agriculture has intensified over the past several decades, and animals are managed increasingly as large groups. As animals are often located remotely on large expanses of pasture, continuous monitoring of animal health and well-being is labor-intensive and challenging. This project aims to develop a solar sensor-based smart farm Internet-of-Things network, which is versatile, reliable, and robust to cyberattacks for smart animal monitoring and to demonstrate its operation and practicality on real farms. The solar sensor network will leverage low-power, wide- area networking to enable animal care personnel to monitor the behavior and health of cattle remotely through the Internet. The proposed research will provide fundamental advances to building an energy-efficient, scalable, communication-efficient animal farm system, while ensuring high monitoring quality under uncertain, dynamic, and hostile smart farm environments. The success of this project will contribute to a farm management system by accurately observing, measuring and responding to variabilities in animal agriculture systems.

The proposed work will design an energy-centric solution that actively schedules communication and computation to minimize energy waste in energy harvesting contexts. The proposed sensor node will monitor biometrics, acceleration, and location of animals and is powered by solar energy. The proposal further builds a physical and medium-access communication layer that is actively aware of the energy-mismatch between the low-energy sensors and the more capable LoRa (Long Range) gateways. The adoption of wireless technologies introduces cybersecurity vulnerabilities, and hence, cybersecurity is another major design objective of the proposed system by leveraging belief models and deep learning techniques while maintaining high quality monitoring services. The proposed sensor network will be tested at Virginia Tech?s farm testbeds, which have been designed to test and showcase such technologies for pastured livestock. The research will also be beneficial to the fields of semiconductor devices, embedded systems, Internet-of-Things (IoT) devices, wireless communications including 5G and beyond, robust machine/deep learning, cybersecurity, statistical signal detection, and agricultural production. The project will pioneer transformative research to increase productivity of animal agriculture and allow for real-world testing of advancements.