Collaborative Research: CNS: Medium: Energy Centric Wireless Sensor Node System for Smart Farms

在过去的几十年里，畜牧业得到了加强，动物越来越多地作为大群体来管理。由于动物通常被安置在偏远的大片牧场上，因此对动物健康和福利的持续监测是一项劳动密集型工作，而且具有挑战性。本项目旨在开发基于太阳能传感器的智能农场物联网网络，用于智能动物监测，该网络具有通用性、可靠性和抗网络攻击能力，并在真实农场中演示其可操作性和实用性。太阳能传感器网络将利用低功耗广域网，使动物护理人员能够通过互联网远程监控牛的行为和健康。拟议的研究将为建立节能、可扩展、通信高效的动物农场系统提供基础进展，同时确保在不确定、动态和敌对的智能农场环境下的高监测质量。该项目的成功将通过准确观察、衡量和应对动物农业系统的变化，为农场管理系统做出贡献。提出的工作将设计一个以能源为中心的解决方案，主动安排通信和计算，以最大限度地减少能源收集环境中的能源浪费。该传感器节点将监测动物的生物特征、加速度和位置，并由太阳能供电。该提案进一步构建了一个物理和中等访问通信层，该层主动意识到低能量传感器和更有能力的LoRa（远程）网关之间的能量不匹配。无线技术的采用引入了网络安全漏洞，因此，通过利用信念模型和深度学习技术，同时保持高质量的监控服务，网络安全是所提议系统的另一个主要设计目标。拟议中的传感器网络将在弗吉尼亚理工大学的农场试验台进行测试，该试验台旨在测试和展示放牧牲畜的此类技术。该研究还将有利于半导体设备、嵌入式系统、物联网（IoT）设备、无线通信（包括5G及以后）、鲁棒机器/深度学习、网络安全、统计信号检测和农业生产等领域。该项目将率先开展变革性研究，以提高畜牧业的生产力，并允许对进步进行实际测试。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.