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

合作研究：CNS：媒介：用于智能农场的以能源为中心的无线传感器节点系统

基本信息

批准号：
2106987
负责人：
Dong Ha
金额：
$ 57.38万
依托单位：
Virginia Polytechnic Institute and State University
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2025-09-30
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2106987&HistoricalAwards=false
关键词：
Collaborative Research CNS Medium Energy

项目摘要

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.

在过去的几十年里，畜牧业得到了加强，动物越来越多地被作为大群体进行管理。由于动物往往位于偏远的大片牧场上，持续监测动物的健康和福祉是劳动密集型和挑战性的。本项目旨在开发一个基于太阳能传感器的智能农场物联网网络，该网络具有通用性、可靠性和对网络攻击的健壮性，用于智能动物监控，并在实际农场上展示其操作和实用性。太阳能传感器网络将利用低功率、广域网络，使动物护理人员能够通过互联网远程监测牛的行为和健康。这项拟议的研究将为建立一个节能、可扩展、通信高效的动物养殖场系统提供根本性的进步，同时确保在不确定、动态和恶劣的智能农场环境下的高监控质量。该项目的成功将有助于通过准确地观察、测量和响应畜牧业系统中的变化来建立农场管理系统。拟议的工作将设计一个以能源为中心的解决方案，该解决方案将主动调度通信和计算，以最大限度地减少能源收集环境中的能源浪费。建议的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。该提议进一步建立了一个物理和中等接入通信层，该层主动意识到低能量传感器和功能更强的LORA(远程)网关之间的能量不匹配。无线技术的采用带来了网络安全漏洞，因此，网络安全是拟议系统的另一个主要设计目标，它利用信念模型和深度学习技术，同时保持高质量的监测服务。拟议的传感器网络将在弗吉尼亚理工大学的农场试验台上进行测试，该试验台旨在测试和展示用于牧场牲畜的此类技术。这项研究还将有益于半导体设备、嵌入式系统、物联网(IoT)设备、包括5G及以上的无线通信、稳健的机器/深度学习、网络安全、统计信号检测和农业生产等领域。该项目将开创变革性研究的先河，以提高畜牧业的生产率，并允许对进步进行现实世界的测试。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。