SBIR Phase I: Connected Livestock: Farm Animal Health Monitoring and Virtual Fencing Internet of Things (IoT) Device

小型企业创新研究(SBIR)第一阶段项目的更广泛影响/商业潜力是，通过协助牧场主/农民就何时何地放牧做出更明智的决定，实现全面的农场管理，同时通过再生农业将对环境的负面影响降至最低。这项创新使实时监测动物健康成为可能，以协助疾病控制和预防。管理不善的牲畜系统造成了各种环境和健康问题。该项目包括物联网、传感器、机器学习和无线通信方面的创新，当应用于农业实践时，旨在从动物健康、环境、生产力和农场经济的角度改变牧场主和农业企业管理农场的方式。这一创新可能会对农业增效和降低成本产生影响。农民将能够使用该平台的传感器收集的数据来跟踪和调节动物的运动，对动物的活动和行为进行分类，并实时预测和监测动物的健康。及早发现对健康的影响，可以在更大范围内进行预防性或早期治疗，以及疾病控制和预防。这个SBIR第一阶段项目旨在开发一个物联网(IoT)平台，能够实时跟踪各种数据，包括动物运动(如位置和方向)、动物活动(如行走、放牧等)、动物行为和动物健康。这些传感器数据是监测和评估对动物健康保护至关重要的一系列变量的理想选择。拟议的动物管理系统具有变革性，因为它能够在使用最小功率的情况下收集精确的多传感器数据，无线通信数据，并且运行时间更长。这些功能将收集关于动物运动、活动和健康的实时数据，从而能够对动物进行准确的分析、表征和监控。拟议的研究和开发活动将集中于优化惯性测量单元(IMU)传感器和其他组件，以实现有效的动物控制，描述动物活动和行为，并开发用于实时监测动物健康的机器学习模型。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。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to enable holistic farm management by assisting ranchers/farmers in making more informed decisions about when and where to graze their livestock while minimizing negative environmental impacts through regenerative farming. The innovation enables monitoring of animal health in real time to assist in disease control and prevention. Poorly managed livestock systems have resulted in a variety of environmental and health problems. The project, which includes innovation in the Internet of Things, sensors, machine learning, and wireless communications, when applied to farming practices, seeks to alter how ranchers and agricultural businesses manage farms in terms of animal health, the environment, productivity, and farm economics. The innovation may have an impact on agricultural efficiency and cost reduction. Farmers will be able to track and regulate animal movement, classify animal activity and behavior, and predict and monitor animal health in real time using data collected by the platform's sensors. Early detection of health impacts enables preventive or early-stage treatments, as well as disease control and prevention on a broader scale.This SBIR Phase I project seeks to develop an Internet of Things (IoT) platform capable of tracking a variety of data in real time, including animal movement (e.g., location and direction), animal activity (walking, grazing, etc.), animal behavior, and animal health. These sensor data are ideal for monitoring and evaluating a range of variables critical to animal health protection. The proposed animal management system is transformational because it is capable of gathering precise multi-sensor data while using minimal power, communicating data wirelessly, and running for an extended period of time. These capabilities will gather real-time data on the animal's movement, activity, and health, enabling accurate analysis, characterization, and monitoring of the animals. The proposed research and development activities will focus on optimizing intertial measurement unit (IMU) sensors and other components for efficient animal control, characterization of animal activity and behavior, and development of machine learning models for real time monitoring of animal health.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.