Drones and AI On-Farm

**John Hill和Eden Muzzall，T/A E和J Farming在Littledale** 正在与中央兰开夏大学（UCLan）和Myerscough学院合作开发一个大胆，雄心勃勃和创新的解决方案，这将彻底改变不太受欢迎的地区的畜牧业农民如何在他们的农场业务中日常运作，同时也利用行业子部门的新机会，并在更广泛的英国研究社区内加速创新。这个以生产力和可持续发展为重点的试点 ** 项目将调查并演示如何使用无人机和人工智能软件进行牲畜管理，以便在问题成为重大问题之前检测到问题。它将提供一种更好的方式来定期检查农场的动物，按需向农民提供准确的信息，并在动物失踪或需要关注动物健康和福利的情况下进行早期干预，它还可以减少我们对化石燃料车辆的依赖。目前的方法严重依赖劳动时间投入和人类判断。使用基于人工智能的软件可以消除人为错误的机会，并减少劳动时间投入。无人机连同其传感器和软件可以被设计成检测温度变化，因此，使我们能够监测进入季节（温度上升）的奶牛，支持更集中的产犊期。该技术还提供了动物体温异常的及时早期指示，以便可以快速进行治疗或干预。这些信息将有可能降低抗生素的使用和死亡率，同时也会提高动物的健康、福利和生产力。项目目标：* 减少农民花在覆盖大空间上的时间，使农民可以专注于其他业务领域并提高生产力 * 减少对化石燃料的依赖，以实现更好的可持续性和环境影响，并逐步实现净零排放 * 通过简化运营和使用强大的数据分析来提高农场的弹性。一个关键目标 ** 是降低无人机部署的技能，使所有农民都能使用无人机。这将包括开创性地使用“无人机在盒子里”的解决方案。中央兰开夏将与用户体验专家协商，设计一个界面，重点是清晰度和易用性，只提供必要的信息时，它是必要的，从而减少农民的学习曲线。

**John Hill and Eden Muzzall, T/A E and J Farming in Littledale** are working in partnership with The University of Central Lancashire (UCLan) and Myerscough College on the development of a bold, ambitious, and innovative solution that will revolutionise how livestock farmers from less favoured areas operate day-to-day in their farm business, while also exploiting new opportunities within industry subsectors and accelerating innovation within wider UK research communities.**This productivity and sustainability-focused pilot** project will investigate and demonstrate how using drones and artificial intelligence software for livestock management can detect issues before they become major problems. It will provide a better way to regularly inspect animals on a farm, provide on-demand accurate information to the farmer and enable early interventions should an animal go missing or needs attention on the grounds of animal health and welfare, and it can also reduce our reliance on fossil-fuelled vehicles.Current methods rely heavily on labour time input and human judgment. The use of AI-based software can remove the chance of human error and lower labour time input. A drone, together with its sensors and software can be designed to detect temperature changes, therefore, giving us the ability to monitor cows which are coming into season (where their temperature rises), supporting a more concentrated calving period. The technology also provides a timely early indication of animal temperature anomalies so that treatment or interventions can be administered quickly. This information will potentially lower antibiotic use and mortality rates, whilst also increasing animal health, welfare, and productivity.**Project aim:*** Reduce the amount of farmer's time spent on covering large spaces so farmers can focus on other areas of their businesses and improve productivity* Reduce the reliance on fossil fuels to have better sustainability and environmental impact and progression towards net zero emissions* Increase farm resilience by streamlining operations and using robust data analytics.**A key objective** is to de-skill drone deployment to make it accessible to all farmers. This will include pioneering the use of 'drone in a box' solutions. UCLan will consult with user experience specialists to design an interface that is focused on clarity and ease of use, providing only the necessary information when it is required thereby reducing the learning curve for farmers.