The use of GPS tracking and the LoRaWAN network to improve productivity of grazing dairy cows

使用 GPS 跟踪和 LoRaWAN 网络提高放牧奶牛的生产力

• 批准号: 105150
• 金额: $ 29.68万
• 依托单位: CHALCOMBE
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=105150
• 关键词: use; GPS; tracking; LoRaWAN; network

"British milk yields per cow have increased by 50% in the past 20 years (AHDB, 2018). Whilst grazed grass is a cheap, sustainable, high quality feed current grazing systems do not support these increased yields so cows are fed supplements or even housed them over the summer to ensure higher feed intakes. Such actions increase feed costs and environmental problems such as slurry disposal.Our vision is to develop a system that will collect cow behavioural data in real-time and use artificial intelligence techniques to determine when best to allocate additional pasture to grazed herds resulting in higher intakes and more milk production from grass. To date there has been a market failure in such applied grassland research as there are few established companies in the sector who would financially benefit from promoting such work.This innovate project will use cow behavioural data to track grazing intensity and determine when best to automatically allocate additional grazing. This will increase milk production from grass and lead to more cows to be grazed more of the time helping to meet society's desire that dairy cows should be grazed at grass.Small collar-mounted sensors with track the cows using GPS signals and monitor their grazing behaviour through accelerometer data. A small proportion of cows in the herd (5-8%) will wear the collars throughout the grazing season and the collected data will be sent via a low power wide area network (LoRaWAN) to the internet. The LoRaWAN system (2015) has a 10 km range so it can receive data from all fields on a farm and has a low power requirement so that small batteries can be used to power the sensors over a full year. It has been used in the urban sector but not in lowland agriculture.We will track cows to determine when they move to and from the milking parlour and to monitor their grazing activity in the fields. Group grazing behaviour will be used to determine when best to allocate extra grazing. A signal will be generated to trigger a field gate to open, allowing the herd access to fresh pasture.Over time the system will build up a database of where the cows have grazed which can be used to quantify the productivity of each field. This information will improve and support pasture management decision making such as the need to re-seed grazed pastures."

在过去的20年里，英国每头奶牛的牛奶产量增加了50%(AHDB，2018年)。虽然牧草是一种廉价、可持续、高质量的饲料，但目前的放牧系统不支持这些增加的产量，因此奶牛在夏天被喂食补充剂，甚至饲养它们，以确保更高的饲料摄入量。这些行动增加了饲料成本和泥浆处理等环境问题。我们的愿景是开发一个系统，实时收集奶牛的行为数据，并使用人工智能技术来确定何时最好地将更多的牧场分配给放牧的牛群，从而导致更高的采食量和更多的草产奶。到目前为止，这种应用草地研究一直存在市场失灵，因为该行业几乎没有老牌公司能从推广这类工作中获得经济利益。这个创新项目将使用奶牛行为数据来跟踪放牧强度，并确定何时最好自动分配额外的放牧。这将增加牧草的产奶量，并导致更多的奶牛在更多的时间被放牧，这有助于满足社会对奶牛应该在草地上放牧的愿望。安装在项圈上的小型传感器使用GPS信号跟踪奶牛，并通过加速度计数据监控它们的放牧行为。牛群中的一小部分奶牛(5%-8%)将在整个放牧季节佩戴项圈，收集的数据将通过低功率广域网络(LoRaWAN)发送到互联网。LoRaWAN系统(2015)的射程为10公里，因此它可以从农场的所有田地接收数据，并且电力需求较低，因此可以使用小电池为传感器全年供电。它被用于城市部门，但不用于低地农业。我们将跟踪奶牛，以确定它们何时进出挤奶厅，并监测它们在田野中的放牧活动。将根据群体放牧行为来确定何时分配额外放牧的最佳时机。系统将产生一个信号，触发一个牧场大门打开，允许牛群进入新鲜牧场。随着时间的推移，该系统将建立一个数据库，记录奶牛在哪里放牧，可以用来量化每个牧场的生产力。这些信息将改善和支持牧场管理决策，例如需要重新播种放牧的牧场。