AI driven affordable zero emission robot for soil health and fertiliser optimisation and carbon negative agriculture

人工智能驱动的经济型零排放机器人，用于土壤健康、肥料优化和碳负农业

• 批准号: 10043170
• 金额: $ 6.34万
• 依托单位: AUTODISCOVERY LTD.
• 依托单位国家: 英国
• 项目类别: Grant for R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10043170
• 关键词: AI; driven; affordable; zero; emission

Nitrogen fertilizer enables us to grow crops with higher yields supporting half of the World's population. Today, fertiliser production consumes approximately 1.2% of the world's energy excluding energy cost of transportation, storage and application of the fertilizer. There is no efficient way to measure soil N leading to fertilizer overuse (sometimes by 200-300% of what is required). Excess nitrogen can also lead to poor crop health and promotes diseases. This in turn leads to the need for pesticides and fungicides. In addition, excess nitrogen can cause crops to lodge before harvest, leading to lower yields and quality.Accurate precision fertilisation based on in-situ measurement drastically reduces the amount of fertiliser that is applied, reducing energy required to manufacture, distribute, store and apply fertilizer and additionally improve, crop yields and health, whilst reducing carbon emissions and environmental pollution - contributing to the UK's net zero targets.A cost efficient tool that farmers can use to accurately measure soil nitrogen is needed. The solution proposed is an autonomous robot that can measure soil quality in-situ. Low capital cost and full autonomy is required to allow for return on investment and cheap operation. Additionally the robot needs to be fully electric with option of re-charging from solar or other renewable power in-field. We have tested mapping capability of the robot and demonstrated functionality in grassland.Currently the robot, autonomy instrumentation is already finalised and the autonomy software has been tested in certain environment but requires further adjustment for some crops. This project focuses on the mapping camera and soil sensor and the AI models required to create accurate Nitrogen maps and calibrate the sensors in-situ. The AI models will be created in collaboration with Manchester Metropolitan University (MMU).The project specifically targets the export market looking at high value crops in South East Asia such as Coffee, Mulberry (silk), tea and cotton. Coffee in particular requires optimisation of fertilisation to make production sustainable.The ethical consideration of automation and AI is ownership. We believe these tools need to be affordable enough so that end-users can invest and get full ownership of the equipment. It is our social responsible to make autonomous equipment affordable.

氮肥使我们能够种植产量更高的作物，养活世界一半的人口。如今，化肥生产消耗的能源约占世界能源的 1.2%，不包括化肥运输、储存和施用的能源成本。没有有效的方法来测量土壤氮，导致肥料过度使用（有时是所需量的 200-300%）。过量的氮还会导致作物健康状况不佳并促进疾病。这反过来又导致对杀虫剂和杀菌剂的需求。此外，过量的氮会导致作物在收获前倒伏，导致产量和质量下降。基于原位测量的精确施肥大大减少了肥料的施用量，从而减少了制造、分配、储存和施用所需的能源化肥并进一步提高作物产量和健康，同时减少碳排放和环境污染，为英国的净零排放目标做出贡献。农民需要一种能够准确测量土壤氮的经济高效的工具。所提出的解决方案是一种可以现场测量土壤质量的自主机器人。需要低资本成本和完全自主才能获得投资回报和廉价运营。此外，机器人需要是全电动的，并且可以选择通过太阳能或其他可再生能源进行现场充电。我们测试了机器人的测绘能力，并在草地上演示了功能。目前机器人、自主仪器已经定型，自主软件已经在一定的环境下进行了测试，但需要针对某些作物进行进一步调整。该项目重点关注测绘相机和土壤传感器以及创建准确的氮图和现场校准传感器所需的人工智能模型。人工智能模型将与曼彻斯特城市大学 (MMU) 合作创建。该项目专门针对东南亚高价值作物的出口市场，如咖啡、桑葚（丝绸）、茶叶和棉花。咖啡尤其需要优化施肥以使生产可持续。自动化和人工智能的伦理考虑是所有权。我们相信这些工具需要足够实惠，以便最终用户可以投资并获得设备的完全所有权。让自主设备价格实惠是我们的社会责任。