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

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。今天，化肥生产消耗了大约1.2%的世界能源，不包括运输、储存和施用化肥的能源成本。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%）。过量的氮也会导致作物健康状况不佳并引发疾病。这反过来又导致对杀虫剂和杀真菌剂的需求。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。基于现场测量的精确施肥大大减少了肥料的施用量，减少了制造、分配、储存和施用肥料所需的能源，并进一步提高了作物产量和健康状况，同时减少碳排放和环境污染-为英国的净零目标做出贡献。需要一种农民可以用来准确测量土壤氮的成本效益工具。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权，以实现投资回报和廉价运营。此外，机器人需要完全电动，可以选择从太阳能或其他可再生能源现场充电。我们已经测试了机器人的测绘能力，并在草原上演示了功能。目前，机器人，自主仪器已经完成，自主软件已经在某些环境中进行了测试，但需要进一步调整一些作物。该项目的重点是测绘相机和土壤传感器以及创建准确的氮地图和原位校准传感器所需的AI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。特别是咖啡，需要优化施肥，使生产可持续发展。自动化和人工智能的道德考虑是所有权。我们认为，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全部所有权。让自主设备变得负担得起是我们的社会责任。

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.