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更高产量的作物，养活世界上一半的人口。今天，除运输、储存和施用化肥的能源成本外，化肥生产消耗了全球约1.2%的能源。没有有效的方法来测量导致化肥过度使用的土壤氮（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引发疾病。这反过来又导致了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。基于现场测量的精确精确施肥大大减少了肥料的使用量，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，同时减少了碳排放和环境污染-为英国的净零目标做出了贡献。农民需要一种经济有效的工具来精确测量土壤氮。提出的解决方案是一个可以在现场测量土壤质量的自主机器人。低资本成本和完全的自主权要求允许投资回报和低成本运营。此外，机器人需要完全电动，并可选择从太阳能或其他可再生能源中充电。我们已经测试了机器人的绘图能力，并展示了在草原上的功能。目前，机器人的自主仪表已经完成，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。该项目重点关注测绘相机和土壤传感器，以及创建精确的氮地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。该项目特别针对东南亚的高价值作物出口市场，如咖啡、桑葚（蚕丝）、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量是所有权。我们认为，这些工具需要足够实惠，以便最终用户能够投资并获得设备的完全所有权。让人们负担得起自动设备是我们的社会责任。

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.