Hay Aye – using artificial intelligence on the farm

The agricultural sector has undergone a significant transformation driven by the introduction of Artificial Intelligence (AI) and machine learning (ML), quite literally, into the field. New advances are not only enhancing productivity but also cultivating sustainable farming practices. In this article, we explore the growth of AI in agritech, and briefly consider the challenges which can be associated with gaining patent protection for technology in this area in the UK and Europe.

The Growth of AI in Agriculture

The increasing global population size and greater pressure on the natural environment means that food producers and farmers are under pressure to produce more food while reducing their environmental impact. AI and ML methods are transforming some agriculture areas by providing innovative solutions to these challenges. From crop growth and condition monitoring to pest control, AI is enabling farmers and others working in the agritech sector to make data-driven decisions that can increase or optimise crop, herd, and flock yields, improve the health and wellbeing of livestock, while also reducing or limiting harmful effects on the environment.

Recent Applications of AI and ML in Agritech

Crop and Soil Monitoring
AI-powered systems are transforming how farmers monitor crop health and soil conditions. Traditional methods of observation and manual testing are being replaced by drones, satellites, and sensors which collect data which are then processed by associated systems equipped with AI algorithms. These technologies provide real-time data on a variety of soil moisture, nutrient levels, and crop growth stages. For instance, the European project “SmartAgriHubs” has used AI to analyse data from various sensors, enabling precise irrigation and fertilization, managing water resources more effectively, and reducing eutrophication from over or off-target fertilising. This ensures that less fertiliser is used, and that the fertiliser which is used can be applied to achieve the greatest effect.

Pest and Disease Detection
AI is also playing a crucial role in early pest and disease detection. Machine learning algorithms can analyse images of crops to identify signs of infestation or disease, allowing for timely intervention. SmartAgriHubs also implements methods which allow for early crop disease detection. Additionally, the European Union’s Horizon 2020 funded “PestNu” project employs AI algorithms to drive robotic traps for real-time pest monitoring in open-fields and greenhouses, significantly reducing the need for chemical pesticides, which in turn limits the knock-on effects of these chemicals on the wider environment.

Livestock Health Monitoring
In livestock farming, AI is being used to monitor animal health and behaviour. CattleEye is one example where AI driven computer vision has been used to autonomously monitor the number, health status, behaviour, and activities of cattle herds. While on dairy farms, 3D cameras record cows leaving milking sheds. The video from these cameras is then analysed using AI to provide weight, posture information, body condition, and also biomechanical information to highlight any mobility issues. These analyses can quickly highlight health problems which may need professional veterinary intervention, decreasing suffering of the animal, and increasing the chances of returning the animal to full health, increasing herd yield and productivity.

Intelligent Spraying and Weeding
AI-driven machinery is revolutionising the way farmers manage weeds and apply pesticides. Intelligent sprayers and mechanical weeders equipped with computer vision can target specific areas, reducing the use of chemicals and minimising environmental impact. John Deere has developed the See & Spray Ultimate which scan the crops using up to 36 cameras which are fed into an AI algorithm to determine what is a weed and what is a crop, with the weeds being precisely targeted by the herbicide, leaving the crops untouched.

Patent protection

Patent protection is essential for ensuring that you can control who can use your invention, either by preventing others from benefiting from your crop of ideas, or by licencing others to use your technology. Applying for a patent can therefore be very lucrative whether it is to enable you to root yourself in the market and provide a platform to establish yourself as a sector leader, or by generating income from licencing to others for a fee.

Challenges

At the European Patent Office (EPO) the UK Intellectual Property Office (UKIPO), AI and ML methods are considered to be computer implemented inventions. If inventions in this area are not drafted correctly, there is a risk they may fall into excluded matter. However, implementations of AI and ML in argitech often have a technical effect, for example using a trained model to identify the probability of a group of pixels in an image being a crop plant or a weed or classifying an animal biomechanical data as outside the normal range and therefore requiring veterinary attention. If the method has a technical effect, from the point of view of the EPO and the UKIPO, they should not be excluded from patentability.

Venner Shipley have patent attorneys with extensive experience and expertise in the AI and agritech sectors and can help guide you through the process of applying for patents in this area. Please get in touch to find out more.