The global artificial intelligence (AI) market in agriculture is expected to register a compound annual growth rate (CAGR) of over 21.52 percent, during the forecast period of 2019-2024, a study conducted by Research and Markets has revealed.
Driverless tractor is trending in market as these tractors can steer automatically using GPS-based technology, lift tools from the ground, recognise the boundaries of a farm, and can be operated remotely using a tablet. A fleet of smaller automated tractors could lift farmer revenue by more than 10 percent and can reduce farm labour costs.
Maximise crop yield using machine learning technique is driving the market. Species selection is a tedious process of searching for specific genes that determine the effectiveness of water and nutrients use, adaptation to climate change, disease resistance, as well as nutrients content or a better taste. Machine learning, in particular, deep learning algorithms, take decades of field data to analyse crops performance in various climates and based on this data one can build a probability model that would predict which genes will most likely contribute a beneficial trait to a plant.
Increase in the adoption of cattle face recognition technology is driving the market. Through the application of advanced metrics, including cattle facial recognition programmes and image classification incorporated with body condition score and feeding patterns, dairy farms are now being able to individually monitor all behavioural aspects in a group of cattle.
Increased use of Unmanned Aerial Vehicles (UAVs) across agricultural farms is driving the market as the use of drones in the agriculture industry can be used in crop field scanning with compact multispectral imaging sensors, GPS map creation through onboard cameras, heavy payload transportation, and livestock monitoring with thermal-imaging camera-equipped drones, which increases the demand of UAVs, the study has anticipated.
However, lack of standardisation is restraining the market growth as lack of standards in data collection, and lack of data sharing is high, and machine learning and artificial intelligence and advanced algorithm design have moved so fast, but the collection of well-tagged, meaningful agricultural data is way behind.
Agricultural drones to drive the growth
According to the study, as global population projected to reach over 9 billion by 2050, agricultural consumption is expected to increase by a massive 70 percent, where drones have now been mainstreamed for smart farming assisting farmers in a range of tasks from analysis and planning to the actual planting of crops, and the subsequent monitoring of fields to ascertain health and growth.
Drones equipped with hyperspectral, multispectral, or thermal sensors are able to identify areas that require changes in irrigation. Once crops have started growing, these sensors are able to calculate their vegetation index, and indicator of health through AI, by measuring the crop's heat signature.
No one likes the idea of chemical spraying, but, for the time being, it's a necessary part of large-scale agriculture. Fortunately, smart farming drones are helping reduce its environmental impact. Specialised UAVs are equipped with sprayers, with various kinds of technology, like ultrasonic echoing devices and lasers, which can measure distance with extreme precision. The result is a massive reduction in overall spray and a much lower chemical level reaching the groundwater.
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