A large number of processes in the agricultural industry are currently being automated. Artificial intelligence helps farmers make their jobs more cost-effective. It does this by reducing expenditure on consumables and increasing yields. A huge number of systems are now helping the farmer to make a decision on performing any work on the farm: meteorological stations, sensors, satellites providing images of the terrain, etc. New developments in this area appear every day. If in 2014, 190,000 measurements were taken every day in the most modern economy, then by 2050, according to researchers, this number will grow to 4.1 million. Independently, a person with such a volume of information will be impossible. Self-learning systems used to analyze, process, and summarize data from monitoring devices appear. Data science services company helps in this sphere. This company makes artificial intelligence evident by helping businesses to discover what they can do with AI.
Artificial intelligence in-field monitoring
The Taranis system shows good results in-field monitoring. It is an Israeli production system that is capable of collecting plant data, identifying various impacts, and evaluating to eliminate them. In the course of analyzing the situation, information obtained from observation sensors, meteorological data, and high-resolution aerial photographs is used. Taranis can identify sectors of the field with slow plant growth, identify affected insects, nutrient deficiencies, and diseased plants. Taranis proposed options for a way out of this situation, and also calculate the optimal time frame.
The American company IBM has released a platform called Watson Decision Platform for Agriculture, which processes information obtained from remote sensing of the earth. Farmers can be provided with data on disease or pest infestation of corn crops. Watson Platform, like Taranis, is a way to offer the farmer ways to solve a problem. The required amount of pesticides will be calculated, the optimal processing time for problem areas, the condition of the plants will be assessed and preventive measures will be proposed. The system is able to collect data based on data from previous seasons, provide a graph of changes in the schedule, a forecast for yield and its dynamics based on data from previous seasons.
There are a number of other models that can be used to analyze information and recommendations for housekeeping:
- Health Change Maps and Notifications platform from Farmers Edge;
- Field Manager from Bayer
- Hummingbird Technologies platform.
All these platforms use satellite, ground-based monitoring data, meteorological information and analyze them using patented algorithms.
Innovative Weed Control Projects
If we talk about ai in agriculture, work continues around the world to improve pest control systems. A new garden spraying device has been tested in India. The system was installed on a tractor and, using ultrasonic sensors, the dimensions of the tree and the distance to it were determined. After analyzing the data, a jet of the required power and with the required amount of active substance was formed. The experiment showed that in this way it is possible to save up to 26% of the herbicide.
German companies Bayer and Bosh are working on Smart Spraying technology. The system will distinguish a weed from an agricultural crop, determine its type, and, taking into account the data entered into the program, inject the required amount of herbicide. EcoRobotix is working on a device that can independently move around the field, find and treat weeds. The company expects that the use of the device will reduce the amount of herbicide applied by 20 times.
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