From Field Monitoring to Harvesting: AI Application in Agriculture From Field Monitoring to Harvesting: AI Application in Agriculture

AI-enabled systems are able to optimize a variety of processes in the agricultural sector. Such technologies will allow farmers to analyze the soil and crop state, cultivate lands with fertilizers and pesticides, and gather the harvest. The article reveals how AI solutions are used in the agricultural sector.

Field Monitoring

Rural laborers have to monitor their fields regularly to detect various vegetation issues. Today, this task can be entrusted to artificial intelligence systems that collect and analyze data bulks and provide information about the current condition of lands.

Israel-based Taranis startup has developed a platform for taking images using drones and planes. The AI system analyzes images and determines problem areas there. It defines plant diseases and pests as well as figures out whether seeds have enough nutrients.

Innovation Agro Technologies offers such a technology in Ukraine.

Another territory examination solution is IBM’s Watson Decision Platform for Agriculture. The platform processes information of Earth's remote sensing and provides farmers with data on corn area parasitic attack and diseases. The computer assesses the plant condition, identifies the best possible terms for cultivating affected areas with pesticides, and assists inpreventive measures.

Weed Killing

Weeds despoil cultivated plants of nutrients, shade them from the sun, spread diseases, and cause pest proliferation. According to various data, farm workers annually lose 10-50% of their crop because of them. Due to artificial intelligence technologies, farmers can identify weeds and destroy them pointwise.

Trimble has designed the WeedSeeker autonomous system for spraying undesirable plants with pesticides. It recognizes them using LEDs and sends a corresponding signal to the mechanical chemical sprayer. The pulverizer activates right over the weed. With pesticides being diffused dotted rather than everywhere,peasant laborers spend less costs on harvest protection activities.

Blue River has designed a robotic device called See & Spray. Using computer vision, it monitors and removes weeds as well as analyzes their immunity to herbicides. Developers assert that this system allows to reduce the amount of chemical agents and cut expenses by 90%.

Disease diagnostics

Detection of plant diseases and adoption of treatment measures prevent crop losses and decrease potential damage. Now, farmers should just have a smartphone equipped with special software for these purposes.

Peat has created the Plantix app. It contains a large library of plant images. The solution allows farmers to diagnose over 60 illnesses occurring among vegetable world representatives.

Bayer’s Scouting app processes images and recognizes 17 diseases. Besides, the software identifies weeds and determines the nitrogen level of cultivated plants. It informs users of dangerous illnesses or pests near the land lot.

AI Conference Kyiv: From Field Monitoring to Harvesting: AI Application in Agriculture 1

Robotic Devicesin Agriculture

Nowadays, various companies are developing robotic equipment for numerous tasks: cultivation of agricultural lands, irrigation, fertilizer diffusion, weed control, harvesting, etc. Such means of transport do not get tired, can operate at any time of day or night, and can cultivate more areas than people and conventional machines do.

The University of Sydney has developed an unmanned agricultural robot – Ladybird. Its obligations: monitoring of field condition, creation of technological maps, control over pests and plant growth. Due to the automated manipulator, the machine gathers the harvest and uses herbicides, knives, microwave radiation, and laser beams to combat weeds.

Agrobot has designed a robotic harvester, SW6010, for growing and harvesting strawberry. Color sensors allow it to recognize and pick ripe berries, leaving green harvest to ripen. The device sorts and packs strawberry.

CROO Robotics has introduced a robot harvesting and allocating the crop. One unit of such equipment replaces 30 people and cultivate up to 8 hectares of land.

Ukrainian Experience

According to BusinessViews, Ukraine is ranked first worldwide in terms of production and export of sunflower oil and sunflower cultivation; third in cereals export; and second in export of nuts, corn, and rape plant. Farmers succeed in this sector because of artificial intelligence technologies. Besides, various Ukrainian startups develop AI systems for the agricultural industry.

The Field monitoring service is a brainchild of the Ukrainian development team. It detects plant diseases on photos, providing users with growth stage data and treatment tips.

Agri Eye agricultural startup is developing unmanned aerial vehicles with multi-spectrum cameras. They shoot agricultural lands and assess crop conditions.

Kray Technologies has produced a quadcopter designed for spraying fertilizers and pesticides. It is equipped with the computer vision system allowing to recognize barriers on its way and avoid them. The flying vehicle cultivates up to 486 hectares.

Petiole is another Ukrainian agricultural startup. It has invented a system for immediate measurement of leaf area using a smartphone. Based on these data, the program monitors the plant growth dynamics and helps to realize how leaves respond to weather conditions, fertilizers, and other factors.

Earth Observing System is developing an AI platform, EOS Crop Monitoring Tool, to collect and systematize information about agricultural lands using satellites 24 hours a day, 7 days a week. The service will allow to control any changes in the land territory as well as to monitor seedlings and their maturity.

Conclusion

As of today, artificial intelligence is an efficient tool for the agriculture development. Automating such processes as field monitoring, harvesting, pest control, and weed killing, farmers can faster accomplish given objectives, optimizing their expenditures and increasing revenues.

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