Application of Artificial Intelligence (AI) in Agriculture

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A large number of processes in the agriculture industry are now being automated. AI in agriculture make the work of farmers more cost-effective. This comes at the cost of reduced spending on consumables and increased yields. A huge number of systems are now helping the farmer to make decisions about what to do on the farm: weather stations, moisture sensors, satellites that provide images of the area, etc. Every day there are developments in this area and the number of new devices is growing. If in 2014 190,000 measurements were taken daily in the most modern farms, by 2050 this number, according to researchers, will grow to 4.1 million. On their own, it will be impossible for a person with such an amount of information. It’s useful to hire ai developers. Systems capable of self-learning are emerging that are used to analyze, process and summarize data from monitoring devices.

 Artificial intelligence in the monitoring of fields

The American company IBM released a platform called Watson Decision Platform for Agriculture, which processes information obtained by remote sensing of the land. A farmer can be provided with data on corn crop infestations by diseases or pests. The Watson Platform, like Taranis, is able to offer the farmer solutions to the problem. It will calculate the necessary amount of pesticides, optimal timing of treatment of problematic areas, assess the state of plants and propose preventive measures. The system is able to collect data on moisture, terrain and meteorological situation to provide a graph of soil moisture changes, yield forecast and its dynamics based on data from previous seasons.

There are a number of other platforms in the world, which are able to analyze information and provide recommendations for farming:

  • Farmers Edge’s Health Change Maps and Notifications platform;
  • Bayer’s Field Manager application;
  • Hummingbird Technologies platform.

All these platforms use data from satellites, ground monitoring, meteorological information and with the help of patented algorithms analyze them.

 Artificial Intelligence and Plant Treatment

Various herbicides and chemicals are now ubiquitous in agriculture. The use of these substances is generally accepted even at the legislative level, but this does not negate their harmfulness with the benefits they bring. By reducing the amount of pesticides used, it is possible to reduce the financial costs and improve the condition of the land with a further increase in yields. Trimble has developed the WeedSeeker spot weed spraying system to do just that. Weed identification is accomplished through LED sensors that scan the terrain in the red and infrared ranges:

– The light reflected from the weed is instantly analyzed, 

– A command is given to the nozzle,

– The active ingredient is released. 

The herbicide injection allows treatment of plants even in strong winds, and the time of nozzle activation depends on the set speed of movement. The system saves up to 80% of the active ingredient in areas with intermittent weed occurrence.

Other developments using artificial intelligence

Uptake is developing devices that will be installed on machinery and will analyze its work and offer options to optimize the work process. In America, spot irrigation systems are being developed. The project aims to reduce the amount of wasted water by precisely irrigating plants in places where it is required. In general:

  •  The demand for agricultural products is only increasing every year.
  •  At the same time human labor from the economic point of view is not profitable for this industry. 
  •  Therefore, the future will see an increase in the development of various robotic systems and artificial intelligence systems.


About author
Breanna, with the help and support of BeDoper's audience, provides fresh news on the tech and EdTech daily to your screen. Stay connected with Breanna on FB, Twitter, and Pinterest to spice up your feeds and productivate your time.
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