| Issue |
E3S Web of Conf.
Volume 458, 2023
International Scientific Conference Energy Management of Municipal Facilities and Environmental Technologies (EMMFT-2023)
|
|
|---|---|---|
| Article Number | 09024 | |
| Number of page(s) | 7 | |
| Section | IT and Mathematical Modeling in Energy Systems | |
| DOI | https://doi.org/10.1051/e3sconf/202345809024 | |
| Published online | 07 December 2023 | |
The use of artificial intelligence algorithms to monitor the technical condition of energy-intensive tractors
1 Federal Scientific Agro-Engineering Center VIM, 1 Institutsky proezd, 5, Moscow, 109428, Russia
2 Kaliningrad Research Institute of Agriculture, All-Russian Research Institute of Phypatothology, 5 Institute Str., 143050, Bolshie Vyazemy, Odintsovsky district, Moscow region, Russia
3 Russian State Agrarian University – Moscow Timiryazev Agricultural Academy, Timiryazevskaya str., 49, 127434, Moscow, Russia
* Corresponding author: redizdat@mail.ru
The development of new software that uses artificial intelligence in its work is being carried out all over the world. Also in parallel with the programs new computing devices are being developed that allow storing and processing large amounts of data. It allows us to create complex computer systems that involve many third-party devices. This article is devoted to the growing role of artificial intelligence in agriculture, namely in diagnosing the condition of agricultural machinery. Modern devices for diagnosing the condition of the tractor fleet allow us to accumulate a large amount of information. Also on many modern tractors the manufacturer already provides a built-in on-board system based on a CAN interface, which serves to control the operation of the equipment. It allows us to accumulate huge data banks. But the question now arises about processing all this information. This article describes methods for structuring large amounts of such information and most importantly analyzing them using artificial intelligence algorithms.
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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