With the arrival of 5G, the AI ??deep learning industry is developing faster and faster. In the future, many repetitive tasks will be replaced by robots. The editor of Wugu.com believes that in today's market-oriented and efficiency-first world, as long as the cost is low enough and the conditions are suitable, many occupations will be replaced by robots overnight.
As an industry with a large amount of repetitive labor, large-scale agriculture is most suitable for automated robots to show off their skills. The combination of AI and robots will lead to more and more application scenarios for agricultural robots. As long as the cost of agricultural robots is low enough and the efficiency is higher, this day will come soon. Perhaps in a few years, we will find that in the vast countryside, there are no farmers, and there are intelligent robots everywhere farming, weeding, and harvesting.
Through data analysis, the editor of Wugu.com has found various AI agricultural robots that have been used on a large scale. These agricultural robots will form a package of AI solutions for agricultural production, sowing, irrigation, and weeding.
◆◆Unmanned Tractor
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In large-scale agriculture, tractors have many application scenarios, but the driving requirements for tractors are not high. Compared with unmanned vehicles, because human lives are at stake and the testing requirements are extremely high, unmanned tractors do not require such high testing requirements. The unmanned tractor can use GPS navigation to measure the boundaries of the land, use programming to determine the path, and combine it with the very mature image recognition technology in AI, so the unmanned tractor can drive into the farmland.
Europe’s CNH Industrial Company has launched a driverless tractor that can cultivate and harvest tirelessly around the clock. The tractor is remotely monitored by the farmer and has different program settings for different production tasks.
◆◆Unmanned sowing
In agricultural production, sowing requirements are very high. It is difficult for ordinary seeders to meet the precise sowing requirements, and manual sowing is time-consuming and laborious. The foreign company John Deere has developed an unmanned seeder that uses big data to calculate the depth and spacing required for sowing based on soil nutrients and other conditions, and then conducts unmanned sowing in a targeted manner to ensure a high yield.
◆◆AI Irrigation
Drip irrigation technology is very developed and has become popular, but it requires farmers to check the drip irrigation equipment and manually control various instruments. Vinduino currently launches a package of AI solutions that can collect dripper data on site, analyze it, and make precise irrigation decisions, which can be executed automatically without manual operation.
◆◆AI weeding
Weeding and insect removal are very tedious labor. Currently, Germany’s Deepfield Labs laboratory has developed a set of equipment that can automatically weed and remove insects based on the navigation system. Pest Control uses visual recognition technology in AI to automatically identify crops, weeds, and pests. It is not only efficient, but also more accurate in pulling out weeds and pests than manual weeding and pest control without damaging crops.
◆◆Fine Picking
Traditional picking machines work roughly and often destroy crops. Some fruits and vegetables with ultra-thin skins can only be picked by hand, which does not take advantage of the cost control of agricultural production. , and the robot combined with advanced algorithms can carry out precise picking according to the location, shape and maturity of fruits and vegetables without damaging the fruits and vegetables and at an extremely fast speed.
The farmers of the future will be held by scientists who understand agricultural technology and programming. They are mainly responsible for maintaining the normal operation of AI agricultural robots and designing more accurate and efficient agricultural solutions based on climate and soil conditions. And those Farmers with rich agricultural production experience will provide experience for these solutions to ensure that AI agriculture is more intelligent.