How AI Can Help In Agriculture — Five Applications and Use Cases
Artificial Intelligence (AI) is expanding its footprints at the ground level making a significant impact in the world’s most vital sector — Agriculture. After healthcare, automotive, manufacturing, and finance sectors now artificial intelligence in agriculture is providing cutting-edge technology for harvesting with better productivity and crop yield.
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The Agriculture sector is the foundation of the world’s economy and with the increasing population, the world will need to produce 50% more food by 2050. AI-enabled technologies can help farmers get more from the land while using resources more sustainably. Here, we’ll learn how AI can be used in agriculture and its applications into farming.
AI Applications with Use Cases in Agriculture and Farming
With the heavy investment in developing autonomous vehicles for various needs, the agriculture sector will be also getting benefits with self-driving or you can say driverless tractors.
With more quality AI and machine learning training data for agriculture, the farm sector is going to be revolutionized by the large scale use of autonomous tractors for performing multiple tasks.
Video: Autonomous Tractor at Work
These self-driving or driverless tractors are programmed to independently detect their plowing position into the fields or decide the speed and avoid obstacles like irrigation objects, humans and animals while performing various tasks.
Similarly, AI companies are developing robots that viewing through computer vision to see and easily perform multiple tasks in the farming field. Such robotics machines are trained to control weeds and harvest the crops at a much faster pace with higher volume compare to humans.
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These robots are well-trained to assist in checking the quality of crops and detect unwanted plants or weeds with picking and packing of crops at the same time capable to fight other challenges faced by the agricultural labor force.
Companies like Blue River Technology and Harvest CROO Robotics are making such robotics machines that can control unwanted crops or weeds and help farmers in picking or packing of crops with higher volumes.
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Controlling Pest Infestations
Pests are one of the worst enemies of the farmers damaging the crops globally before it is harvested and stored for human consumption. Popular insects like locusts, grasshoppers, and other insects are eating the profits of farmers and gobbling the grains meant for humans. But now AI in farming gives growers a weapon against such bugs.
AI and data companies are helping farmers to get alert on their Smartphones about the grasshoppers likely to descend towards a particular farm or matured crop field.
AI companies using the new satellite images against pictures of the same using historical data and AI algorithm detects that the insects had landed at another location and farmers use such information after confirmation and timely remove the costly pests from their fields.
Soil and Crops Health Monitoring
Continues deforestation and degradation of soil quality are becoming a big challenge for food-producing countries. But now a German-based tech startup PEAT has developed a deep learning-based application called Plantix that can identify the potential defects and nutrient deficiencies in the soil including plant pests and diseases.
This app is working on image recognition-based technology and you can use your smartphone to capture the plant’s image and detect the defects in the plants. You will also get soil restoration techniques with tips and other solutions on short videos on this app.
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Similarly, Trace Genomics is another machine learning-based company that provides soil analysis services to farmers. Such apps help farmers to monitor the soil and crop’s health conditions and produce a healthy crop with a higher level of productivity.
SkySquirrel Technologies acquired by another similar company VineView brought drone-based aerial imaging solutions for monitoring crops health. A drone is used to make a round of capturing the data from the vineyard field and then all the data is transferred via a USB drive from the drone to a computer and analyzed by the experts.
The company uses algorithms to analyze the captured images through computer vision and provides a detailed report containing the current health of the vineyard, generally the condition of grapevine leaves as these plants are highly prone to grapevine diseases like molds and bacteria helping farmers to timely control using the pest control and other methods.
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Precision Farming with Predictive Analytics
AI applications in agriculture expanded into doing accurate and controlled farming through providing proper guidance to farmers about optimum planting, water management, crop rotation, timely harvesting, nutrient management and pest attacks.
Video: What is Precision Farming?
While using the machine learning algorithms in connection with images captured by satellites and drones, AI-enabled technologies predict weather conditions, analyze crop sustainability and evaluate farms for the presence of diseases or pests and poor plant nutrition on farms with data like temperature, precipitation, wind speed, and solar radiation.
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AI in agriculture not only helping farmers to automate their farming but also shifting to precise cultivation for higher crop yield and better quality while using less resources.
Companies involved in improving the machine learning or AI-based products or services like training data for agriculture, drone and automated machine making will get technological advancement in future will provide the more useful applications to this sector helping the world deal with food production issues for the growing population.
This article was originally submitted at www.vsinghbisen.com