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The Future of Farming Automation with Use of AI

Agriculture has always been a field that requires a lot of hard work and human supervision to complete even the smallest of tasks. It also requires a skilled human eye to recognize ripe crops to pick them, diseases to treat them, and insects to prevent harm. So, it’s fair to say that a lot of work is needed to grow food, and this necessity will increase given the population rise. In 2021, the global consumption of food reached 2.5 billion metric tons, which is expected to be 3 million metric tons by 2027. And this is where agriculture technology comes in. 

Why and How Is Technology Used in Agriculture?

Why?

To feed the constantly growing population, food production must increase by a whopping 70%. The amount of arable land is limited, and the water levels are receding, which causes the Green Revolution problem all over again. How do we get to a significant increase in food production? The only way it can be achieved is through the help of new technology in agriculture like Artificial Intelligence (AI), drones, Internet of Things (IoT), and other data-driven means. 

How?

The data-driven farming gives farmers the ability to map every farm and overlay it with lots of data to analyze and use appropriately. Soil nutrient level, soil moisture level, the readiness of your cucumbers – everything can be detected by drones and displayed on the screen in detail. 

There are the following farming automation techniques farmers use: 

  • Precision agriculture: apply nutrition only where and when it is needed. 
  • Precision livestock farming: monitor animals to improve their production. 
  • Phenotyping: understand why the same seed grows differently in different soil parts. 
  • GIS-based agriculture: pick the right piece of land to grow harvest. 
  • Satellite crop monitoring: get satellite images of fields to see crop dynamics. 
  • Innovative robots and machinery: increase automation and save human resources.

To understand how to increase the productivity of the agriculture sector with AI specifically, let’s look at how AI agriculture innovations are being incorporated into farming. 

To discover agriculture software examples that optimize farm work, go to our previous article

In-Field Monitoring with Computer Vision

AI agriculture technology can be used to monitor the health and progress of crops in the field: 

  1. Pests are a major issue in agriculture as one of the main sources of crop reduction, causing damaged crops in food production. With the use of computer vision drones, farmers can identify harmful pests. Once they are detected, the drone sprays the crop with pesticides. 
  1. Using AI agriculture technology in computer vision, farmers will also get notifications as soon as the disease is spotted. Earlier the disease is detected greater the chance of healing due to no spread on other crops, which ensures better quality control. 
  1. Computer vision is also used to check crop readiness and livestock. The last can be monitored 24/7 for sicknesses to take action immediately when detected.  
  1. Computer vision can be applied to the problem of soil diagnosis. For example, PEAT startup has developed an algorithm to identify soil strength and wellness. The goal is to reduce the chances of growing underdeveloped crops while optimizing the potential for healthy crop production.  

Thus, AI advanced technology in agriculture provides farmers with on-time insights to improve field conditions, save crops, and increase the overall harvest amount and quality.  

Predictive Analytics

The current state of agriculture involves a lot of guesswork, with farmers applying water and pesticides uniformly to crops. The issue with this is there may be some plants in need of additional pesticides, or water other plants will not benefit from. It causes massive waste in both water and pesticides. 

However, with the help of data-driven agriculture technology, farmers can: 

  • utilize precision farming that detects and identifies crops in need of water or pesticides; 
  • provide required nutrition only to plants that really need it; 
  • reduce cost and wastage of water and pesticides. 

With the use of big data, we are able to use it as actionable insights helping farmers make decisions to improve sustainability, strengthen efficiency, reduce costs, and increase profitability. New technology in agriculture helps collect data from soil sensors, GPS-equipped tractors, and other external sources such as local weather data. Such an approach allows farmers to increase productivity while decreasing manpower drastically. 

Autonomous Robots

One of the major applications of AI advanced technology in agriculture is autonomous robots. They help increase productivity while allowing farmers to focus on more important aspects that humans must control. For example, due to their accuracy and speed, harvesting and picking are one of agriculture’s most popular robotic applications. Thus, robots can improve the size of yields and reduce waste from crops being left on the land.  

With the use of autonomous robots combined with computer vision, the machine will be able to identify the ripeness of crops and pick based on a few merits such as readiness, disease-free, and more criteria. 

Conclusion

It is fair to say that the application of AI’s new technology in agriculture has come a long way since it is vital to feed the world’s growing population. Thus, farming innovations make this field more productive, safe, and environmentally friendly. However, there are a lot of intriguing ideas and concepts that take agriculture to the next level beyond AI.  

It is always better to get an expert view of your farming business and see which one of the agriculture technologies can improve your fields. Contact us for a free consultation and have your tomatoes revolutionized!

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