With the global demand for food expected to double in the next 50 years, the farming industry is increasingly turning to artificial intelligence to help solve its issues.
With automated farming, farmers can plant crops, spread nutrients, and harvest plants without needing humans to drive tractors. Computer vision-powered equipment is changing the sector, freeing up valuable resources and paving the way for farmers to meet the increasing food supply demand.
In this article, we’ll look at:
- Soil moisture monitoring
- Aerial survey and imaging
- Grading and sorting
- Farm and crop diagnostics
- Autonomous tractors
- Autonomous plows
- Autonomous planting and harvesting
- Indoor farming
1. Soil monitoring
Crop health, quantity, and quality of yield rely heavily on micro and macronutrients. Knowing how crop growth is affected by the environment is vital for production efficiency. Traditional soil monitoring techniques, however, are extremely inaccurate and time-consuming – after all, farmers can’t inspect every single plant in person.
Drones can easily capture aerial image data, with computer vision models being trained to use the information to intelligently monitor crop and soil conditions. By targeting specific issues, AI gives farmers the tools to immediately take action when a problem occurs.
2. Aerial survey and imaging
Computer vision is also a great solution for surveying land, helping farmers keep an eye on both crops and livestock. By analyzing imagery from satellites and drones, AI can alert farmers when something is wrong – without them having to constantly observe their fields.
And that’s not all – aerial imaging can also increase the accuracy of pesticide spraying, which saves on costs and protects the environment.
3. Grading and sorting
Similarly to keeping an eye on crops as they grow to spot defects, pests, and diseases, computer vision is a great asset for sorting the good produce from the bad, and the ugly. It can inspect fruits and vegetables for their size, color, shape, and volume, automatically separating and grading them extremely accurately.
This helps to free up employees and minimize errors, as it makes quality control cheaper and less time-consuming.
Soumya Pisupati
4. Farm and crop diagnostics
Technology companies collect large amounts of data from farms, which can sometimes be from smartphones, drones, and sensors. Several startups are developing AI-based hybrid solutions to collect and manage this type of data.
Cromai, a Brazilian startup, has AI-based solutions that offer farmers diagnostic data about their land and crops. Computer vision helps to capture the shape, color, and texture of crops so they can be further analyzed.
5. Autonomous tractors
Just like self-driving vehicles, autonomous tractors use computer vision and a network of cameras to offer a 360-degree view of the surrounding environment, from crops to people, and more.
When fully automated, they can work around the clock, which simplifies staffing issues and helps to keep employees out of harm’s way. Computer vision for tractors can also map and tag crops, so farmers can understand changes in plants over time and track trends to increase crop yield.
Computer vision-enabled plows and tillers are typically attached to a trailer, automating the process of breaking down the soil and getting it ready for seeds. The plows can also identify everything they come across, avoiding debris, other machinery, and people.
Companies like John Deere, Frontier, and Caterpillar are responsible for the upward trend in autonomous tractor adoption.
6. Autonomous planting and harvesting
Autonomous planters are often attached to tractors to sow seeds. The planters use computer vision to map the soil in detail, and automatically identify the right distances between seeds while tagging their locations.
Eastern Peak and Flash Forrest, for example, use computer vision-enabled drones to plant as many as 20,000 seed pods every day, to help replenish forests that were destroyed by fires.
Tortuga AgTech uses computer vision to automate crop harvesting. This technology identifies and separates plants ready for harvest, reducing costs and increasing harvesting efficiency.
7. Indoor farming
Vertical farming is addressing traditional farming demands of land, water, machinery, and more by growing crops vertically indoors. This maximizes both space and yield, using computer vision to monitor lifecycles through a network of cameras and sensors.
Bowery Farming is a company using autonomous tech for vertical farming, collecting billions of data points to know which plants need more light and letting farmers know when to harvest them.
