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Computer Vision for Sustainable Agriculture: Examples and Cases

14 Jun 2022

 

Impressive population growth promises to reach 8,5 million by 2030, posing a huge challenge for agriculture. With these numbers, by 2050 it will be necessary to produce 70 percent more food. Increasing the area is not a problem, but we will face a labor shortage.

The agricultural industry is highly dependent on human hands, because it requires constant supervision of crops and the collection of products. Farmers must systematically monitor the health and behaviour of animals in order to provide us with healthy meat and dairy products. But human capabilities are not unlimited, so losses in agriculture are often due to untimely decisions or inattention of workers. Therefore, the entire agricultural industry is beginning to switch to technologically sustainable solutions, such as AI and computer vision.  

With the help of artificial intelligence solutions, we can reduce the time farmers have to work in the fields and allow them to focus on more pressing matters. The return on investment in the development of Computer Vision models will not have to wait long - because with this technology, production occurs on a large scale and efficiently. Technology has always had its place in agriculture, especially on a grand scale. Now, it is becoming more enhanced than ever.  

UN Population Statistics

 

Computer vision is a form of AI that trains machines to interpret and understand the visual world in the same way that we humans do. By exploring the vast array of visuals available, models can be trained to anticipate the future. Naturally, this has profound implications for many industries, revealing valuable insights that can help us achieve positive change, from climate change mitigation to early disease detection.  

The possibilities of using artificial intelligence are expanding even more, and on a global scale we are beginning to notice how it affects the world order. With the help of artificial intelligence, and its branches in the form of a computer visible, we are able to achieve the goals of sustainable development.  

In this article, we will tell you about the role of computer vision in agriculture and how it helps us achieve sustainable goals.  

Table of content:  

  • CV and AI in Agriculture
  • How Computer Vision impacts Sustainable Development Goals
  • Computer Vision use cases
  • The ways it works
  • Computer Vision startups in Agriculture industry
  • Conclusion

How CV Impacts Sustainable Development Goals  

There are 17 UN Global Sustainable Development Goals, and in some of them, Computer Vision technology has a direct positive impact. 

 

UN Sustainable Development Goals
UN Sustainable Development Goals

 

Second Global Goal: Zero Hunger  

Over the past few years, we have been producing too much food and a third of produced is simply wasted while there is real hunger in other sides of the world.  

Drones with Computer Vision models are capable of monitoring and planning food production. In addition, this technology is already frequently used in the field of food safety, controlling the amount of food thrown away for better organisation of menus and ordering products.

Global Goal three: Good health and wellbeing  

There is a sharp shortage of doctors all over the world, according to statistics, more than 44% of WHO Member States have less than 1 doctor per 1000 population. The development of Computer Vision models in the healthcare industry allows research, diagnosis and prevention of diseases.  

Global Goal four: Quality education  

Unfortunately, a normal education is not available to everyone in the globe. Government often put other social factors in a higher place, and education goes by the wayside.  

In our new world that is entirely mobile, Computer Vision and Augmented Reality can help reduce learning time, make it easier to find information, and increase student interest in education. 

Computer Vision use cases in the Agriculture Industry 

Livestock farming  

An important aspect of farming is not to prevent animals from living their normal lives in order to be able to watch them in peace. The cameras collect real-time data without disturbing the animals at all. With the help of analytics, you can make decisions about further improvements and treatment. You will always have the most accurate information about your animals, without missing a single event.  

What farm can do with computer vision analytics? 

  • Targeted treatments

You can easily access the health of your livestock at any time with super accurate behavioural analytics. With Computer Vision, you optimise the process of using antibiotics, hormones and vaccines, knowing who needs to be given them and who does not. This, in turn, will protect the health of livestock from unnecessary harm from pills.  

  • Tracking the activity of animals at different stages of growth

It is important to know what stage the animal is at - fertilization, gestation or maternity, in order to monitor their activity and detect abnormal behaviour.  

 

 

Crop monitoring  

Drones have become indispensable in our lives, with their help you can see the fields from a bird's eye view, which makes it possible to analyse the health of the crop and reduce the need for labor.  

The main advantage of Computer Vision models with drones is that they have the ability to cover vast areas in a short time, as well as more efficiently than humans. Further statistics allow to gain a deep insight of the state of crops and soil.  

Many processes are done manually, most of the time spent on determining the signs of the fruit, such as ripeness, colour, size and defects. Every day, agricultural workers perform this task to ensure the quality of the crop and timely solutions, such as additional watering or antibiotics.  

 

Sustainable Pest Management  

Particularly noteworthy are Computer Vision models that detect pests, because they threaten crop fertility as much as drought. According to statistics, about 40% of the annual crop production in the world is damaged by pests. Diseases spread by pests cost the economy more than $540 billion.  

Various insects live off the leaves, extracting food from them, because of this, the process of photosynthesis is poor, the plants begin to get sick, which leads to huge crop losses.  

Pest monitoring is usually done manually by workers, but this method is extremely damaging to crops because detection occurs too late. It is difficult to notice small bugs with human eyes, but this task is easily accomplished with camera.

Using Computer Vision technology on farms will allow you to produce products with less damage, that will help to increase earnings.  

 

Species detection  

According to studies, there are about 8.7 million rare species of animals on land and sea, but only 1.2 million of them have been identified.  

Detecting species is a really challenge for researchers because they are rare! Some of them may additionally be elusive or nocturnal or be extremely difficult to spot.  

Also, the use of manual research threatens species due to contact with people and stress for animal or deliberately allow access to poachers.  

Implementation of such sustainable technology as Computer Vision eliminates all of this risks, cameras can reach the most inaccessible places, can work day and night and do not disturb animals at all.  

By Towards Data Science
By Towards Data Science

The way it works  

Video Cameras

It is not necessary to buy expensive cameras with built-in technology in order to start monitoring your animals in real time and conduct appropriate analytics. The uniqueness of Computer Vision models is that they can be installed on any low-cost CCTV camera.

The installation of models is implemented in two ways:

Server Installation

Thus, the model is installed on the server, it can be Azure, AWS or Digital Ocean. The connection is implemented through the interface provided by the model. After training and setting up the model, data is exchanged on the server, you provide video, and in return you receive ready data about the object.

Installation on the edge

This type of installation provides instant data processing, as they are processed directly in the device. Particularly useful type where you need to receive real-time data and receive notifications. Supports various types of devices - Raspberry Pi, Google Coral або NVidia Jetson.

 

Drones  

Drones have evolved from military aircraft to photography tools and now revolutionary agricultural tools. Flying robots can fly at different heights, allowing them to recognize potential seeding problems that are not visible from ground level. Leaf discoloration, plant stress, or weeds can be a factor in severe crop failure.  

More than half of households in 2016 admitted that they were looking forward to buying a drone. And this is not surprising, because the investment that is invested in the development of Computer Vision models and implementation in the drone, returns in the first years of implementation.  

Drones are getting smarter over time, they can help reduce landing costs by as much as 85% and help grow crops without human assistance. The newest drones are equipped with shooters that launch seeds or nutrients into the field.  

According to experts, the use of drones in agriculture helps to complete tasks 5 times faster than using traditional agricultural equipment.  

 

 

Farming Robots  

Ordinary autonomous machines are being replaced by advanced robots, which are implemented with Artificial Intelligence and Computer Vision models. Such a combination of physical actions and analytical mind completely replaces the routine work of a human.

By implementing algorithms for identifying and picking fruits, camera can determine which fruits are ready to be picked, and the machine in turn picks them.  

Also, this technology helps to easily detect weeds and immediately remove them using herbicides, mechanical damage, lasers or electric current. You can monitor the health status of crops and automatically spray local pesticide flow. An individually calculated amount of pesticides helps to keep part of the healthy crop.  

Another common use is to collect stones. Before planting crops, it is necessary to clear the sowing fields from stones. The manual method requires a lot of effort and time, but with the help of autonomous bots with computer vision models, this task is solved without human participation.  

Startups with Computer Vision in Agriculture industry 

Serket

A technology company that was created by farmers is perfectly aware of all the needs and needs of industry. Serket is developing a sensor less artificial intelligence that uses a video camera to improve farm performance in real time, with a particular focus on pig production.  

The main functions of video surveillance are to monitor changes in the health of pigs, reproduction and the general environment in which pigs live. Computer vision technology helps convert visual information into data that helps make further improvement decisions.  

Cattle Eye

An Irish startup that, like no one else, knows the need for robot automation, because the creator is the son of a farmer. Their main goal is to make video analytics available to every farmer, because any cheap camera can be used to install a computer vision model, and all data is processed in the cloud. This startup specializes in cows, artificial intelligence is able to identify cows, giving each of them a special ID, and then monitors their behaviour and health, collecting all the information into analytics.  

Onecup  

Agriculture startup that has patented its 360 visual live id platform specially designed for the farm, which effectively recognizes the faces of animals and is able to move around the entire field. The main advantage of this technology is that it can recognize a large number of animals at a very long distance and accurately track the activity of each of them - health, activity, nutrition.  

Conclusion     

There is not a single industry that has not been touched by Artificial Intelligence. And as we learned from this article, the use of these sustainable technologies helps our ecology and society achieve their goals.  

We at ByteAnt have been developing Computer Vision models for the past few years and have experience with such a fast-growing industry as agriculture.

Contact us to discuss your ideas for developing Сomputer Vision models individually for your case and start automating your business to achieve goals and reduce costs. And also you can take a look at our ready models on our landing page. 

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