The farming sector remains one of the most important among different industries. People engaged in agribusiness are working 24 hours to increase crops yield and livestock growth. Despite the fact that their life became much easier for today, they still need some technical assistance to save costs and improve productivity at the same time. This is where custom software development and artificial intelligence technologies come to the rescue. Their capabilities seem almost unlimited. And we will prove you it.
We are standing on the threshold of great discoveries. You simply cannot skip them! So hasten to read this article.
What is Mixed Reality?
Mixed Reality (MR) is a term gaining it's popularity today. It defines a combination or union of two virtual environments where two worlds coexist together. Sometimes a mixed reality is called a hybrid reality.
See how it is possible to change the farming with technologies. Read How can technology change farming?
Let's discover some mixed reality examples. It makes it possible to simultaneously investigate a virtual environment and real world as a single whole. Using real environment and coordinates virtual objects can be placed in a real world. When a user approaches a certain object, it is enlarging, when moves away - it is shrinking. Owing to a virtual reality, users can explore an object from different angles and at any distance. Besides, a mixed reality allows users to affect virtual object and interact with them as if they were in the same place.
Mixed reality in action
Mixed reality can turn your smartphone into an interactive handbook where the informational environment for places we are located in is building on. How does MR technology affect farming? 3D-mapping technology makes it possible to turn fields into the virtual environment where farmers can generate different scenarios of crop cultivation, even if they seem fantastic in real life. Special software combined with webcams in a virtual environment augment physical objects as well as integrate us into the virtual world.
Owing to unique capabilities and experience a hybrid reality has, developers start investigating different ways of efficient use of this technology in diversified areas. Present-day medicine, architecture, education, and smart farming are the most advantageous fields for the application of a hybrid reality technology.
Machine learning in agriculture
Machine learning - a complex statistics application for search of consistent patterns in data and development of required forecasts - has eased the process of a task assignment. Developers do not have any longer to build special programs for their computers to solve one task or another. Instead of this, a computer is taught to find the problem by itself, without any assistance. A real breakthrough in the world of information technologies. And, considering technical capabilities of AI, agriculture field cannot be ignored.
History of machine learning has begun in the 1950s when computer scientists managed to teach a computer to play chess. Since then, together with computing capacity, the complexity of consistent patterns and forecasts computer is capable of drafting and detecting has been growing. As well as the complexity of problems computer can resolve today, and farming problems are also included in this list. Moreover, machine learning is a subdivision of artificial intelligence (AI), so complex methods of smart intelligence are applied in ML technology.
AI pyramid - machine learning position
How does ML work in farming practices? The algorithm gets a range of training data and then uses it for requests processing. For example, you can upload in the computer a few pictures with the description like 'A flower is depicted on the image' and 'There are no flowers at this image'. If you add new images to the database after this, it will start identifying pictures with flowers on it's own.
The algorithm keeps on improving. Right and wrong results of an image recognition are sent to the database, and software is becoming smarter with every processed image. In some sense, such process can be compared to building a muscle - the more you train, the stronger you get. The more images you have downloaded in the program, the more precise result it will produce.
Find out what top agricultural apps are available. Read Smart farming: 10 most popular agricultural apps
Thus, AI and machine learning, in particular, can significantly change the agriculture and the whole smart farming field. How? The answer is waiting for you.
Automated farming: how it works
Farming is one of the most ancient human activities. Throughout history generations of people improved their skills in sowing, cultivating and harvesting crops. Such skills gave people a chance to feed themselves. Of course, agricultural tools have always been developed throughout history so today we use mechanical tools instead of their heavy manual counterparts. But computer and similar technologies always seemed to be incompatible with a farming sector. And not so long ago people even didn't imagine how to combine them. However, everything has changed and there is a strong impact of technology on agriculture nowadays.
The mission of a farming sector is to satisfy basic human needs in nutrition. Availability of agriculture has always been a critical factor in a population survival and growth. As modern cities are densely populated, people have to find new sophisticated means to harvest more crops at limited land sections. Implementation of agrochemicals, genetic manipulation and fertilizers on the one hand and information technologies and innovative farming equipment, on the other hand, will help humanity to avoid starvation. Smart farming solutions can save the world if people apply them wisely.
Furthermore, scientists need to find the way to make crops flood and drought resistant in order to grow them in regions with uncertain climatic conditions.
Besides that, it is highly required to find the way to use less water for crops. In the light of all the above, it is impossible to avoid implementation of smart technologies since they can be advantageous and helpful for the whole world population.
Technologies use cases
Today city farming is gaining it's popularity among the urban population. Dubbed vertical farming is one of the leading directions of city farming since it makes it possible to grow fruits and vegetables right indoors in the downtown of a big city. In other words, such harvest can be grown on walls and roofs of buildings. This tendency seems to be a solution to the problem of lack of nutrition. In addition, such technique allows growing crops 20% faster and use 90% less water. Thus, this method can be applied as well even in a very dry region like Eastern Africa.
Second, smart sensors come to rescue today. They can monitor all plants' vitals, send all necessary data in a real-time mode. Here where machine learning comes in. Algorithms check all information, explore it to predict what pests can attack it. Also, mixed reality applications make it possible for farmers to monitor crops condition using special helmets with virtual and augmented reality.
Crop cultivation using mixed reality device
As an example, we can take Plant.IO system. PVC pipes equipped with sensors, lights, cameras etc. are located around the perimeter of the field or greenhouse. All information is sent to the server where machine learning algorithm processes this information and analyzes the whole process. Such mixed reality technology as AR-glasses allow users to see the plant with augmented objects from any point of the world.
What is the sense in it?
It may seem fantastic but the combination of a game with agriculture can really lead to a new level of a crop management and cattle breeding control. This level will be much more convenient and comfortable for farmers. Artificial intelligence together with mixed reality provides everybody with an opportunity to monitor and manage their fields from afar. Thus, previous hard work turns into a funny game due to a merger of technology and farming. What can be better?
By the way, many other industrial areas will make use of these technologies as well.
MR and AI in farming: use of technologies in agriculture
Although some options can be unheard nowadays, there are already existing AI and MR solutions that are applied successfully in farming and simply prove the use of information technology in agriculture.
A prototype of the autonomous tractor was first presented to the public in 2012. It became the first fully autonomous tractor for agriculture. This tractor is equipped with the technology that combines radio navigation and laser gyroscope together with artificial intelligence technologies. Owing to such technologies, the tractor can make it's way on it's own if it has already gone this route with the driver beforehand. And, as specialists say, the tractor won't become a full-fledged farmer during it's first ride. It should be trained as if it were a novice farmer. That is the main mission of artificial intelligence in agriculture.
All information from the tractor is sent to the special app installed on a mobile device. This software can be modified or developed from scratch by development companies like Cleveroad.
Autonomous tractors route in the app
Equipment with computer vision
Something similar but more advanced we can see in another new farming technology - tractor with computer vision system. Tractor has live cams, GPS and computing block. Computer vision system makes it possible to detect dangerous objects with high accuracy - their sizes, and coordinates for the drafting of highly accurate maps. If farmers get a precise location of some alien objects in the field, it will be possible to remove all of them until harvesting stage begins. Otherwise, these objects can be a real threat for mechanical elements of agricultural equipment. The tractor equipped with a computer vision is expected to be available for sale in the nearest two years and related farming apps will be available for the development as well.
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AI-based smart irrigators
Commonly, irrigators are used for watering or spraying chemicals. But today it can perform much more useful functions. Irrigators with integrated machine learning technology and smart farming techniques are able to detect weeds among healthy plants and then spray these weeds with herbicides. Due to special software, irrigators take a picture of all plants and then sends it to the server where AI analyzes this information. By the way, such innovative irrigators can cover more than 5000 plants per minute. This irrigator helps farmers substantially reduce the number of chemicals used. Due to the development of information technologies, cultivating and harvesting of crops will not depend on a human assistance in future.
Satellites with AI
It seems that even space can help farmers simplify their job and make it more pleasant. A startup called Harvesting analyzes satellite data and then special software predicts corn yields. Machine learning algorithms are able to detect the general condition of crops directly from space. It may seem unnecessary, but it is worth noting that a billion of dollars are at stake. And such technology can help save money that is usually wasted due to wrong predictions.
Services for plants' diseases diagnosis
There are special apps and websites that have a few thousands of pictures containing healthy plants and plants with disease. Using this new technology in agriculture, farmers can upload images of sickly plants and AI algorithm will detect what disease is depicted. Agrarians lose much time and money because of the wrong diagnosis. And artificial intelligence will help resolve this problem once and for all. Such services can be very raw today and they still need improving. But our company can help create the app like this since we have large experience in the software development for agriculture.
Monitor your plant condition via the app
Chatbots for farmers
Probably, you know what chatbots are. These virtual assistants are residing in your smartphone and they can interact with you. It is an artificial intelligence that makes it possible for virtual assistants to communicate with users. Therefore, chatbots can become absolutely useful for farmers and high-tech farming. Farmers can ask a question and get an immediate answer or a piece of advice if needed. And we advise you to build your own chatbot that will be created especially for farmers. Thus, it will be targeted for farmers and will be skilled in agricultural issues.
Discover how to create a chatbot. Read Chatbot fever: how to build a chatbot
We think that there is no sense to repeat again that mixed reality and artificial intelligence have a great potential for use in the farming sector. Every day step by step we become closer to automated farming future where manual labor is minimized. Perspectives are simply unlimited. And our goal is to help facilitate the AI and MR technologies developments. Our specialists can make the software according to your order. Contact us and share your idea!
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Watch our video about virtual reality:
What is VR in detail?
Automation in agriculture relies on making farms more automated and efficient with the use of modern technologies.
Machine learning as a subdivision of artificial intelligence easily found its place in agriculture. How does ML work in farming practices? The algorithm gets a range of training data and then uses it for requests processing. For example, you can upload in the computer a few pictures with the description like 'A flower is depicted on the image' and 'There are no flowers at this image'. If you add new images to the database after this, it will start identifying pictures with flowers on it's own.
There are several possible examples of how technologies can help farming:
- Autonomous tractors
This tractor is equipped with the technology that combines radio navigation and laser gyroscope together with artificial intelligence technologies. Owing to such technologies, the tractor can make it's way on it's own if it has already gone this route with the driver beforehand.
- Equipment with computer vision
For example, imagine a tractor with computer vision system. Tractor has live cams, GPS and computing block. Computer vision system makes it possible to detect dangerous objects that may damage agriculture equipment.
- AI-based smart irrigators
Irrigators with integrated machine learning technology and smart farming techniques are able to detect weeds among healthy plants and then spray these weeds with herbicides.
- Services for plants' diseases diagnosis Using this new technology in agriculture, farmers can upload images of sickly plants and AI algorithm will detect what disease is depicted.
Smart sensors come to rescue today. They can monitor all plants' vitals, send all necessary data in a real-time mode. As an example, we can take Plant.IO system. PVC pipes equipped with sensors, lights, cameras etc. are located around the perimeter of the field or greenhouse. All information is sent to the server where machine learning algorithm processes this information and analyzes the whole process.
Evgeniy Altynpara is a CTO and member of the Forbes Councils’ community of tech professionals. He is an expert in software development and technological entrepreneurship and has 10+years of experience in digital transformation consulting in Healthcare, FinTech, Supply Chain and Logistics
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