Farming is one of the most conservative industries around and also the one where a lot of physical labour is still needed. However, if you think that agriculture and innovations are incompatible, you are mistaken. Cutting-edge technologies, such as Artificial Intelligence, Machine Learning, and Mixed Reality have a huge potential in this industry. Let’s have a closer look at how they work for farmers.
Mixed Reality Overview
Mixed reality, also known as hybrid reality, is a unique technology, which allows combining the real (physical) reality with virtual reality. In other words, it allows placing virtual objects into the real world and look at them as if they were real. For example, these virtual objects change their size and shape when you approach them or look from another perspective; i.e. they behave exactly like real physical things.
How is it applicable to agriculture? Well, it helps investigate various scenarios of crop cultivation in real fields. This is done with the help of 3D-mapping technology. Such an approach lets compare several possible scenarios and their efficiency.
Machine Learning Overview
Machine Learning is a general term that is used to describe a breakthrough technology based on the capacity of artificial intelligence to self-learning. Machine learning vs AI is what many people are often confused about. Thus, an ML-based app remembers consistently repeating patterns and uses them to analyse future situations and make precise predictions or give recommendations. Moreover, with every new situation, the accuracy of these recommendations increases. In the following sections, we’ll see how ML can be used in agribusiness.
Why Automate the Farming Sector
Farming is among the most ancient sectors of human activity and the one that has changed very little over the centuries. At the same, it is one of the most important sectors, as it provides people with food. Nowadays, few people want to be engaged in farming because the share of hard manual labour is still high there. Needless to say, the need for modernisation in agriculture became imminent. Here are some more reasons for this phenomenon.
- The growth of the Earth population. The share of the urban population is consistently growing. The agricultural sector must be effective enough to provide all these people with nutrition. In other words, it is necessary to get more crops on fewer lands. To some extent, it is reached through the use of fertilisers and chemicals. However, smart farming technologies can bring agriculture to a new level.
- City and vertical farming development. The idea of growing vegetables and fruits on the roofs and walls of the houses is very attractive for the residents of big cities, especially in the countries with unfavourable conditions for farming (frequent floods or draughts). Also, to some extent, it helps resolve the food problem in these regions. The combination of smart sensors and ML/AI algorithms lets enhance the efficiency of these artificial gardens.
Thus, by using smart technologies, one can add the elements of a game to farming. It’s hard to believe that AR-helmets and glasses, which had previously been associated with entertainment only, can serve as purely utilitarian tools for boosting the efficiency of agriculture.
Use Cases of Smart Technologies in Farming
It may sound surprising but MR and AI are already used in agriculture. Some use cases can seem absolutely unbelievable, but they do exist.
Self-Driving AI-Based Tractors
These smart tractors combine three technologies: artificial intelligence and radio navigation plus laser gyroscope. On the first ride, it must be driven by a real farmer. After that, it remembers the route and repeats it automatically. With every new ride, the tractor gets smarter; i.e. it is trained as a real pupil. Moreover, during its work, it sends all the information to a mobile app, so a farmer can track the process remotely.
Tractors with Computer Vision
Computer vision is a complicated system consisting of a web camera, GPS module, and a computing block installed in a tractor. It helps detect various objects on the way of the machine and change the route in order to pass them by. At the same time, precise coordinates of these objects are sent to a special app.
Smart Irrigation Systems
These systems offer an innovative approach to fighting with weeds. A webcam captures a picture of plants, which is sent to a dedicated server and processed with AI-based software. The latter distinguish weeds from good plants and sends the information to the irrigator, which sprays chemicals only on weeds. On the one hand, it helps reduce chemical consumption. On the other hand, it keeps vegetables free of chemicals.
Predictions from the Space
A new smart solution is called Harvesting. This is a smart program that gets data from satellites and processes it using machine-learning algorithms. Based on the data collected, the program makes accurate predictions regarding the corn yield. It helps farmers plan their activities and budget more precisely.
Plant Diseases Diagnostic
This idea is very promising; however, as of now, it tends to be a sort of raw. The concept is as follows: you upload thousands of pictures of healthy and affected plants in the app. The AI-based app analyses them and “remembers” how various diseases look. After that, all you need is to take a picture of an affected plan and load it in the app. After that, you immediately get the right diagnosis and recommendations on treatment.
Self-learning chatbots can be used as virtual advisers and assistants for farmers. They can learn and store tons of useful information and give fast and precise answers and recommendations at any moment.
As you see, both mixed reality and artificial learning are very promising technologies for the agricultural sector. They help minimise the share of hard physical labour and boost the efficiency of working processes.
About the Author
Vitaly Kuprenko is a technical writer at Cleveroad. It is a software development company located in Eastern Europe. His mission is to provide people with interesting material about innovations in the world of IT.