What's a winemaker to do if he wants to ensure the thousands of bottles of wine he produces are filled with just the right amount of liquid, free from unwanted residue and not broken? He can use computers to watch out for problems.
People obtain the bulk of information about the world around them with the help of sight, and then the brain processes the information received by interpreting it in a special way. Since the invention of computers, the question arose about the possibility of implementing this process with computers. Machine vision is one of the most important components of the new industrial revolution, "Industry 4.0".
The history of machine vision as a science dates back to the 1950s. It was during this period that computers began to become a generally available means of processing and analysing information. However, it should be noted that the first systems for digitising visual information were very primitive and images were small. For more than 30 years, machine vision technology has improved in laboratories - both pattern recognition algorithms and hardware have improved, bringing the technology closer to becoming commercially available. Everything changed in 1990 with the advent of the first unmanned vehicle control system.
Currently, the number of relevant machine vision applications continues to grow. In particular, tasks related to the analysis of video data in real time have become solvable. Examples include robot vacuum cleaners with machine vision systems in our homes, facial recognition systems in supermarkets and access systems in the corporate sector.
But what about Australian agriculture? Private LTE Company offer our own approach to the digital transformation of agriculture. Take a look around - we are surrounded by dozens of cameras, but no one analyses the data from them in order to benefit people or businesses.
Imagine if a camera installed in a shed could signal changes in the behaviour or temperature of cattle. Or an integrated system with a few cameras in a field is able to warn about sun damage, the right watering amount, the response to fertilizer, or possibly forecast when a crop is ready to harvest. Other examples include a machine vision system that can be trained to distinguish one grape/cherry variety from another, be combined with a robotic system for removing cake, or improve the operation of a warehouse. All these examples are no longer fiction, but actually working implementations on modern farms in Europe and the USA.
If you are worried about security, the system can be trained to notice any unwelcome farm visitors. Or vice versa, if data confidentiality is important to you, then the system will analyse only those objects that it is instructed to control. Everything else - including videos with people - will be discarded and not saved.
The types of connection to machine vision systems are also quite different. Don't feel like thinking about IT infrastructure on a farm? The solution is Machine Vision Cloud by the Private LTE Company. Maybe you want your data to never leave the enterprise perimeter - this is possible. Our experts will deploy all the necessary equipment within your location.
In any case, in the post-pandemic period, when markets are expected to be weak, it is important to enter prepared with the minimum costs possible and great opportunities for the growth of your business. But as you know, wheat does not grow instantly, and in order for restaurant guest to be offered the steak you produce, you need to do a lot and work well. Let's do it together! Think about what you want to save from monotonous processes on your farm or agricultural enterprise. Which of your processes are not profitable or not well established?
Contact our experts and benefit from the digital transformation of your business!