The young Dutch company Odd.Bot developed a smart robot — and immediately won the 5G Hub Innovation Challenge. This robot is weeding while driving across the field. A camera, in combination with artificial intelligence (AI), recognizes the difference between crops and weeds. Work that previously had to be done by human hands can now be done fully automated. And a person can make adjustments in real time where necessary. A good example of how companies can renew their way of working through progressive technologies. It ensures cost savings and greater sustainability.
Because, says Martijn Lukaart, founder and CEO of Odd.Bot: “We need to use less poison and fertilizer and more our intelligence. Our robot does not only work more efficiently. In particular, we want to use 170,000 in the next seven years. liter of chemical pesticides, which also ensures more biodiversity.”
Combination of new technologies
Innovations like these are made possible by a combination of new technologies. 5G provides more internet speed and more mobile bandwidth. It enables mass communication between machines and provides ultra-reliable, near real-time communication for critical applications. Edge technology moves artificial intelligence from the robot to the mobile network so that multiple robots can take advantage of it at the same time. And network slicing divides the network into slices, as it were. It creates a private network on a mobile network. This way, business applications are securely and reliably connected to the mobile network, and the capacity is guaranteed — without disruptions from other users.
Learning on the job for robots
These technological developments create plenty of new opportunities for sustainable innovation. And perhaps one of the most interesting aspects of this: the unprecedented opportunities for machine learning. As the example of Odd.Bot shows, people can actively participate in the automated process. They can watch directly and give directions. In this way, people share their knowledge and experience with the robots in real-time.
In fact, this is about learning on the job for the AI, which collects more knowledge and insight and becomes increasingly effective. For example, new applications no longer always have to work flawlessly from day one: the AI can continue to improve itself during work and gradually even exceed the quality level of human work.