AI is now everywhere and is applied to nearly everything in our everyday life.
Artificial Intelligence can also be applied to industry to upgrade manufacturing and improve production processing. Food safety can also benefit from this technology by tracking numerous data sets that can create predictive models that help prevent food contaminations.
What is Artificial Intelligence?
When we refer to Artificial Intelligence, we refer to the branch of computer science that creates algorithms and software to replicate human behaviors.
These types of software make it possible to develop machines with autonomous learning and adaptation capabilities and take the name of Machine Learning.
Machine Learning can be applied to many areas such as finance, insurance, health care, cybersecurity, home automation, interconnected devices, and industrial production, including the food industry.
How AI can help with Food Safety
The AI can be helpful because it can work on database models and create analysis on a large number of datasets acquired on various products and different product and foreign body combinations. In a food production line, the AI can improve inspection efficiency, minimize risks of market recalls, and speed up the process. Sometimes inspections are still carried out on a random and visual basis. In this way, however, many contaminated foods can escape controls, which thus do not guarantee the quality and safety of all products passing through the line. A complete automated system can ensure food safety for every product. AI can improve day-by-day learning to detect new contaminants on new products, working on nearly infinite products and combinations of contaminants.
How Xnext uses Artificial Intelligence for Food Safety
Xnext was the first food inspection company in the world to understand the infinite potentiality of Artificial Intelligence and introduced it into the x-ray inspection systems.
Xnext, together with photonics and nuclear electronics, introduced Deep Learning, a set of techniques that simulate the brain’s learning processes through layered artificial neural networks. These three technologies allow XSpectra, the Xnext patented technology, to detect low-density foreign bodies inside food products such as plastics, bones, insects, cartilages, and rubber otherwise undetectable by conventional x-rays inspection systems.
The detector, that can analyze up to 1024 energy levels of the x-rays, is integrated with the XInspector. The self-learning software, starting from a consolidated background, is adapted from time to time to specific application needs through dedicated training.
In practice, the data relating to the number of photons for each energy band of the X-rays spectrum are crossed with a specific time range. The same dataset is then used to generate an integral image of the contaminated products.
In this way, XSpectra can ensure food safety like never before and minimize consumers’ health risks.