The device named “CATCH”, developed through a joint effort between the Food Engineering Process Laboratory at the İzmir Institute of Technology (İYTE) and the Software Engineering Department at Yaşar University’s Faculty of Engineering, can quickly and reliably detect adulteration in liquid foods such as honey, molasses, and olive oil.

The AI-based system can determine the rate of falsification in liquid foods with high accuracy. By combining thermal imaging technology with convolutional neural networks (CNN), CATCH analyzes not only whether a product is adulterated, but also the exact amount of the adulteration. This innovative technology has been registered and patented by the Turkish Patent and Trademark Office.

Thanks to its user-friendly interface, the device can be operated with a single button and does not require any technical expertise. With this feature, CATCH offers practical usage not only in research laboratories but also in production facilities, quality control units, and market inspections.

How Does the System Work?

CATCH’s technical infrastructure utilizes a combination of thermal imaging technology and convolutional neural networks. Thanks to this architecture, the system can evaluate the purity of the analyzed product while simultaneously determining its adulteration rate in detail.

Click here for the article by TTO İzmir.