Food contamination monitoring via microwave imaging technology
Thesis type EXPERIMENTAL THESIS, MASTER THESIS, MULTIDISPLINARY
Description Foreign body contamination in food is one of the major sources of complaints against food manufacturers, and can lead to injury, loss of brand loyalty and large recall expenses. Different technologies, such as X-ray or infrared techniques, are currently applied to detection systems used for food inspection, but physical contamination, with e.g. wood, plastic, metal and glass, is still present in food.
The main objective of this Master Thesis is to investigate the use of the microwave imaging (MWI) technology for food contamination monitoring. MWI is able, through low-power electromagnetic (EM) waves at microwave frequencies, to non-invasively penetrate an object and provide a spatial map of its EM properties. Such a capability is herein relevant due to intrinsic difference in such properties between food and contaminants.
The main activities will be:
- Characterization of the food/beverage dielectric properties: development of a data-base containing the dielectric properties, in the microwave frequency range, of common food and beverage;
- Development of the imaging algorithms;
- Antenna system design, prototyping and testing: the antenna system, to radiate the food/beverage products with the EM waves at microwave frequencies, will be designed and tested via full wave simulations together with the implemented imaging algorithms;
- RF front-end back-end design and prototyping;
- Accelerated implementation of the imaging algorithms with specialized hardware for inline monitoring (e.g. GPU, FPGA, …).
During the Master Thesis the student(s) will work on one (or more) of the previous activities, related to the student background and interests.
Main reference: J. A. Tobon Vasquez, R. Scapaticci, G. Turvani, M. Ricci, L. Farina, A. Litman, M. R. Casu, L. Crocco, F. Vipiana, “Non-invasive In-line Food Inspection via Microwave Imaging Technology”, IEEE Antennas and Propagation Magazine, Special issue on EM Imaging for Food, Vol. 62, No. 5, Oct. 2020, pp. 18-32, [DOI: 10.1109/MAP.2020.3012898]
Deadline 03/12/2022 PROPONI LA TUA CANDIDATURA