Development of a prototype solution for reducing soup waste in an institutional canteen

Correia, Ana; Aidos, Clara; Caldeira, J.M.L.P.; Soares, V.N.G.J.

http://hdl.handle.net/10400.11/9034

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Authors

Correia, Ana

Aidos, Clara

Caldeira, J.M.L.P.

Soares, V.N.G.J.

Abstract(s)

Food waste has gained increasing attention and debate, given its economic, environmental, social, and nutritional implications. One-third of food intended for human consumption is wasted. Although it is present at all stages of the food supply chain, it is in the final stages of consumption, such as households and food services, that the problem becomes most evident. This work builds on a previous study by the same authors, which identified computer vision as a suitable technology for identifying and quantifying food waste in institutional canteens. Based on this result, this paper describes the proposal and implementation process of a prototype demonstration. It is based on a Raspberry Pi 4 platform, a Resnet-50 model adapted with the Faster Region-Convolutional Neural Network (Faster R-CNN) model, and an algorithm for feature extracting. A specially built dataset was used to meet the challenge of detecting soup bowls and classifying waste in their consumption. A web application was developed to visualize the data collected, supporting decision making for more efficient food waste management. The prototype was subjected to validation and functional tests, and proved to be a viable, low-cost solution.

Keywords

Food waste Institutional canteens Computer vision ResNet-50 Faster R-CNN Feature extraction Internet of Things Prototype

URI

http://hdl.handle.net/10400.11/9034

Citation

CORREIA, Ana [et al.] (2024) - Development of a prototype solution for reducing soup waste in an institutional canteen. Applied Sciences. 14:13. DOI: https://doi.org/10.3390/app14135729