Monitoring Potato Waste in Food Manufacturing Using Image Processing and Internet of Things Approach

Jagtap, Sandeep and Bhatt, Chintan and Thik, jaydeep and Rahimifard, Shahin (2019) Monitoring Potato Waste in Food Manufacturing Using Image Processing and Internet of Things Approach. Sustainability, 11 (11). ISSN 2071-1050

Full content URL: https://doi.org/10.3390/su11113173

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Monitoring Potato Waste in Food Manufacturing Using Image Processing and Internet of Things Approach
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Abstract

Approximately one-third of the food produced globally is spoiled or wasted in the food supply chain (FSC). Essentially, it is lost before it even reaches the end consumer. Conventional methods of food waste tracking relying on paper-based logs to collect and analyse the data are costly, laborious, and time-consuming. Hence, an automated and real-time system based on the Internet of Things (IoT) concepts is proposed to measure the overall amount of waste as well as the reasons for waste generation in real-time within the potato processing industry, by using modern image processing and load cell technologies. The images captured through a specially positioned camera are processed to identify the damaged, unusable potatoes, and a digital load cell is used to measure their weight. Subsequently, a deep learning architecture, specifically the Convolutional Neural Network (CNN), is utilised to determine a potential reason for the potato waste generation. An accuracy of 99.79% was achieved using a small set of samples during the training test. We were successful enough to achieve a training accuracy of 94.06%, a validation accuracy of 85%, and a test accuracy of 83.3% after parameter tuning. This still represents a significant improvement over manual monitoring and extraction of waste within a potato processing line. In addition, the real-time data generated by this system help actors in the production, transportation, and processing of potatoes to determine various causes of waste generation and aid in the implementation of corrective actions.

Keywords:food waste, food sustainability, Internet of Things (IoT), image processing, potato packing
Subjects:D Veterinary Sciences, Agriculture and related subjects > D631 Food and Beverage Manufacture
D Veterinary Sciences, Agriculture and related subjects > D632 Food and Beverage Processing
D Veterinary Sciences, Agriculture and related subjects > D600 Food and Beverage studies
D Veterinary Sciences, Agriculture and related subjects > D633 Food and Beverage Technology
D Veterinary Sciences, Agriculture and related subjects > D630 Food and Beverage Production
D Veterinary Sciences, Agriculture and related subjects > D690 Food studies not elsewhere classified
Divisions:College of Science > National Centre for Food Manufacturing
ID Code:36118
Deposited On:07 Jun 2019 10:23

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