Author(s):
1. Syed Wajahat Mashkoor:
Department of Computer Science, MNSUA, Multan, Pakistan
2. Ayesha Hakim:
Department of Computer Science, MNSUA, Multan, Pakistan
Abstract:
Agriculture export plays a vital role in Pakistan’s economy. Due to inappropriate storage techniques, a large number of export quality of perishable food crops get wasted. Internet of things (IoT) plays an important role in agriculture sector as a way to improve shelf life of perishable fruits and vegetables. Information technology provides a facility to transform traditional storage methods with smart storage techniques. The objective of this study is to predict the shelf-life of perishable fruits and vegetables after harvesting with the help of computer vision and develop a smart storage chamber using IoT-based sensors to maintain the shelf-life. The smart storage chamber monitors the shelf-life of perishable fruits and vegetables and also adjusts the temperature and humidity level to maintain the food crops quality. IoT sensors including temperature and humidity are used in this system. A camera is also installed for capturing live images and prediction is made on the basis of live images by classification models. We have done classification using three different machine learning algorithms including VGG16, CNN and ANN as well as we have used Azure Custom Vision for classification. The average accuracy obtained from VGG16, CNN and ANN was 85.67%, 97.78% and 78.05% respectively. But the average accuracy obtained from Azure Custom Vision was comparatively higher than these algorithm as it was 99.98%. Smart storage chamber is designed to maintain a stable environment according to required fruit or vegetable. By implementing this system we can reduce post-harvest loss of perishable food crops by transforming traditional storage methods into smart storage techniques.
Page(s):
87-87
DOI:
DOI not available
Published:
Journal: Abstract Book on International Conference on Food and Applied Sciences (ICFAS-23) 3-5 August 23, Volume: 0, Issue: 0, Year: 2023
Keywords:
Postharvest
,
Computer vision
,
Artificial Intelligence
,
Smart Storage Chamber
,
Azure
References:
References are not available for this document.
Citations
Citations are not available for this document.