Internet of Things (IoT) - based Fruit Sorting Results Monitoring System

DOI

10.2991/978-94-6463-587-4_74How to use a DOI?

Keywords

Algorithms; IoT; Machine learning; Monitoring; Tensor Flow

Abstract

This research presents an experiment utilizing machine learning technology in an automatic simulator designed for sorting fruit by type and color conditions. The simulator is integrated with a real-time monitoring system that uses deep learning algorithms. The deep learning methods applied enable automatic monitoring of fruit sorting results, which can be transmitted via an Android-based application over the internet. The fruit sorting machine is equipped with a dashboard for monitoring and control, displaying both the quantity and quality of the fruit. This system can also be applied directly to fruit plants, allowing remote analysis of fruit production via an internet network. The real-time monitoring system provides accurate data and information on early fruit crop production. During software and hardware testing, the fruit sorting machine was able to detect the color quality of four different types of fruit using object detection technology based on the Tensor Flow Lite algorithm. The system’s performance was evaluated using a confusion matrix, achieving a precision rate of 85.7%, an accuracy rate of 81.2%, and a recall rate of 72%. These results demonstrate that the detection system performs optimally in identifying fruit types.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - I Wayan Raka Ardana
AU  - Luh Gede Putri Suardani
AU  - I Nyoman Kusuma Wardana
AU  - I Gusti Putu Mastawan Eka Putra
PY  - 2024
DA  - 2024/12/01
TI  - Internet of Things (IoT) - based Fruit Sorting Results Monitoring System
BT  - Proceedings of the International Conference on Sustainable Green Tourism Applied Science - Engineering Applied Science 2024 (ICoSTAS-EAS 2024)
PB  - Atlantis Press
SP  - 664
EP  - 671
SN  - 2352-5401
UR  - https://doi.org/10.2991/978-94-6463-587-4_74
DO  - 10.2991/978-94-6463-587-4_74
ID  - Ardana2024
ER  -