The Accuracy of Sorting Beverage Cans and Bottles for a Reverse Vending Machine

Main Article Content

egkarin watanyulertsakul


At present, there are many types of beverage packages such as cans and plastic bottles which lead to a large number of waste beverage cans. Furthermore, throwing beverage cans away without management tends to be an ineffective way to get optimal utilization of resources. Hence, the primary emphasis of this work is on the development of automatic sorting of beverage cans for reverse vending machines. In addition, the accuracy testing of sorting beverage cans by the machine was designed based on three techniques which are easy to implement and which will bring sustainable energy innovations with communities’ participation. There are two sampling groups of cans and plastic bottles in the experimental studies. The first group is the group which already has data in the system for using this in a prototype of sorting process. The latter one is the group without data in the system or which has never been used before.

Furthermore, the reverse vending machine has two types of proximity sensors; inductive and capacitive which work together. The experimental results of sorting beverage cans and bottles on two sample groups show that the average accuracy of sorting is 99.20%. The sorting of beverage cans and bottles based on magnetic hinge and barcode provides an average accuracy of 79.20% and 50.00%, respectively. Classifying using the proximity sensor has the fastest operation with an average of 2.66 seconds, followed by barcode and hinge. Those takes 4.01 and 5.21 seconds, respectively.


Article Details

How to Cite
egkarin watanyulertsakul, “The Accuracy of Sorting Beverage Cans and Bottles for a Reverse Vending Machine”, ECTI Transactions on Computer and Information Technology (ECTI-CIT), vol. 13, no. 1, pp. 70-79, Oct. 2019.
Artificial Intelligence and Machine Learning


[1] Chanthuma P. Success Factors in the Recycling Bank of Kham Ngnang Ruay in Kham Nam Saep Sub-district, Warinchamrap District, Ubon Ratchathani Province. Area Based Development Research Journal, 6(5), 2014, pp 94-107.
[2] Wongpanit. Product Purchase Invoice on Thursday 18 April 2019. (Online) April 18, 2019. (cited April 18, 2019). Available from: print_history_price.
[3] Oldring, P. K. Packaging Materials 7. Metal Packaging for Foodstuffs, International Life Sciences Institute, Sep. 2007. D/2007/10.996/7, ISBN 90-78637-06-6, Belgium (44 pages).
[4] Choudhury, B., Choudhury, T. S., Pramanik, A., Arif, W., & Mehedi, J. (2015, March). Design and implementation of an SMS based home security system. In 2015 IEEE International Conference on Electrical, Computer and Communication Technologies (ICECCT) (pp. 1-7). IEEE.
[5] Mayhall, D. J., Stein, W. and Gronberg, J. B. Computer Calculations of Eddy-Current Power Loss in Rotating Titanium Wheels and Rims in Localized Axial Magnetic Fields (No. UCRL-TR-221440). Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2006.
[6] Kinney, T. A. (2001). Proximity sensors compared: Inductive, capacitive, photoelectric and ultrasonic. Online: https://machinedesign. com/sensors/proximity-sensors-compared-inductive-capacitive-photoelectric-and-ultrasonic.
[7] Hornung, M. R., & Brand, O. (2012). Micromachined ultrasound-based Proximity sensors (Vol. 4). Springer Science & Business Media.
[8] Ruan, J., & Xu, Z. (2011). A new model of repulsive force in eddy current separation for recovering waste toner cartridges. Journal of hazardous materials, 192(1), 307-313.
[9] Eddy current aluminum recycling machine from crushed electrolytic capacitors . [Online]. Available
[10] Platt, C. (2016). Encyclopedia of Electronic Components Volume 3: Sensors for Location, Presence, Proximity, Orientation, Oscillation, Force, Load, Human Input, Liquid and Gas Properties, Light, Heat, Sound, and Electricity. Maker Media.