Development of low-cost sensory system to sort recyclable materials

Recycling some waste materials can be one of the great solutions to preserve the earth. However, managing the recycling process is still an issue. One of the issues is related to sorting the waste materials. Many people still fail to place the waste materials according to their respective bins. On...

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Bibliographic Details
Main Authors: Sallehuddin, Muhammad Syafiq Iskandar, Jasni, Farahiyah, Wahid, Azni Nabela
Format: Proceeding Paper
Language:en
en
Published: IET 2022
Subjects:
Online Access:http://irep.iium.edu.my/101940/8/101940_Development%20of%20low-cost%20sensory%20system.pdf
http://irep.iium.edu.my/101940/9/101940_Development%20of%20low-cost%20sensory%20system_Scopus.pdf
http://irep.iium.edu.my/101940/
https://ieeexplore.ieee.org/document/9964153
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Summary:Recycling some waste materials can be one of the great solutions to preserve the earth. However, managing the recycling process is still an issue. One of the issues is related to sorting the waste materials. Many people still fail to place the waste materials according to their respective bins. One way to tackle this issue is to have an automated sorting system. To sort the recycle materials, sensory system is needed. Among the commonly utilized is camera. However, camera detection system usually requires high processing power and high storage. Besides, camera detection system is prone to attract thief as it can be used in many applications. Thus, an alternative sensory system is needed to automatically sort the recycle materials. In this project, the Light Dependent Resistor (LDR)-based sensory system was developed and experiments were performed to investigate the feasibility of the system. These sensors were used to investigate the optical properties of plastic bottles and aluminium cans and consequently develop a classification model to categorize plastic bottles and aluminium cans. The proposed sensory system managed to achieve average of 92.8% in identifying plastic bottles and aluminium cans accordingly. These findings proved that the LDR-based sensory system is feasible to identify some of the recyclable waste materials; plastic bottles and aluminium cans by manipulating its optical properties.