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IoT-based collection vendor machine (CVM) for E-waste management

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Abstract

The disposal of electronic waste (E-waste) is a challenging concern since the electronic equipment contains hazardous substances. In a personal computer, there may be lead in the cathode ray tube (CRT) and soldering compound, mercury in SWITCHES, and cobalt in steel components, among other equally toxic substances. Improper E-waste management will harm the environment and human health. Hence, an appropriate waste management technique for saving the environment and natural resources is the need of the hour. In this paper, we proposed the IoT-based collection vendor machine (CVM) for E-waste management. The Customer will have registered with the proposed system to obtain a QR code. QR code consists of all necessary information related to the customers. The Customer will attach this QR code with his E-waste item and dump it in CVM. Eventually, the Collector will collect E-waste items from CVM and deposit in the warehouse for recycling and billing. The proposed prototype of CVM will use ultrasonic sensors to measure the capacity of CVM at a particular instant and send an alert message to the concerned authority at a certain threshold point. Arduino offers a platform on which one can mount the sensors and fetch the sensor's data. Proposed CVM provides us with more economical substitutes for imported devices, which cost us enormously. The proposed CVM is highly tracked and secure system than random 'kabariwala' who is unaware of the proper disposal method of toxic waste.

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Authors and Affiliations

  1. Kabadi Techno Pvt. Ltd., Agra, India

    Kuldeep Singh

  2. CSE, IEC College of Engineering and Technology, Greater Noida, India

    Gayatri Arora & Ankit Gupta

  3. CSE, Delhi Technical Campus, Greater Noida, India

    Pushpa Singh

Authors
  1. Kuldeep Singh
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  2. Gayatri Arora
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  3. Pushpa Singh
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  4. Ankit Gupta
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Correspondence to Pushpa Singh.

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Singh, K., Arora, G., Singh, P. et al. IoT-based collection vendor machine (CVM) for E-waste management . J Reliable Intell Environ 7, 35–47 (2021). https://doi.org/10.1007/s40860-020-00124-z

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