Issue |
MATEC Web Conf.
Volume 140, 2017
2017 International Conference on Emerging Electronic Solutions for IoT (ICEESI 2017)
|
|
---|---|---|
Article Number | 01030 | |
Number of page(s) | 4 | |
DOI | https://doi.org/10.1051/matecconf/201714001030 | |
Published online | 11 December 2017 |
Smart Bin: Internet-of-Things Garbage Monitoring System
Universiti Malaysia Perlis, ENAC Research Cluster, 02600, Arau, Perlis, Malaysia
* Corresponding author: fazira@unimap.edu.my
This work introduces the design and development of smart green environment of garbage monitoring system by measuring the garbage level in real time and to alert the municipality where never the bin is full based on the types of garbage. The proposed system consisted the ultrasonic sensors which measure the garbage level, an ARM microcontroller which controls system operation whereas everything will be connected to ThingSpeak. This work demonstrates a system that allows the waste management to monitor based on the level of the garbage depth inside the dustbin. The system shows the status of different four types of garbage; domestic waste, paper, glass and plastic through LCD and ThingSpeak in a real time to store the data for future use and analysis, such as prediction of peak level of garbage bin fullness. It is expected that this system can create greener environment by monitoring and controlling the collection of garbage smartly through Internet-of-Things.
© The Authors, published by EDP Sciences, 2017
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.