Air And Noise Pollution Monitoring System Over Internet Of Things

Phan, Tse Wai (2019) Air And Noise Pollution Monitoring System Over Internet Of Things. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

Text (24 Pages) Air and noise pollution monitoring system over Internet of Things.pdf - Submitted Version Download (1MB)

Abstract

The recent scenario of tremendous increase in air and noise pollution is the largest challenge encountered by the public.Air and noise pollution had brought a huge impact to living organism and environment where it could lead to adverse effects on human health.This creates a need of measuring and analysing the air and noise pollution level from the monitoring system in order some actions and solutions can be taken.However, there is unavailable on the combination on air and noise pollution monitoring system for the Department of Environment (DOE) in Malaysia. Besides, the data and the status of the pollutions obtained by the DOE is not shared to the public. Hence, in this project, a real-time air and noise pollution monitoring system with Internet of Things (IoT) was developed in order to store the data collected in the cloud platform.Two gas sensors with model MQ135 and MQ7 were used to detect the level of carbon dioxide (CO2) gas and carbon monoxide (CO) gas in unit of parts per million (ppm) where Gravity Analog Sound Level Meter SKU SEN0232 was used to detect the noise level in decibel (dB).The data collected from the sensors was transferred and saved to an Advanced Reduced Instruction Set Computing Machine (ARM)-based minicomputer Raspberry Pi 3 which then uploaded the data to a cloud platform called ThingSpeak.The data collection time of monitoring system for one cycle was set to a minimum of 15s where the system was set to 17s.in the experiments.The sound level meter in the system had high sensitivity as it compared with a Sound Pressure Level (SPL) meter. The MQ135 and MQ 7 sensor were well functioned and capable to detect the level of CO2 gas and CO gas in the unit of ppm. All of the data collected from the system were successfully stored and uploaded to ThingSpeak which then displayed in the ThingSpeak channel graphically.The air and noise pollution monitoring system over IoT in this project was developed successfully and well functioned.

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