Environmental air quality monitoring is crucial for precautionary measures, and for increasing awareness. The traditional method of monitoring air pollution involves temporal-spatial measurements using instruments and air quality meters. This method is both cumbersome and stressful, lacking the capability for continuous monitoring. The emergence of cost-effective, micro-scale sensing technology has significantly changed this conventional approach. An air pollution monitoring system based on Internet of Things (IoT) was developed, and put into operation. The IoT-based air pollution monitoring system, transmits data on air pollution from its sensors to ThingSpeak cloud server. This transmission is facilitated through instructions provided by the microcontroller and the internet gateway. The results of air pollution measurements obtained from these sensors are displayed on ThingSpeak webpage, enabling remote access. A comparison was conducted between values obtained from the IoT-based air pollution monitor and those recorded by conventional air quality meters. This comparison revealed a high level of accuracy, with a tolerance value of . Statistical analysis from an ANOVA test revealed a P-value of 0.993, exceeding the significance threshold of 0.05. The F value of 7.17E-05 was also observed, which falls below the critical F value of 4.747. This further established that the observed distinctions between the developed IoT-based air pollution monitoring device and traditional air meters hold no statistical significance. Therefore, the developed IoT-based air pollution monitoring system is practical and effective. It facilitates the real-time monitoring of air quality across various environments where the device is deployed. This capability ensures continuous monitoring around the clock.
Key words: Air pollution, Internet of Things, Monitoring, Temporal and Spatial Dimensions.
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