Performance Evaluation of IoT Sensors in Urban Air Quality Monitoring: Insights from the IoT Sensor Performance Test

Abstract

In this paper, we report on extensive experiments conducted to evaluate Internet of Things (IoT) sensor performance in monitoring urban air quality. As certified sensors showed a considerably reduced air quality measurement error of 4.3% compared to uncalibrated sensors at 8.5%, our results highlight the crucial function of sensor calibration. The performance of sensors was impacted by environmental factors; higher temperatures produced better accuracy (3.6%), while high humidity levels caused sensors to react more quickly (2.3 seconds). The average air quality index (AQI) recorded by inside sensors was 45, but outside sensors reported an AQI of 60. This indicates that the positioning of the sensors had a substantial influence on the air quality data. Additionally, the methods of data transmission were examined, and it was found that Wi-Fi-transmitting sensors had lower latency (0.6 seconds) and data loss (1.8%) than cellular-transmitting sensors. These results emphasize the significance of environmental factors, sensor placement strategy, sensor calibration, and suitable data transmission techniques in maximizing IoT sensor performance for urban air quality monitoring, ultimately leading to more accurate and dependable air quality assessment.

Keywords

• urban air quality
• iot sensors
• sensor calibration
• environmental conditions
• data transmission methods