Wireless Sensor Network Dependable Monitoring for Urban Air Quality

This paper presents an Internet of Things-enabled low-cost wireless sensor network with newly-developed dependable schemes to improve reliability for monitoring air quality in suburban areas. The system features sensing units for router communications with energy savings from dynamic conservation. Based on the reliability function and mean time to failure, a continuous time Markov chain model is used to analyze the monitoring performance. The proposed dependable monitoring network is shown to achieve high availability with regards to energy consumption and data assurance with the survival probability of over 80% during a minimum period of 72-hour operation for monitoring air quality in a suburb. Distributions of fine particle concentrations studied over a 6-month period demonstrate feasibility of the developed system in its high correlations to benchmark monitoring stations with the Pearson's coefficients obtained at 0.903 and 0.817 respectively for PM2.5 and PM10. Statistical analysis is conducted for performance evaluation in association with two extreme events, one with bushfires and the other with pandemic lockdown. The results obtained indicate enhancements in reliability and accuracy of the colocated dependable low-cost sensors network proposed for wireless monitoring of air quality in urban conditions.