Monitoring Air Quality in Urban Areas Using a Vehicle Sensor Network (VSN) Crowdsensing Paradigm

Abstract

We present new advances in monitoring particulate matter (PM) in urban areas within a participatory vehicle sensor network (VSN) that exploits the use of multiple mobile low-cost IoT devices. These devices send geolocated PM measurements to an IT infrastructure and enabled us to reconstruct, in real time, the spatial and temporal distribution of pollutants in the study area in a web-based environment. The newly acquired data were integrated with independent reference measurements available from governmental environmental agencies. We deployed the infrastructure in the city of Trieste (Italy), since the beginning of 2021, with the help of several volunteers and the local transportation authority (Trieste Trasporti). By analysing the data, we delineate areas with lower air quality and identify the possible causes of these anomalies. We were able to define a belt outside the urban center where an enhanced concentration of pollutants occurs due to a higher flux of vehicular traffic that tends to jam there. Overall, our results demonstrate that this approach can be helpful in supporting urban planning and can also stimulate the community to reflect on how they can improve air quality in the area they live by reducing the use of private cars in favour of more widespread public transportation usage.

Hyperlocal Air Pollution in London: Validating Low-Cost Sensors for Mobile Measurements from Vehicles

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Blockchain-Based Reputation Sharing for High-Quality Participant Selection of MCS

“…It is a new data acquisition mode that combines crowdsourcing ideas and perceptual ability of multiple mobile devices. MCS leverages the movement of people to perceive and collect data according to specifc requirements, which has been applied in air monitoring, intelligent transportation, urban management, and other aspects [1][2][3][4]. Compared with the traditional fxed-deployment perceptual system, MCS has the advantages of low cost, easy maintenance, and good scalability.…”

Preference-Matched Multitask Assignment for Group Socialization under Mobile Crowdsensing

“…The Internet of Things (IoT) connects devices and equipment through sensing technology to achieve a leap forward in interconnecting things and objects [ 2 ], driving the development of mobile crowdsensing (MCS) under a large-scale sensing network [ 3 ]. As the development of MCS advances, researchers have come to acknowledge that it can significantly enhance the current approach of processes such as environmental monitoring and sensing [ 4 , 5 ]. Thus, investigating MCS technology is imperative.…”