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In this paper we present a case study of IoT participatory sensing where a user sends a query to the cloud to query a location's ozone (O3) level at a particular time to decide if it should enter the location based on its susceptibility to the O3 level detected. All IoT devices (e.g., smart phones carried by humans or smart cars driven by humans) capable of detecting O3 submit O3 sensing reports via wireless data communication links to the cloud for sensing result aggregation. The major challenge is the selection of trustworthy participants because not all IoT devices will be trustworthy. We leverage a “Trust as a Service” (TaaS) cloud utility to address the issue of selecting trustworthy participants. Using real traces of O3 levels and mobility traces of users in the O3 community of interest (O3COI) group in the city of Houston, we demonstrate that with the help of the TaaS cloud utility, a user in this O3COI group is able to obtain O3 readings very close to the ground truth O3 level despite 30% users are untrustworthy.