Investigating Users' Inclination of Leveraging Mobile Crowdsourcing to Obtain Verifying vs. Supplemental Information when Facing Inconsistent Smat-city Sensor Information

Smart cities leverage sensor technology to monitor urban spaces in real-time. Still, discrepancies in sensor data can lead to uncertainty about city conditions. Mobile crowdsourcing, where on-site individuals offer real-time details, is a potential solution. Yet it is unclear whether users would prefer to utilizing the mobile crowd on site to verify sensor data or to provide supplementary explanations for inconsistent sensor data. We conducted an online experiment involving 100 participants to explore this question. Our results revealed a negative correlation between perceived plausibility of sensor information and inclination to use mobile crowdsourcing for obtaining information. However, only around 80% of participants relied on crowdsourcing when they felt the sensor information as implausible. Interestingly, even when participants believed the sensor data to be plausible, they sought to use crowdsourcing for further details half of the time. We also found that participants leaned more towards using the crowd for explanations (48% and 49% of instances) rather than seeking verification when encountering perceived implausible sensor information (38% and 32% of instances).