Pei Zhang, associate research professor of electrical and computer engineering at Carnegie Mellon University, turned to taxis as a mobile sensing platform. Why? A fleet of taxis has a long operational time, a large spatial coverage, and great potential for data collection…

o gain better data for accurate learning, Zhang and his colleagues developed an algorithm to create the best plan to motivate taxi drivers to drive to less popular areas-to actuate them in order to collect data via monetary incentives…

The actuation system for city-wide crowdsourcing of data reaped positive results. The researchers saw a 40 percent improvement in sensing coverage quality and up to 30 percent increase on ride request matching rates, with only 10 percent of the baseline budget required. They have collaborated with Chinese company Environmental Thinking and currently have 146 deployments in Shenzhen and 19 in Tianjin.
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