Smart cities utilize various Internet of Things (IoT) sensors to collect data around the city to improve traffic congestion or reduce noise and pollution. But one major obstacle stands in the way: cities are large and it’s impossible to deploy sensors all over the city.
This is where Pei Zhang comes in. The associate research professor at Carnegie Mellon University is trialing a project in the Chinese cities of Shenzhen and Tianjin that turns taxis into a mobile sensing platform.
“Placing sensors all over a city with high density would be expensive and difficult to maintain, but managed fleets like taxis are everywhere and go everywhere in a city,” Zhang said in a press release.
Zhang and his colleagues have developed an algorithm to optimize data collection routes by providing financial incentives to taxi drivers to travel to less popular areas. The algorithm takes several factors into account, such as the location of a given taxi, the possible routes, the potential customers and the need to reduce costs.
Zhang has now teamed up with the Chinese company Environmental Thinking to install sensors on 146 taxis in Shenzhen and 19 in Tianjin. To date, the researchers have seen a 40 percent improving in sensing coverage quality and up to a 30 percent increase on ride request matching rates.
“As cities becomes smarter, our system will provide high resolution and accuracy sensing information to city managers or occupants,” said Zhang. “With better situational awareness, a smart city will be better able to respond to its occupants.”
