Bluetooth, Wi-Fi Data From Buses Could Improve Transit Systems: Study

Transportation engineers from the University of Washington (UW) have developed an inexpensive system to sense Wi-Fi and Bluetooth signals from bus passengers' mobile devices and collect data to build better transit systems.

The technology, tested on UW shuttle buses, collects data about where bus riders get on and off, how many people use a given stop and even how long they wait to transfer to another bus.

On any given bus ride, a good share of passengers are reading, texting or rocking out to music on their phones or tablets.

"In the future, though, those mobile devices may add more value to our transit commutes than simply filling time," the researchers noted.

The challenge here is to filter out all the signals from mobile devices running Wi-Fi or Bluetooth carried by people who were near the bus but not actually riding on it.

"So we have to make sure we filter out those addresses," said Kristian Henrickson, civil and environmental engineering doctoral student and research assistant.

The sensors - which cost about $60 (roughly Rs. 4,080) per bus - can detect a unique identifier called a Media Access Control (MAC) address associated with a particular mobile device as it boards and leaves the bus to offer complete and real-time travel data.

The system only collects MAC addresses and the time and location they are detected from Bluetooth or Wi-Fi signals, and each address is anonymised for privacy protection.

One open question is whether data collection that relies on Wi-Fi and Bluetooth signals could leave out certain segments of the population such as the elderly or low-income who may not carry mobile devices or use wireless networks.

That's why UW researchers are also interested in investigating how people use different technologies during their commutes.

Given the penetration of cell phone ownership, though, Henrickson said the technology's potential to improve equity in the transit system arguably outweighs possible drawbacks.

"Think about understanding how long and disconnected a route may be from some less-privileged neighbourhoods to an employment centre. This technology provides a much better way of assessing that and possibly improving upon that," Henrickson noted.