Three winners that used sensors and GPS trackers to gather various types of data were named following the 48-hour hackathon.
San Francisco has made itself a blank canvas for the Internet of Things, and creators have now begun to trace the beginnings of paintings on it.
The city offered up public infrastructure to a private company, SIGFOX, in October in order to establish a network dedicated to IoT solutions. Officials in the city Department of Technology were quick to point out at the time that the city didn’t have any specific uses in mind for the network, but wanted to foster the creativity of its tech-centric environs to find beneficial applications.
So the city hosted a 48-hour hackathon from Nov. 20-22 in an effort to develop ideas. On Nov. 23, the department announced the winners:
“The hackathon generated some really good use cases and basically prototype or experimental proof of concept that some of these things could be accomplished with IoT enablement,” said San Francisco CIO Miguel Gamiño.
The projects are all in early stages, he said, but could offer broad benefits to the city in the future. For instance, Audio Argus might be useful for detecting when certain machines like fleet vehicles and medical devices are close to breaking down.
“With audio sensors, maybe you can predict mechanical breakdown because those things make certain sounds and sound signatures,” Gamiño said.
Better Bike might also one day lead to better-informed city planning. San Francisco is aiming for zero traffic deaths by 2024, so Gamiño said efforts like Better Bike would be poised to contribute to safer urban design.
“That could be used for all sorts of different things,” he said. “It might influence how traffic patterns are designed for bikes to increase safety.”
Applications for the city’s IoT network don’t necessarily have to be for municipal purposes, he said, noting that they could also run for commercial uses. The SIGFOX network also might not be the only network the city uses for IoT solutions.
Ultimately, he said, the future is wide open.
“We are very much at a frontier,” he said. “What I’ve often said is that it’d be like trying to predict the ultimate killer app of the Internet 30 years ago. Thirty years ago you wouldn’t have been able to predict Airbnb or Uber, or else you’d be $50 billion [richer], right?”