Over the past 25 years or so, San Diego has become a hub for innovation in telematics, and in providing technologies and services that enable long-haul trucking companies and other fleet operators to monitor the location and operation of their vehicles.
Qualcomm (NASDAQ: [[ticker:QCOM]]) pioneered the use of satellite-based messaging and vehicle tracking technology in 1988 with its Omnitracs business (now an independent company based in Dallas, TX). Since then, San Diego startups DriveCam, Networkcar, and SmartDrive Systems have evolved into major providers of tracking, recording, and analytic services that help transportation companies analyze driver performance, manage risks, and improve their fleet efficiencies.
It’s turned into a big business, so much so that you might think innovation in vehicle telematics had run its course. The industry’s recent consolidations include the private equity firm GTCR’s $500 million buyout of DriveCam, now known as Lytx. In 2012, Verizon acquired Networkcar, (now operating as Verizon Networkfleet) as part of its $612 million buyout of Hughes Telematics.
But Sandeep Panya still sees plenty of room for innovation on the road ahead—especially as the development of self-driving cars accelerates.
As the president of Netradyne, a new San Diego startup, Pandya is focused on applying machine vision and machine learning technologies to the enormous amounts of data being generated by digital video cameras aboard thousands of trucks and other vehicles throughout the United States. The big idea at Netradyne is to use artificial intelligence technologies to help identify risky driver behaviors in real time—and to alert fleet managers accordingly.
“The insurance industry is looking for data on dynamic performance,” Pandya said. “It’s not enough to get an alert a day later or two days later. When you see a driver starting to struggle, a fleet manager can step in and call the driver and find out what’s going on.”
In a recent statement, Netradyne said it is incorporating AI modules made by Nvidia, the Santa Clara, CA-based chipmaker, enabling each dashboard unit to analyze video data generated simultaneously by four cameras aboard each vehicle (looking forward, backward, and to each side). Nvidia has emerged as a leader in machine learning tasks, to which its graphics processing chips are well-suited. By doing the machine learning aboard each vehicle, NetraDyne says only the most critical information is passed up to the cloud, where it can be relayed to fleet managers.
“We wanted to develop technology that solves a big data problem—and one of the basic problems in big data is [processing and analyzing] video,” Pandya said. “If you could take analytics into the device, you’d have a full-time reviewer in the cab all the time.”
Existing telematics technologies can alert fleet managers if a vehicle has been in an accident, but Pandya said Netradyne’s technology is intended to also issue real-time alerts for two other types of
