
Big data generates a lot of buzz because it enables a lot of deep insights that otherwise would be difficult or impossible to glean. That means it’s valuable not only to businesses and other organizations, but also to hackers and fraudsters.
Take the example of vehicular/transportation big data, a sprawling category that includes location, speed, drivetrain diagnostics, fuel economy and driving behavior. Vehicle data is typically collected via the On-Board Diagnostics (OBD) port, which is built into every U.S. manufactured light duty car and truck since 1996. The data is then relayed, often over cellular, to the vehicle owner and/or a party it authorizes, such as its insurance provider.
This data gives fleet owners, consumers, government transportation departments and other stakeholder valuable information such as:
- Hard acceleration and braking. For example, a taxi company might use this data to identify employees who need a refresher course that increases safety while reducing premature brake wear. Parents, meanwhile, could use this feedback to determine whether their teens are driving recklessly. State, federal and municipal transportation departments could use anonymized, aggregated versions of this data to identify roads that need to be redesigned.
- Health of systems and components. A trucking company can use a remote diagnostics system to collect engine and transmission fault code information and identify when certain repairs are needed. Through analysis and proactive maintenance, companies can save money and keep their trucks on the road.
- Congested areas. There are plenty of sources of real-time traffic information, but big data can be more effective for avoiding traffic jams and all of the costs that come with them. Understanding where their vehicles operate well below the speed limit helps long-haul trucking companies determine which routes their drivers should avoid, thus maximizing productivity and minimizing fuel waste. Transportation departments can use similar data to identify areas that need to be upgraded.
- Safety and fuel efficiency. Federal regulators could use anonymized, aggregated data to verify automaker claims about fuel efficiency and to identify models that are experiencing high amounts of accidents, potentially indicating a design flaw. This information then could be shared with consumers and fleet owners, enabling them to make decisions that would be difficult or impossible without those big data insights. With regards to fleet safety, the data can be used for driver risk and safety reporting, which captures information on speeding, seat belt usage, driver braking habits, acceleration, after-hours vehicle usage, and more.
Security Doesn’t Have to Come at the Expense of Opportunity
Those are just a few examples of vehicular data’s economic benefits, both for individual vehicle owners and collectively as a society. These same benefits are jeopardized more by attempts to lock down the data than by breaches.
Make no mistake: This data must be kept secure and private, and it can be in a variety of technological and policy ways. For example, the end-to-end encryption used for other types of big data can be applied just as effectively. Meanwhile, fleet owners, insurance companies and consumers can determine which data they’re willing to share, with whom and how it can be used.
These are among the sensible, practical and effective alternatives to heavy-handed laws, such as the SPY Car Act of 2015, that would severely limit who can access OBD-facilitated data – and thus eliminate many of that data’s benefits for vehicle owners. A more balanced approach can be found in “right-to-repair” legislation, which ensures that the OBD-enabled diagnostic data that’s always been available to manufacturer dealerships is accessible by independent repair shops, too. As a result, owners have more options for servicing their vehicles, as well as the information they need to service vehicles themselves.
That’s yet another example of the economic benefits that vehicular data provides, and we’ve only scratched the surface of what’s possible. To continue that innovation and drive even more benefits, regulators, vehicle owners and the automotive ecosystem should always look for ways to balance privacy and security with utility and opportunity.
This article was originally published on www.insidebigdata.com and can be viewed in full


Archive
- October 2024(44)
- September 2024(94)
- August 2024(100)
- July 2024(99)
- June 2024(126)
- May 2024(155)
- April 2024(123)
- March 2024(112)
- February 2024(109)
- January 2024(95)
- December 2023(56)
- November 2023(86)
- October 2023(97)
- September 2023(89)
- August 2023(101)
- July 2023(104)
- June 2023(113)
- May 2023(103)
- April 2023(93)
- March 2023(129)
- February 2023(77)
- January 2023(91)
- December 2022(90)
- November 2022(125)
- October 2022(117)
- September 2022(137)
- August 2022(119)
- July 2022(99)
- June 2022(128)
- May 2022(112)
- April 2022(108)
- March 2022(121)
- February 2022(93)
- January 2022(110)
- December 2021(92)
- November 2021(107)
- October 2021(101)
- September 2021(81)
- August 2021(74)
- July 2021(78)
- June 2021(92)
- May 2021(67)
- April 2021(79)
- March 2021(79)
- February 2021(58)
- January 2021(55)
- December 2020(56)
- November 2020(59)
- October 2020(78)
- September 2020(72)
- August 2020(64)
- July 2020(71)
- June 2020(74)
- May 2020(50)
- April 2020(71)
- March 2020(71)
- February 2020(58)
- January 2020(62)
- December 2019(57)
- November 2019(64)
- October 2019(25)
- September 2019(24)
- August 2019(14)
- July 2019(23)
- June 2019(54)
- May 2019(82)
- April 2019(76)
- March 2019(71)
- February 2019(67)
- January 2019(75)
- December 2018(44)
- November 2018(47)
- October 2018(74)
- September 2018(54)
- August 2018(61)
- July 2018(72)
- June 2018(62)
- May 2018(62)
- April 2018(73)
- March 2018(76)
- February 2018(8)
- January 2018(7)
- December 2017(6)
- November 2017(8)
- October 2017(3)
- September 2017(4)
- August 2017(4)
- July 2017(2)
- June 2017(5)
- May 2017(6)
- April 2017(11)
- March 2017(8)
- February 2017(16)
- January 2017(10)
- December 2016(12)
- November 2016(20)
- October 2016(7)
- September 2016(102)
- August 2016(168)
- July 2016(141)
- June 2016(149)
- May 2016(117)
- April 2016(59)
- March 2016(85)
- February 2016(153)
- December 2015(150)