Car accidents are a common and unfortunate reality and the product of human error. However, for Bolivian Deep Micro Systems the way to safer streets and deterring driver misconduct is possible through artificial intelligence (AI).
That’s why entrepreneurs at this startup developed various algorithms to identify vehicles by reading their license plate.
When this software is then paired with the startup’s reportedly low-cost surveillance camera, it’s easier to catch cars that run a red light or are going above the speed limit.
Bolivian-born and tested, this startup aims to expand into Mexico.
Artificial intelligence for safer streets
Certainly, this technology is useful for detecting devious drivers. Nonetheless, it’s not enough to catch a person and slap them on the wrist with a fine or take away their license.
Educating drivers is a more integral approach to raise awareness on the dangers of bad driving and ultimately, prevent accidents.
In that sense, AI and IoT may lend a (digitized) hand.
Machine learning can assist by identifying recurring patterns of individual misconduct. That information, when passed on, can provide officials with more in-depth knowledge as to how to better educate these drivers.
Are they speeding in the mornings because they’re late to work? Or is it something that only happens on Friday nights when it’s likely they’ve gone out drinking? An algorithm may pick up on these insights.
It also has applications to improve urban planning and traffic control.
A missing stop sign may be causing repetitive accidents on a small intersection. Such a little detail can be caught through AI and IoT technology.
That’s why the fact that Deep Micro Systems’ solutions are open-sourced provides a hopeful note on mixing their cameras with other hardware and software to provide customized answers to each location’s unique needs.
The only thing missing in this apparently perfect picture is the assurance that the data gathered by these surveillance systems is adequately protected by decision makers and stakeholders.
Moreover, given the prevalence of passwords like “1234” and “password,” there’s still a long way to go in providing secure surveillance that also ensures a person’s privacy.
Not to mention the security risks linked to IoT tech.
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