It’s clear that connected devices are helping improve lives by monitoring things like blood pressure and infusion pumps in hospitals, and there’s the promise of solutions like connected ambulances helping speed up the diagnosis of patients. But connected devices are also critical for preventing accidents in the first case. Now, IoT can combine with edge devices, using big data to deliver real-time warnings to help prevent one of the most fatal disasters on the road: Motorcycle accidents.
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Motorcycles are at the top of the most hazardous vehicles, according to the National Highway and Transportation Safety Administration. In 2018, 4,985 people died on motorcycles, and 82,000 more were injured in crashes. This is on the rise––the figure has more than doubled over the last 20 years, since 2,116 died in 1997, and the presence of smartphones is responsible for some of the distractions that can lead to these accidents. Additionally, 31 states still do not require the use of helmets–which can reduce deaths by 42%–and are, at this point, the only proven way to save lives, according to 2012 research by the U.S. Government Accountability Office.
According to David Linthicum, Deloitte’s chief cloud strategy officer, a connected motorcycle presents a solution. Linthicum is a rider, and his main interest is, “Not having people die on the highway.”
“If you get involved in an accident, chances are you’re going to get extremely injured or you’re going to die,” he said. So he took on the project to help make riding safer. IoT devices can collect information on the road––such as speed, behavior, the direction of other close vehicles, road conditions, obstacles, and more––as well as health information on the driver, like blood pressure, heart rate, oxygen saturation, and other points.
By combining this data, the system can generate and send information to an edge device, creating real-time alerts for riders.
Riders would wear either a helmet for a Bluetooh, which would pass along these alerts, which would be configured. A rider could receive information on anything from road conditions, to fuel level, to the imminent dangers posed by nearby vehicles, for instance.
Some of these features are already available on cars, such as collision avoidance and lane-departure avoidance. But Linthicum said the issue is that “We’re not sharing data within these vehicles. We’re not analyzing data that leads to good and bad outcomes.”
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The connected motorcycle has three tiers. The IoT might have 25 points from the bike, biotelemetry points from the human from something like a Fitbit, and the data goes into an edge device like a Raspberry Pi (which is inexpensive), and this data can detect patterns and alert riders.
“What’s unique about it is that the data goes back into the system. It’s training the data to teach an AI (artificial intelligence) engine what is actually causing issues,” Linthicum said.
The architecture for the system, Linthicum said, has been built, and the implementation is pretty easy. Adding sensors to a vehicle could be as low as $10––which he recently put on a bike. The technology, he said, which is collecting data and training it, is proven. The next step is developing a prototype and getting it into production.
The system is designed to “reduce the guesswork for the rider,” Linthicum said. “When I ride my bike, my head is on a swivel. I have to be completely defensive.”
“As time goes on,” he said, “the system will become smarter. It could cut fatalities in half.”