Allison interviews Awf Wiswasi from MOTER about their software that collects and processes car data to help drivers, fleet owners, and insurance companies.
During a drive, MOTER software collects real-time data from the car using COVESA standards and sends the data to MOTER servers for processing using proprietary algorithms.
From the driver’s perspective, MOTER data can be used to detect events, avoid potential accidents, and provide real-time coaching to improve driving habits. Events could include speeding, hard braking, or unexpected lane departure, for example. Based on the driving behavior, a driver score is computed. The driver can recall data from a drive and determine which actions led to a reduction in their driving score.
MOTER is looking for companies and organizations to partner with to install MOTER software into cars they control. An example might be for use in a fleet of vehicles operated by a company. A fleet owner could use MOTER data to determine good vs. problem drivers. In another example, if MOTER data were provided to an auto insurer, the company could use the data to adjust insurance premiums based on drivers’ scores.
Learn more at https://moter.ai/
Using a Screen Reader? click here
Transcript of Interview:
Allison: I’m in the Moter booth, MOTER, with Awf Weswasi, and the pitch here says, “MOTER is the bridge between automotors, automakers, and insurers.” So I’m thinking this is going to be controversial and awesome. What do you have to tell us about today, Awf?
Awf Weswasi: So basically, we get our data from the car using Covesa standard signals, and then our SDK library is the software we create. We have driver scoring, driver coaching, and then accident and event detection. So basically, you have our software in the car, and as you drive for each trip, it would score you and check your driving behavior.
Allison: I don’t like that. I’m a terrible driver.
Awf Weswasi: So that’ll help you become a better driver and safer also.
Allison: So does it gamify it? Is that part of it?
Awf Weswasi: Think of it as every time you drive better, your score increases, so you pay less premium. That’s kind of the idea.
Allison: So as I’m driving, and actually it’s very strange for Steve and me that we’re watching the video, the videos are all with cars driving right where we live or in our neighborhood. So I’ve got this system in my car, and I’m going to be driving along. I’m paying attention. I’m not paying attention. I’m getting a score. And whatever I do is being reported to my insurance company.
Awf Weswasi: No. So whatever you do is going to go to the cloud, where for now, it’s mostly ride-share rentals like fleets, similar like that. And then so imagine a fleet manager wants to see who are his best drivers and worst drivers. So you can easily go look at the data, see each driver’s scoring and their driving events like speeding, tailgating, hard braking, you know, all accidents if they cause any.
Allison: I’m okay as long as somebody else is getting monitoring, just not me. But no, it doesn’t go directly to an insurance company.
Awf Weswasi: Oh, it does not. Oh, okay. It doesn’t go right away. So that’s another thing. Like it would depend on the who or the customer. So one of our customers, for example, is a non-emergency medical, like non-emergency fleet, so like not 911, but those, you know, someone wants to go to the hospital, someone’s on a wheelchair, and they need those. We install those in their vehicles also to keep monitoring how good those drivers are because maybe like someone elderly, someone is sick or injured. And so make sure they’re safe.
Allison: Yeah, basically, make sure the driver is not driving recklessly. Okay, so let’s talk a little bit more about how this works. I see two pieces of hardware here. I see a cluster module and a console map. I got a bunch of wires. I got some Ethernet going on here. What is all this hardware?
Awf Weswasi: So these, imagine these are the car infotainment systems in the middle. And so our products, basically the software that’s installed in these. That one over there acts like the car. You see, you’re sending the signals to the car software, and then our software is in there. It scores the driver and also sends driver coaching messages and information. So all you have to do is just turn on your car and start driving. And it takes care of it.
Allison: So this is hardware simulation we’re looking at right here. This is not something I’ve got to install in my car if I’m one of these drivers.
Awf Weswasi: Like imagine this is a car and that’s another car.
Allison: I got you. I got you. So we see somebody driving along and maybe they’re not paying attention to the road. It’s going to give them some sort of signal to say, “Hey, you want to look back at the road and you’re watching the score.”
Awf Weswasi: It’s speeding right now. So the driver was speeding. So you get that recorded. And then sometimes like a lane departure, if they go. And then you can go back and look at your trip, see what happened. Like look at what caused your score to drop or increase.
Allison: So this is, at this point, you’re looking at companies that you can partner with to put this in cars for, say, if you could get Uber to do it. Well, that doesn’t work as well because it’s not really a fleet, but maybe somewhere where they control the vehicle, right?
Awf Weswasi: Yeah. We want to support as many different platforms as we can so that our software can, they can just install it and then do whatever they want to do with the.
Allison: It’s got a little big brother on it. I’m not going to lie. A little bit, a little bit. But I don’t know. Again, my premise is humans shouldn’t be driving at all. So if this helps us to be better drivers, maybe that’s the right thing.
Awf Weswasi: Yeah, I would say it’s on your side, then it’s against you. It’s more to help the driver than actually like be taxing to the driver.
Allison: All right. Thank you very much. This is very interesting. The company name is Moter, M-O-T-E-R. If people want to learn more, where would they go?
Awf Weswasi: moter.ai.
Allison: Very good. Thank you.
Awf Weswasi: Thank you so much. Appreciate it.