Video telematics is forecast to grow at a 16.6% CAGR in the North American region alone in the coming years (Berg’s Insight). Video telematics is one of those truly rare occurrences in the industry where everyone benefits – driver, fleet manager, fleet owner, and telematics service providers (who integrate video). It is then no surprise that from being a “nice to have” add-on on top of telematics for commercial fleets, video telematics has come into its own in 2021 becoming a key part of the suite of tools at the disposal of a fleet manager.
Crash for cash scams, where scamsters ‘create’ accidents by cutting in front of a truck and braking hard, etc., meant that drivers and fleets were getting blamed for accidents they were not at fault in. Further, this not only hurt the fleet’s business interests seriously with pay-outs for fraudulent claims, but it resulted in insurance becoming more expensive for the fleet for no fault of theirs. For drivers, this dangerously threatened their livelihood as accumulating a lot of points on their license can stop them from driving. As a result, fleets started installing dash cams that recorded video all the time. These were mostly not connected cameras – so if there is an accident or a claim, to know exactly what happened, one had to access the camera, connect it to a computer and ‘pull’ out the video manually. This was a huge moment for the commercial fleets industry because they now had a tool that could protect their drivers and their business against fraudulent claims
That one needed physical access to the camera (the vehicle) was a problem – this was solved by having cameras that were connected. They had 3G (now LTE/4G) so that using a dashboard or a web application, a fleet manager sitting in her office can request a video snippet from a particular dash camera. Driver exoneration was the first use case of dashcams and to date, remains the most important benefit from a driver and fleet’s perspective.
Telematics units have accelerometers that can detect hard braking, acceleration, and cornering. Since these events usually stem from a lack of anticipation, they were seen as cues of dangerous driving. Just knowing these events had occurred with no other context meant a fleet manager or a driver could not revisit the event to study how it happened, why it happened, and if something could be done to prevent such events from occurring.
With dashcams already installed, one had to connect the camera to the telematics unit in some way so that every time a high G event occurs, a snippet of video would automatically be generated and optionally uploaded to the cloud.
So, for example, if hard braking occurred, the fleet manager could see the video to see what happened and if the driver was at fault or not. In many a case, the driver would have braked to avert a collision that became likely due to some other vehicle’s mistake. These were instances where drivers would have unfairly got blamed, instead, they were now commended for taking evasive action and avoiding a bad outcome. From merely recording data in case it is needed, cameras moved up a step to provide context when high G events occurred.
There was still no way to know if a driver was distracted or tailgating a vehicle before a hard braking event. Some premium video telematics services offered a manual review of event videos generated from high G events that would tag every event as to whether it was preventable or not, thus providing fleets with information that could be used for driver training and coaching. These services were very expensive.
As AI and ML advanced in the last decade, chipsets that could run AI/ML algorithms in real-time entered the market. From approximately 2015 onwards, new-age video telematics companies came to the fore. AI on the edge was their key differentiator. For a fleet, what this meant is that the smart camera could “see” what was going on and could tell if a driver was distracted or tailgating a vehicle even if there was no hard braking event! In-cab coaching became popular – providing real-time feedback to the driver whenever the AI detected dangerous driving. Preventive and predictive were the new mantras.
With AI on the edge, fleet managers now had an extremely granular and realistic picture of the risk that their fleet faced from dangerous and bad driving practices. From relying on high G events only for understanding driver behaviour, fleet managers now could rely on direct causal indicators of risk such as tailgating, stop sign violations, distracted driving, use of electronic devices, drowsy driving, etc. From a coaching perspective, this meant driver feedback and coaching would become highly personalized and actionable.
For AI-on-the-edge to become mainstream, it is important to be able to optimize the AI so much that it can run on ‘ordinary’ hardware that does not have very expensive GPUs. Further, no matter how great a camera offering is, to truly go mainstream, globally, customers must have choices! So, smart dash cams that span a wide range of hardware across price points are needed. This is especially true for telematics service providers who are looking to integrate video telematics – having options will mean they can cater to different segments of their installed base as well as go global.
AI can be used to analyze videos and provide a lot of insights. There is a risk of going after gimmicky features that serve more as cool demos and features for marketing than provide a serious benefit to the fleet. There will be a greater focus on benefits, than features.
Whether it is driver exoneration or driver coaching, workflows will come to the fore. Ease of use will trump feature richness. UI and UX will become extremely important – expectations from B2B software traditionally have been low as far as UI and UX are concerned, but it will no longer be so. The most popular solutions will not necessarily have the most features, but they will have features that are intuitive and easy to understand and use.
While there is an inordinate focus on using video to detect dangerous driving, one should not lose perspective that an overwhelming percentage of drivers are consummate professionals who have impeccable safety records and often do heroic maneuvers to protect others on the road! Using video to recognize such positive behaviour and appreciating such drivers will be a key trend.
Installation of a dashcam solution has traditionally involved expert installers, resulting in the vehicle being unproductive for a longer time and costing the fleet. There will be a big move towards solutions that are easy to install, and preferably self-install. Applications will guide the fleet technicians during the install process – saving fleets time and money!
Finally, as video telematics goes mainstream, whether it be a fleet or a telematics service provider offering video telematics, the question of how to manage the cameras in the field becomes the focal point. Tools to understand camera health, data consumption, and the ability to do updates over the air (OTA) will be crucial. Without this, scaling will be nearly impossible.
In summary, 2022 will be a huge year for video telematics – it provides huge opportunities for fleets and telematics service providers alike. For fleets, it helps protect their reputation, guard against fraud, understand driver behavior better, helps drivers become safer, and reduces accidents – saving money for the fleet. From a fleet’s perspective, they would very much appreciate if telematics service providers offered integrated video telematics – so that they have one technology vendor for all their needs – from location analytics, compliance, operations, maintenance to video analytics! Therefore, this presents telematics service providers an opportunity to differentiate and upsell, providing more value to their fleet customers while improving their key business metrics.
Happy new year to everyone!