Changing face of Telematics with Autonomous Vehicles Technology Stack

Photo by Markus Winkler on Unsplash

Telematics — the technology of sending, receiving and storing information using telecommunication devices to control remote objects, the integrated use of telecommunications and informatics for application in vehicles and to control vehicles on the move, global navigation satellite system technology integrated with computers and mobile communications technology in automotive navigation systems. These are all typical definitions from Wikipedia. The industry of telematics emerged with the emergence of the telecommunication systems with 2G and GPS based positioning to share location details of a vehicle. The world today in 2021, has seen Google Waymo, Tesla Autopilot, Cruise,, Voyage like companies putting the whole GPU systems in the vehicle where the vehicle is taking all the decisions all by itself. The GPS based location tracking and Autonomous Vehicles, are two extremes of vehicular technologies. And this is a very strange situation and opportunistic in a way, where 90% of the commercial trucks are not even using Telematics and the world has reached to Level-5 Autonomy. The interesting thing to consider here is, how do we bridge the gap and how do we emerge in the age of advanced technology and communication.

The road to Autonomy and Level — 5 like autonomous systems are not going to come suddenly, it’ll be a journey, a long journey of transformation of technological adoption for commercial vehicles. The journey of vehicular telematics has started from GPS based navigation systems which is now a mandate in India for commercial vehicles and many other countries globally. The next improvement which was introduced was OBD — II based engine diagnosis along with location-based settings. With OBD-II based devices, the visibility of the vehicle being monitored improved a lot and it led to predictive maintenance which involves lots of data science and machine learning technologies. This led to requirement of high computing over the cloud/local servers for running heavy learning algorithms to derive predictions. This was achieved around 2006–2008 in US and around 2010 in India where Indian vehicles started coming with OBD-II port in the vehicles which supported J1939 and other related software stack for reading the data from the engine of the vehicle. With the OBD-II based devices which were able to get a picture of driving behavior and resulted in better fleet management systems.

The new era started in vehicular telematics when cameras joined the race as contextual information started with dashboard camera systems, which were able to record videos and store it in the device itself. Lot’s of people started using CCTV solutions in heavy vehicles for surveillance purpose. The need of the visual information started making a space in the market but there were not many of the solutions/products available in the market and those available were not affordable in the Indian context. The other most important aspect in the telematics industry is the communication medium, starting with 2G enabled devices started throwing data for OBD-II & GPS based systems. For the telematics industry to grow, there has always been a trade-off between the performance & price. If you want more features, there’s a cost to pay per vehicle, but there’s very little room available for high-end technical products to outshine old ones as they are little more expensive and so becomes luxury where older technology is easily available for lower cost. The real challenge for newer technologies to pre-empt the GPS based systems and speed-based analytics which is going on since years now.

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Entrepreneur, Startup Founder & CEO @drivebuddyAI. Learning from human drivers for the future drivers.

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