How Data Science is shaping the Future of Connected Vehicles By Manish Panjwani, CTO, Shriram Automall

How Data Science is shaping the Future of Connected Vehicles

Manish Panjwani, CTO, Shriram Automall

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In an exclusive interview with CIO Tech Outlook, Manish Panjwani, CTO Shriram Automall, shares the role played by data science in improving the quality of automobiles and how it has changed the way automakers deliver upgrades to their offerings. He also provides pointers on how public enterprises can leverage this data to improve the existing public infrastructure to mitigate climate change. With over eight years of experience as a CTO and co-founder of two innovative companies, he is a business and technology leader who leverages cutting-edge solutions to achieve strategic goals and operational excellence.

Data science contributes to the energy efficiency of connected vehicles. In what ways are automakers using data science to enhance the energy efficiency of connected vehicles? How does this impact the overall sustainability goals of the automotive industry?

Data is the new oil. We have vehicles which operate on numerous fuel sources, and an automaker’s goal is to get the best output from the vehicle irrespective of the fuel source. It is essential to ensure the efficiency of the vehicle without compromising on any of the security aspects, build quality or overall performance of the said vehicle.

To guarantee all of the aforementioned, data points are necessary, and these data points are stored in the vehicle’s CPU, and these are shared with the OEMs for further improvement. It has to be kept in mind that operating condition and efficiency of the vehicle is vastly dependent on the user’s behavior with said vehicle. Data is the common denominator that will accurately allow gauging of all the parameters. It will be helpful in analyzing and providing sound guidance to automakers to build efficient vehicles in the future.

Data science plays a critical role in enhancing vehicle safety, how are automakers and tech companies leveraging data science to improve the safety features in connected vehicles?

While data collection is essential, capturing the right day is paramount. Capturing data through sensors, cameras, and other peripherals helps drivers make better-informed decisions in many ways. Initially, this was carried out with ADAS (Advanced driver-assistance system). Currently, ADAS 2.0 is the norm; there are plans for version 3.0 and 4.0, which are geared towards an autonomous vehicle. As the shift to driverless cars is becoming apparent, more components and technologies are becoming involved, with data being the crux of it.

Data science plays a major role in predicting the behaviors of objects on the streets, ranging from pedestrian activity to reading the traffic lights. These scenarios, which are relevant in the real world, are trained back to the systems, which are called models. The data becomes a benchmark for determining safety standards for the vehicle.

With the growing amount of data generated by connected vehicles, what role do data analytics and artificial intelligence play in improving predictive maintenance and reducing unexpected breakdowns?

Many vehicles generate a sizable volume of data, and this data, directly or indirectly makes its way into the OEM centres. Here one can predict the possibility of vehicular damage which may result in a breakdown. While the vehicle would be on the road and the center will be at different a different location, it is important to establish the connection between the two of them.

As we progress, the features will multiply by a thousand fold, and the data points will correspondingly increase, the amount of permutations and combinations in this data set will be astronomical when externalities are put in to the picture. These parameters will inevitably play a major role in determining vehicular breakdown. These are some spaces where lot of innovations can be seen happening in the future.

How does data science support the integration of connected vehicles with smart city infrastructure, particularly in improving traffic management?

Innovation is on the side of the private players. A lot of innovation is happening, systems are being updated on the go without the necessity of going to a pit shop. The pit shop is now digital, the OEM (Original Equipment Manufacturer) sends a patch that updates the vehicle on the run, the performance boost is happening irrespective of the location of the driver. The data science is evolving at a pace where autonomous vehicles are fast approaching.

The public infrastructure should also be upgraded by leveraging the data. Public enterprises and corporations alike should scale up so collected data can be leveraged to its full potential. For example, traffic through an intersection can be monitored to identify predictable patterns and traffic volume so traffic lights can operate on this information.

We live in a period where ease of access to cars has resulted in large scale traffic obstructions and the environment is suffering due to this excess fuel burning, so it is important to upgrade our current mode of traffic management.


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