THE GLOBAL TELEMATICS MARKET

DEMOCRATISING DATA:
Who benefits from the rise of intelligent cars?


Dr. Steve Marsh explores how telematic data can work alongside transactional, social and user data to help benefit all aspects of society


There are 37.5 million cars on the UK’s roads, all becoming more intelligent and whetting consumers’ appetites for greater convenience. Assistive technology, like self-parking and blind spot alerts, has already become commonplace.

In the newest models, everything from mileage to fuel consumption, battery levels, tyre pressure, oil and water levels is automatically monitored to provide drivers with a real-time view on vehicle performance. When a fault is detected, the necessary parts can be instantly ordered and the vehicle automatically booked into the nearest approved garage for repair or maintenance without the driver having to do anything.

When integrated with a mobile app, telematics can be taken one step further and allow drivers to complete basic everyday tasks from their smartphone, from remotely locking or unlocking the car or sounding the horn and flashing the lights if they can’t remember where they have parked. At the same time, concerns around safety and security are driving demand for even greater connectivity and intelligence in vehicles. Automatic crash notifications can sense any large impact to a vehicle and communicate instantly with emergency services to let them know there has been an accident. While GPS data can offer theft alert assistance and help recover stolen vehicles, this is just the beginning.

“Concerns around safety and security are driving demand for even greater connectivity and intelligence in vehicles”

Modern cars are being built with up to 100 sensors that measure everything from braking force to headlight use, GPS data and their proximity to other cars or objects. Each one is generating tonnes of data on speed, routes and fuel consumption. As increasingly connected cars generate massive amounts of information, the global telematics market is expected to become big business. Some analysts believe it will reach almost US$100 billion by 2026. The sheer quantity and complexity of information is overwhelming. To unlock the true potential of intelligent vehicles and telematic data, the industry needs an approach that allows extreme data-processing at speed.

By itself, telematic data holds limited value. To understand the reality on the road, organisations need the ability to harvest data from a combination of images, video and audio to develop their intelligence-gathering arsenal. The cloud has provided organisations with the infrastructure to explore and analyse information like never before. The power of a scalable structure allows telematic data to be ingested and processed in real-time then visualised to show something that is easily understandable. Only then is it possible to draw intelligence, knowledge and information from the data available.

For example, by monitoring the time of day that someone is driving, the length of journeys, their average driving speed, braking performance and the type of roads that they are driving on then it’s possible to gain valuable insight into driver behaviour: insurers then use this information to deliver personalised pricing on policies. Drivers that demonstrate safe driving can benefit from reduced premiums, while high-risk driving can increase them. In the event of an accident, telematics also helps insurers gain deeper insight into accidents and reconstruct certain scenarios to understand how a crash happened and who is at fault. Data on a vehicle’s movements immediately before and after a crash can be gathered to provide a visualisation of the crash and help validate a claim. Through this approach, insurers are using telematic data to align premiums with actual need and support claim management to boost profitability.

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Bringing together multiple data sets and drilling-down into the data using complex multi-dimensional filters, such as time range, specific locations or even vehicle type, can make data even more powerful. Take the data that insurers are collecting on driver behaviour - everything from braking habits to idling and accelerating. When this insight is combined with other data sets and visualised, it shows people something they understand and reveals hidden patterns. Local councils could combine it with information on weather conditions or time of day and visualise the data as a heat map to understand how the behaviour of drivers changes in response to bad weather or conditions on the road.

Companies using city IoT data can make links between seemingly unrelated datasets, helping a city to become smarter, greener, healthier and more efficient. Looking to the future, 5G also has a key role to play in making this a reality. 5G is made up of small cells, which offers speeds that are 50 times faster than 4G and capable of transmitting data to and from connected devices at low latency. As 5G becomes commonplace, location intelligence will continue to advance.

“By using city IoT data links can be made between seemingly unrelated datasets, helping a city to become smarter, greener, healthier and more efficient”

The cells that make up 5G will become mini-data centres that operators use to work out the movement of people and traffic. The ultra-fast low-latency that 5G offers, combined with the emergence of omnipresent cloud connectivity, can also be used to exchange data between connected cars and autonomous vehicles, almost instantly. In the future, we will reach a point where a city or town could identify a spell of bad weather on the horizon and dynamically adjust the routes of autonomous commuter vehicles depending on the time of day and weather conditions to help traffic move more efficiently.

Telematic data is starting to permeate so many aspects of our daily lives without us even fully realising. It’s just one example of an ecosystem producing extortionate amounts of data that we need to get on top of to unlock value.

However, to realise the huge potential of telematic data, we must be able to efficiently and quickly process phenomenally large sets of data. To democratise this explosion of data and ensure the insights are used, all of the data across an environment needs to be collected, organised, indexed, analysed and visualised. Then it can be integrated with contextual intelligence and mapped in real-time. Location intelligence is all about bringing order to data. Time and location are used to index data to offer visualisations that provide deeper insights. At the same time, these insights are delivered faster so that discoveries are unearthed more frequently.

“We will reach a point where a city or town could identify a spell of bad weather on the horizon and dynamically adjust the routes of autonomous commuter vehicles depending on the time of day and weather conditions to help traffic move more efficiently”

In today’s constantly connected environment, each device fitted with an IoT SIM becomes a point of interest. A data-first approach assists us in using the data available to improve efficiencies and gain a competitive edge. Collecting data is one thing, using it productively is another.

FYI


Dr Steve Marsh is chief technology officer of GeoSpock

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