Arrive Alive

Big Data and telematics: Reinventing road safety

The science of telematics has long been applied to keep track of vehicles and to protect those vehicles, their drivers, and their cargo. Now, Big Data is driving an explosion in the power of telematics, which presents huge benefits for drivers and fleet owners alike.

Telematics is a field that combines telecommunications and informatics and is often used in the mobility sector to gather data from vehicles. Telematics applications then use insights from the acquired data to provide services such as protecting drivers and fleets as well as enhancing efficiency and productivity.

Big Data, on the other hand, involves the analysis of large and complex data sets to draw insights. Big Data relies on volume, variety, velocity, and veracity to ultimately provide value through the insights from the data.

As technology has advanced, sensors and Internet of Things (IoT) devices have become able to obtain ever larger amounts of data. Today, IoT generates most of the data on earth. Some estimate that the volume of data in the world should reach 163 Zettabytes by the year 2025.

In the case of telematics, the data is generated by vehicles, their drivers, and their cargo. Modern telecommunications allow that data to be transmitted in real-time. Powerful processing capacity now exists to be able to process this data, extract numerous valuable insights from it and then present these insights rapidly, in an easily digestible format.

Telematics is very much a data game today, and it is tightly interwoven with the evolution of Big Data – the processing of large, complex data sets made possible by modern digital information-storage capacity, modern analytics tools and cloud computing.

Big Data enables thorough behavioural and predictive analytics value to be extracted from telematics. Today, many telematics organisations have entered the Big Data field, purely because of the sheer amount of data their devices generate, and the need to acquire storage and processing capacity to deal with it.

This melding of disciplines has brought significant benefits for individuals and organisations, and is helping to make mobility massively safer and more efficient. These are critical considerations in a time of growing environmental awareness, safety consciousness and intense business competition.

Telematics devices are now extensively deployed across society on vehicles’ onboard computer networks to track vehicle parameters, identify maintenance issues, and to shape driver behaviours.

Besides the IoT devices and sensors that gather data, a key technology helping to gain understanding from the telematics-Big Data revolution is artificial intelligence (AI).

AI can be used in many ways to gain insights and predictions on data. For example, AI allows fleet managers to proactively monitor fleet and driver performance, using AI-powered onboard cameras.
 
Technology such as the Netstar AI Camera Solution uses road-facing cameras to provide real-time output on safe following distances and forward collision risks, while in-cab cameras monitor driver fatigue and distractions. In-vehicle voice notifications coach drivers in real time to rectify any risky driving behaviour while they are behind the wheel.
 
This application fuses telematics, AI and Big Data to source data and provide fleet managers with actionable insights that they can use to protect their fleets, as well as their brand reputation.
 
Drivers also get real-time alerts about any road danger. Driving events are tagged and recorded and uploaded to the cloud for later online review – for driver training, or in the case of insurance claims.
 
Human error accounts for 90% of road accidents. The loss of life and collateral damage from road accidents can be prevented, or reduced, by improving poor driver behaviours such as speeding, harsh braking, smoking, or using a cellphone. Better driving can also massively reduce fleet costs like fuel, maintenance, and insurance overheads.
 
AI-driven telematics using onboard cameras allows the kind of data insights to be gleaned that can improve driver safety and performance, though video-based coaching.
 
This leads to safer roads for drivers, passengers, and other road users; reduced vehicle downtime; fewer accident-related repairs and maintenance costs; and real savings on insurance premiums and fuel.
 
For fleet managers, AI-powered data analytics means safer drives, better driver behaviour, and greater efficiencies across their businesses. Ultimately, businesses can pass on the benefits of this AI-telematics-Big Data convergence to consumers in the form of more affordable services and far safer road transport networks.

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