Data analytics and IoT – inseparable sources of value

Share This Article

Sadly, we’re a few years away from the Hoff’s ‘KITT’ autonomous Trans-Am supercar in Knight Rider becoming a reality on British roads. But it’s not impossible – as the Internet of Things continues to gain momentum across almost every aspect of our lives, cars are in the vanguard, rapidly getting smarter and more connected.

My car isn’t too old or too shabby, but when it does occasionally grumble or whinge at me, the feedback it gives isn’t the most helpful… Usually, the first sign I get that something’s wrong is when an unintelligible hieroglyphic appears on the dashboard.

Trawling through the car’s manual for translation – and then eventually resorting to searching online from my smartphone – the real problem isn’t a lack of information, but simply that there’s too much of it. And most of it is irrelevant. When all I need to know is whether it’s safe to drive home, or if I need to sit still and call for roadside rescue.

Large volumes of unstructured data can just be a burden to manage – but add context and suddenly you’ve created intelligence. Add analysis and you can derive actionable insight… and it is at this point that the IoT really starts to deliver value.

The fact that garages have been plugging into customers’ car on-board diagnostics (OBD) ports for well over a decade means that theoretically, mountains of contextualised data has long been available on every symptom, fault and fix on every make and model of car at every age and mileage.

It’s just that nobody has collected, collated and, critically analysed and presented it….

‘Co-operation’ is a word the automotive sector is largely unfamiliar with in terms of sharing information and creating industry-wide standards. This means that virtually every make and model of car has a different string of diagnostic codes for each fault.

Trying to collate these globally would have been an immense challenge even if these diagnostics were unified across the sector. The fact they’re not would make the already daunting task of creating a global overview of the health of our vehicles nothing short of a Herculean feat. But the one technology that can manage it? …Big Data.

We’ve already started to see it – whether it’s from telematics firms like Risk Technology teaming up with diagnostic reporting experts Innova or RAC mining their massive base of fix-to-fault data from 10+ years of roadside repairs, we’ll soon start to see apps on our phones giving us genuinely useful messages based on a deep analysis of the data.

“Your Audi A6 will need a new air mass sensor in the next month or 1,200 miles. Your local garage has a price-match offer on the parts and labour. Click here to see the offer …”

Imagine the day when we’re getting messages like that. But while that’s all well and good, insights like that only come from crunching huge chunks of static data offline and that’s a bit like infinite monkeys and typewriters – sooner or later, enough computing power will inevitably wring some useful insight from that much data.

What I’m really interested in is whether analytics in real-time can give me any value from the Internet of Things data in the same context. I’d like to see the day when my car tells me: “I slowed you down because there’s a patch of ice on the third bend ahead.”

And that could be coming sooner than you think. Live, connected OBD devices can already report back anonymised streams of data complete with GPS location in real-time.

This means cloud-based analytics engines can correlate metrics like outside temperature and ABS deployments with a road intersection generated from reverse geocoded mapping to warn drivers – and even autonomous cars themselves – of the dangers ahead.

This is the thinking behind INRIX’s new road safety initiative, but it’s already feasible for any telematics service provider by reading back the OBD data from their clients’ fleets.

There is huge scope for the scale of data headed our way as the number of connected things grows, and while, like economists, there are more opinions than observers, they all agree – it’s a very big number.

But it’s all about context. Merely having this data to hand offers us nothing in terms of value. We need the systems to be able to analyse it and draw actionable insight in order to truly achieve the vision that people see and hope for from the Internet of Things.

So, before long, when something lights up on the dash, my smartphone app will simultaneously tell me that, e.g. it means there’s a non-critical but serious fault, needing attention within the next 100 miles.. so it’s safe to drive home.

In nearly all areas of life where we see a wasted opportunity or a chance to be more efficient, technology is now the magic bullet we’ve been waiting for. But to develop technology with the intuition of KITT, we desperately need a step-change in attitudes to see data analytics and the Internet of Things as two inseparable sides of the same coin.

This article first appeared in IoT Now –