The other day I heard about an interesting experiment to deliver highly targeted advertising to Japanese consumers.
Now, as we all know, Japan is a pretty consumer-driven society with a high uptake and appreciation for the latest and greatest in gadgetry -- heck, this is the country that invented multi-function toilet seats which perform a plethora of functions in one. So given the sophisticated nature of the Japanese consumer, it is fair to expect that their advertising will be similarly sophisticated.
The experiment I heard about brought together a bevy of different vendors -- data storage, hardware manufacturing, big data and the like. The idea of the experiment was to deliver targeted roadside advertising within the context of digital signage. Signing up to all the right buzzwords, I was told that the experiment would leverage big data, deep learning and artificial intelligence.
What really happened was pretty simple -- a camera would record individual cars as well as traffic patterns and volume. The system would apply automatic vehicle recognition to work out what type of vehicle was being driven. The premise being that advertising for a driver of a Toyota Prius is probably different from that for the driver of a Porsche. Th project (which, it must be added, is at this stage merely a proof of concept) is planned to be ready for practical application in the next six to 12 months.
That in itself is kind of weird -- Quanta and Intel deal with servers and silicon. Even Cloudian's industry area is deep infrastructure, not the sort of place that you'd expect to find externally-facing projects.
Still, it's a good way for these vendors to gain some external attention, I guess. In terms of the actual public facing aspects, once the analytics were in place to recognize vehicle makes and models, Dentsu created ads that are targeted toward specific vehicles.
Cloudian kicked off the project by providing the software with training data that consisted of a large volume of vehicle information, images and video of car models, plus vehicle attribute inputs. This information was classified using the smart data storage functionality and will be tested to accurately identify vehicle models on Tokyo roadways.
As part of this experiment, Cloudian will also capture detailed, real-time data related to traffic volume at various times in the day, which can be made available to public institutions such as the Ministry of Land, Infrastructure, and Tourism, local municipalities in Japan and to enterprises for retail location planning.
This just feels too course for me. Recognizing vehicles based on imagery is not massively novel. It is an extension (actually, a simpler problem, to be honest) to social networks' facial recognition software that consumers have somewhat grown accustomed to.
I'm also pretty dubious that something as blunt as the sort of car that I drive can really generate predictions about the sort of advertisements that will be most appropriate for me -- people have lots of different reasons for the sort of cars they drive.
It strikes me, however, that this is less about delivering a truly innovative advertising product and more about showing how these more foundational technology vendors can have a part to play in more cutting edge technology approaches. Some might say that it is the perfect example of vendors trying their hardest to look cool when they decidedly are not. There is no doubt that these contextual approaches will increasingly become the norm:
“In today’s fast-moving advertising world where consumers expect tailored experiences and uniquely relevant messages, we are thrilled to work with Cloudian and QCT to pilot an innovative, highly targeted advertising approach,” said Ichiro T. Jinnai, director, Out Of Home Media Service Division, Dentsu, Inc. “We will bring our proven global advertising expertise to bear for planning, sales and media development of the ads that are automatically served based on the deep learning analysis from HyperStore about the approaching vehicle. Cloudian is the perfect partner to lead this effort and showcase its smart data storage capabilities for a new era of IoT experiences.”
I'm not sure if that isn't slightly gilding the lily but nonetheless, this is an interesting example of applying technology in the broadest possible way -- let's revisit this project in a year or so to see where it's gone. Of course there are the overtones of a George Orwell-esque Big Brother situation with all of us being watched continuously, but I fear that is one battle which has already been lost.
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