Sep 23–26, 2019
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Executive Briefing: Making intelligent insights at the edge—The demise of big data?

Alasdair Allan (Babilim Light Industries)
5:25pm6:05pm Wednesday, September 25, 2019
Location: 1E 10/11
Average rating: *****
(5.00, 1 rating)

Who is this presentation for?

  • Managers and architects




The current age where privacy is no longer “a social norm” may not long survive the coming of the internet of things. Big data is all very well when it’s harvested quietly, silently, and stealthily behind the scenes. To a lot of people, the digital internet still isn’t the as real as the outside world. But it’s going to be a different matter altogether when your things tattle on you behind your back.

The recent scandals and hearings around the misuse of data harvested from social networks has brought long-standing problems around data privacy and misuse to the surface, while at the same time the GDPR in Europe has tightened restrictions around data sharing. However, Alasdair Allan explains, the new generation of embedded devices, and the arrival of the internet of things, may cause the demise of large-scale data harvesting entirely.

In its place, smart devices will allow you process data at the edge, making use of machine learning to interpret the most flexible sensor we have, the camera. Interpreting camera data in real time, and abstracting it to signal rather than imagery, will allow you to extract insights without storing potentially privacy- and GDPR-infringing data.

While social media data feeds provide “views,” lots of signal, it provides few insights. Processing imagery using machine learning models at the edge, on potentially non-network-enabled embedded devices, will allow you to feed back into the environment in real time, closing the loop without the large-scale data harvesting that has become so prevalent. In the end, we never wanted the data anyway; we wanted the actions that the data could generate. Insights into your environment are more useful than write-only data collected and stored for a rainy day.

Prerequisite knowledge

  • Familiarity with the GDPR
  • A working knowledge of machine learning (useful but not required)

What you'll learn

  • Discover how machine learning on the device allows the processing of data and decision making in real time without reference to the cloud
  • Learn the implications for current business models built around large-scale data harvesting and some ideas around the legal, ethical, and privacy implications of the technology
Photo of Alasdair Allan

Alasdair Allan

Babilim Light Industries

Alasdair Allan is a director at Babilim Light Industries and a scientist, author, hacker, maker, and journalist. An expert on the internet of things and sensor systems, he’s famous for hacking hotel radios, deploying mesh networked sensors through the Moscone Center during Google I/O, and for being behind one of the first big mobile privacy scandals when, back in 2011, he revealed that Apple’s iPhone was tracking user location constantly. He’s written eight books and writes regularly for, Hackaday, and other outlets. A former astronomer, he also built a peer-to-peer autonomous telescope network that detected what was, at the time, the most distant object ever discovered.

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