The Fifth Elephant 2016

India's most renowned data science conference

Four horsemen of the IoT

Submitted by Anuj Deshpande (@anujdeshpande) on Sunday, 1 May 2016

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Technical level

Intermediate

Section

Full talk

Status

Submitted

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Abstract

MQTT brokers have been around for quite a bit. But never before has there been so much active development for IoT cloud providers. Silicon is cheaper than ever. IoT, especially industrial, is now feasible for even small and medium sized enterprises with lower margins.

Outline

I will be splitting the talk in 4 parts.

  1. Security
  2. Cloud backend
  3. Hardware (yay!)
  4. Data

Security - How to ensure that your devices don’t turn up on Shodan

You not only have to worry about using SSL/TLS (which is not always possible on low power silicon), but you also need to ensure that your device firmware stays secure. Non-standard practices, planned and unplanned obsolescence are causing consumers to be extremely cautious.

Running the backend like GOOG/AAPL

What if you were Apple or Google and had to manage millions of devices ?? With IoT you will have to manage devices like the big guys, no matter how small you are.
For example MSFT now has device queries in Azure IoT which is a neat buil tool to manage your fleet.

Hardware

From 8 bit microcontrollers, to FPGAs. Everything is an option as prices drop and tools become open source. The hobbyist and maker movement is surely accelerating things with the rise of ESP and Pi.
I’ll be going through this as briefly as possible using some tables and charts.
This will also cover a quick comparison of the wireless protocols.

Data -The currency of our times

You might have heard how Foursquare is accurately predicting revenue reports using the sensors in your phones. Tools like Amazon’s Rules Engine let you pipe data, like you would on the CLI, on the cloud. I’ll be showing a few examples of going from a single device to a stream of thousands using simple point-and-click configurations.

Tools like these don’t just let you collate and quantify your data, but also let you create ML models on the fly. AWS and IBM Watson are two such examples who are providing tight integrations between data gathere from things and predictions made by complex algorithms.

Requirements

None

Speaker bio

Anuj runs his own little company called Makerville, where they build hardware and the software to go with it. Some of their projects. He is working on a project called Knit which he is super excited about!

Before this he was part of the team that did Tah. He also loves to build interactive installations, like Internet connected bubble machines and life size smartphones.

Links

Slides

http://slides.com/anujdeshpande/4-horsemen-of-the-iot#/

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