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IoT analytics, Edge Computing and Smart Objects

Guest blog post by Ajit Jaokar

In this post, I propose that IoT analytics should be a part of 'Smart objects' and discuss the implications of doing so

The term ‘Smart objects’ has been around from the times of Ubiquitous Computing.

However, as we have started building Smart objects, I believe that the meaning and definition has evolved.

Here is my view on how the definition of Smart Objects has changed in the world of Edge Computing and increasing processing capacity

At a minimum, a smart Object should have 3 things

a) An Identity ex ipv6
b) Sensors / actuators
c) A radio (Bluetooth / cellular etc)

In addition, a smart object could incorporate

a) Physical context ex location
b) Social context ex proximity in social media

To extend even more, Smartness could incorporate analytics

Some of these analytics could be performed on the device itself ex computing at the edge concept from Intel, Cisco and others.

However, Edge Computing as discussed today, still has some limitations

For example:

a)     The need to incorporate multiple feeds from different sensors to reach a decision ‘at the edge’

b)    The need for a workflow process i.e. actions based on readings – again often at the edge with it’s accompanying security and safety measures

To manage multiple sensor feeds, we need to understand concepts like sensor fusion (pdf) (source freescale).

We already have some rudimentary workflow through mechanisms like IFTTT(If this then that)

In addition, the rise of CPU capacity leads to greater intelligence on the device – for example Qualcomm Zeroth platform which enables Deep learning algorithms on the device.

So, in a nutshell, its a evolving concept especially if we include IoT analytics in the definition of Smart objects (and that some of these analytics could be performed at the Edge)  ..

We cover these ideas in the #DataScience for #IoT course and also at the courses I teach at Oxford University

Comments welcome

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