IoT Part 2: So why the interest in the Internet of Things?

This is a fairly simple post as there are three main drivers for the sudden interest in the IoT – in no particular order:

  1. Sensor module costs
  2. Wireless networks
  3. Technology trends
A microsensor with coin for scale  this is a titan compared to the sensors that can be injected into your body for medical monitoring (credit: beob8er, Flickr)

A microsensor with coin for scale – this is a titan compared to the sensors that can be injected into your body for medical monitoring (credit: beob8er, Flickr)

Sensor modules are the electrical circuitry that incorporates the transducers that sense the information and the communications chips that send it.  Other solid-state components that perform various processing, decision-making and response functions can also be added in as required, but it’s the cost reductions of the sensors and comm’s chips that are having the most effect on the IoT market.  McKinsey recently stated that sensor/actuator module costs had dropped 80 – 90% in the last 5 years, while the Financial Times recently said that sensor/comm’s modules had dropped from 50 to 15 Euro over the last 4 years.

Wireless networks have become ubiquitous and low cost.  The coverage of fast 3 and 4G networks has supported the phenomenal uptake of smartphones, and is a key enabler for the IoT.  The volume of data generated by all these connected devices may ultimately mean that bandwidth becomes a key IoT constraint – speaking from personal experience as someone who has instrumented a fleet of 40 cars to capture around 20 data fields at 5 second intervals over months at a time, the costs associated with this can still be prohibitive even if the situation is improving.

Technology trends towards cloud computing and big data analytics (amongst others) are also key IoT enablers.  The ability host data and process it away from connected devices significantly reduces costs and lifts system performance to useful or highly profitable levels.  And the ability to handle all this data and make sense of it is also becoming more widespread.  The importance of big data analytics is clear when it is considered that a Boeing 787 aircraft generates around half a terabyte of data for every long-haul flight (Financial Times 2013).

Next post – the key challenges.

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