IOT Advances
Brad Parsons

IOT is Old, Meet AIOT

Next month I have been asked to present at the Industrial IOT Summit, the event is sponsored by the giants of industry, GE, Schneider, Bosch etc. As I sit here writing my presentation, I’m reflecting on the phenomena that is the Industrial IOT. Firstly, why the fuss? Sensors have been around for decades in industry. Many may be wondering what all the fuss is about. Isn’t IOT really about RTU’s, PLC’s, IMU’s (and other 3 letter acronyms?). Well yes,…. and no…. Let me explain.

We’ve seen huge advancements in consumer technologies over the last 15 years, driven by the internet, mobile phones, telecoms, cloud etc. The underlying technologies that drove the consumer era are now creating huge opportunities across industry. We can now apply extremely powerful (but low cost) sensors, transmit massive data, store it in the cloud and analyse it with Artificial Intelligence (AI). The opportunity now is to have machines analysing machines.

Sensing conditions such as temperature, vibration, humidity etc is really just measuring, it is a value (at a point in time). When analysed by a human, context is added. Measure + context = meaning. For example, if a machine temperature is 50 degrees, is this good or bad? Well, it depends on the context, without context, it’s impossible to answer, we need to know what’s normal, from there we need to understand is this figure rising or falling, if so, how quickly? etc. (You get the idea.) At present it seems most IOT vendors are so focused on the measures, they miss the meaning. Decisions are made on meaning, not measures.

Unless you’ve have been hiding under a rock, you will note the massive predictions of billions of sensors being connected to the internet. The general consensus is that for every human (we now have 7B), there will be around 7 IOT devices (or ~50B). So who exactly is going to provide all of this meaning ? Well, unless we start to employ every man, woman and child …

So the question remains ? At MOVUS, we’ve thought a great deal about this and as a result we’ve developed an IOT Value Model. We see four key stages of value creation. Firstly Visibility (where is my asset?), Utilisation (is it operating or not?), Availability (how healthy is it?) and finally Life Cycle Cost (purchase price+maintenance cost+energy+disposal). Visibility and utilisation are fairly straight forward. However, these are the low hanging fruit, the real value is in availability and life cycle cost. No surprises, energy is typically 50-60% and maintenance is 25-40% of the costs of a machine. This is where it’s gets interesting. Imagine when purchasing your new pump, if you knew the meantime to failure for that pump (measured not estimate), or you knew the expected failure modes or you could compare the total life cycle costs (purchase price, average energy costs, average maintenance costs and disposal costs) between makes and models? Would purchase price be so important anymore?

Maintenance practices have largely remained the same for decades. Simplified, run until it breaks (then repair/replace), inspect periodically (repair/replace), replace ahead of expected failure and for a small amount of cases (<5%), put a expensive array of sensors to capture every detail about the machine. The first three cases require humans, the last, uses lots of instrumentation. So where does IOT come in?

If we are to achieve the value of the IOT revolution, then mankind cannot be the bottleneck, in providing meaning to measure. In achieving the real power and value of the IOT, we need artificial intelligence systems that analyse, predict and ideally learn. At MOVUS we’re continuously building such device (the FitMachine – yes we have the trademark – sorry Fitbit, burn!). With our device installed, technicians don’t climb on rooftops or down pipes filled with sewerage (nasty!) just to inspect machinery.

The real value of IOT isn’t in the measuring, it is in the ability to make more informed decisions. For value to be achieved then decisions need to be made. To reduce the total cost of your assets then I believe AI is the only way forward if we are to adopt these technologies on a global scale. The benefits that flow will be improved safety, reduced risk, reduced cost and our machines will be operating longer. Oh!, and the most important benefit, people who feel empowered with better information to make far more informed decisions (which they didn’t have to climb down a sewer pipe to get). 🙂

Brad Parsons is CEO and Founder of MOVUS, are building the FitMachine – ‘A Fitbit for Industrial Machines’. Find more information at

*FitMachine is a trademark of MOVUS ** Fitbit is a trademark of


This article was originally posted on LinkedIn on 31 January 2017.