In 1943, the CEO of IBM, Thomas Watson, predicted: “I think there is a world market for maybe five computers.” We’ve come a long way since that ill-fated comment and the next revolution (the next Industrial Revolution according to Forbes) is said to be the Internet of Things (IoT) – with Cisco predicting upwards of 50 billion devices and computers by 2020. That’s seven times more ‘smart things’ than there are people on the planet.
No doubt you’ve heard of the IoT – it seems hard to miss these days. In short, it won’t just be computers and mobiles that are connected, but office lights, industrial machines, cars, agricultural fields and local buses. Literally anything and everything. And that’s not omitting the explosion in ‘wearables’ such as smartwatches and other health gadgets.
The IoT will make new data available in ways we couldn’t imagine before; it will spur new markets and connect existing markets that previously had little overlap, further driving the need for applications that can make sense of the available data to extract meaningful results.
Automating this kind of information discovery will be huge, IDC forecasts a $7.1 trillion market by 2020; McKinsey suggest a more ‘reserved’ $6.2 trillion impact by 2025. When you see numbers like this you realise that something rather dramatic is afoot.
IoT in manufacturing a growth sector
IoT in manufacturing is widely tipped as one of the growth sectors. Indeed, big business has been instrumenting its expensive machines for years so that impending failures can be identified before they occur – various terms such as condition monitoring, asset management and health monitoring have been used. Such systems have been the key ingredient to running a pre-emptive maintenance campaign and decreasing unplanned downtime.
The problem with these earlier systems, though, has been the high cost, long deployment phases and inherent complexity that required an engineering team to interpret the data and decide on suitable actions. This has meant that smaller businesses or those in the ‘wrong’ sector have been simply locked out.
Moreover, those systems tend to be quite niche-oriented and offered limited scope in terms of being part of a more holistic approach involving inventory management, spares and logistics control, training, asset management and continuous improvement techniques.
Forcing down prices and democratising data access
This is where IoT is really exciting and can play a big role as it forces down prices and democratises data access, delivering a solution enterprise-wide. Fortune.com highlights that IoT could deliver maintenance savings of 25 per cent, reduce unplanned downtime by 50 per cent and extend the life of machinery by years. Gartner forecast 30 per cent Total Cost of Ownership (TCO) savings through the use of ‘smart’ technologies.
Coupled with advances in analytics and low-cost communications infrastructure, the time for providing sophisticated and affordable predictive IoT systems is now. There will always be a need for specialist prognostics systems but most will benefit from a ‘good enough’ cost-effective solution – think of the Pareto principle and how camera phones (once thought of as an impractical joke) have all but killed off sales of point and shoot compact cameras.
IoT does not sit in a technology silo, it demands organisational and business model changes. That alone will turn off large swathes of businesses. However, benefits will start becoming too overpowering to ignore and organisations will have no choice but to adopt or fail. Business will need to create their own Internet of Assets™.
Benefits of advanced predictive analytics
At Senseye, we’re developing a product to do just that, delivering the benefits of advanced predictive analytics to organisations that have previously considered it unaffordable or too difficult to implement and work with.
Senseye takes real-time data from IoT devices, machines and the environment and mines the data for complex patterns, trends and anomalies. This enables it to identify when a component is likely to wear and need replacing, when a machine has been used incorrectly and how production could be optimised. This is driven by innovations in machine learning, big data and artificial intelligence.
Delivering this technology to previously excluded organisations does have design implications. For one, an engineering department is unlikely to exist to interpret data and decide on what needs doing. This means that results are provided in plain English, direct to the user (even by text, if necessary) - no more hunting through graphs or Excel spreadsheets.
Senseye is currently running trials in three sectors: agriculture, solar and renewables and manufacturing. Contact us at
www.senseye.io if you’d like to joining these
trials and find out more.
Senseye is an easy-to-use, online tool that takes data you already have from equipment, sensors and the environment to provide forecasts that keep you one step ahead. Senseye was founded in early 2015 by a team who had previously worked on complex and costly predictive analytics systems; it works by exploiting patent-pending analytics technology to deliver fast business insights without the hard work and expense that other products demand. Contact them through their website www.senseye.io and follow them on Twitter @senseyeIO to learn more
Simon Kampa is the CEO of Senseye and an avid proponent of the Internet of Things and using remote sensor data for the benefit of businesses. Simon has a background in Computer Science and holds a PhD in Artificial Intelligence