There are many definitions of the Internet of Things (IoT), some very technical. In simple terms it is where embedded sensors, processing, data analytics and wireless connectivity enable machine-to-machine communications. This enables one device to pass data and instructions to another for it to perform an action without any need for human intervention.
The term itself was first used in publications around 1999 although the principles and (wired) practical examples go back to Alan Turing's work in World War Two at Bletchley Park and arguably all the way back to the invention of the telegraph machine.
Whilst greatly ambitious there have been huge advancements made in developing a car that drives itself – to the point today where there is a race for many leading companies to have their car to be the first certified to be legally deployable on the road without a driver. You may well have seen or heard of the Google Smart car for example – a top technology company leading the way in the automotive world, really quite remarkable and showing how traditional business and IT markets have converged.
This is an incredibly sophisticated example of IoT where a large number of sensors work in combination with GPS and historical data to allow a car (or indeed any vehicle) to go from A to B by understanding where it is, what is around it and how it can safely get there in an efficient way.
Whilst these car designers are unsurprisingly having to overcome problems found in testing today, there is a very realistic expectation that they will be fit for real world use by as early as 2020. This has obvious benefits to us as consumers around convenience and safety although early adopters will need to be trusting and of a strong constitution (albeit there will be emergency manual overrides.)
The Internet of Things is also potentially supportive of supply side pull systems where a Kanban type message can be triggered and acted upon.
For many years there has been a concept of consignment stock managed by suppliers, particularly in the automotive and industrial business-to-business markets. Here the supplier stock is physically held on a key customer's site and the supplier takes responsibility for replenishment and self-billing. This works well but is often human resource intensive with the need for supplier reps to visit in order to check stock levels and count stock. Whilst EDI and the internet have helped to smooth this process it remains problematic.
The IoT can extend its reach beyond purchasing and delivering products into the aftermarket.
An expensive and critical piece of equipment can self-diagnose an issue, ideally before it becomes critical, and issue a message to a designated service company for that particular component. This would send the necessary information to the suppliers system which could trigger a service order which is scheduled directly to a service engineer, issue the parts and alerts him or her with all the information needed directly onto their handheld device or smartphone.
Or even more simply the thermostatic sensor in a freezer could send a message to the smartphone of an internal employee to alert them to a temperature too high or low. The person could then attempt to reset this direct or diagnose from the phone and take any other action necessary in super quick time. This would be invaluable in the medical, engineering, food, technology, industrial and energy marketplaces where key equipment down time is critical.
Big data analytics is the process of examining large data sets containing a variety of data types to uncover hidden trends and opportunities. This clearly applies to businesses who have adopted the IoT into its business processes and have significant databases of transactions that should be mined for competitive advantage, upsell and cross sell opportunities and customer service improvement.
The data could well indicate a critical piece of machinery that is consistently failing within the supply chain or one that you service for a customer. It could show one batch of component that is failing at many customers that you can track back to a particular supplier shipment. Or maybe a trend of buying patterns by a customer that otherwise would have gone unnoticed or indeed one who is incrementally moving their business elsewhere.
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