The continuing convergence of IoT with machine learning (ML) and Cloud computing is transforming what’s possible with many legacy products. The emergence of these technologies means minimal design changes are needed to enhance functionality. This is enabling greater product automation, advanced user interfaces (UI), access to insightful analytics, and more.
In many cases, these product enrichments can be achieved without significant investment. For example, by adding simple sensors or a camera, OEMs can now deploy sophisticated solutions such as predictive maintenance in an industry setting, or optimise production processes in manufacturing environments.
The business case for adding IoT functionality
The potential is certainly there for ambitious manufacturers that want to seize a competitive advantage and reap the commercial benefits.
For instance, it’s now possible to give users the option to add new features and services, via over-the-air (OTA) upgrades. This is allowing businesses to open up new after sales channels, introducing fresh revenue generating opportunities. By giving customers the ability to upgrade their products remotely, they can also enrich user experiences and build brand loyalty – which will, in turn, help to retain customers and futureproof product ranges.
That ability to upgrade products remotely also helps to reduce costs by minimising the resources required to maintain and update products – while also mitigating the risk of expensive product recalls.
The potential is so great that a failure to take advantage of IoT, ML and cloud-enabled solutions, could actually be a risk for manufacturers. Those that are slow to react could find themselves left with static, expensive-to-maintain devices. This could also open the door for new entrants to enter the market or allow other market players to raise the bar.
Turning concepts into reality
The business case is clear, but how simple is it, in reality, to add the solutions that enable these benefits? Is it really feasible to enable functionality, such as an advanced UI or product automation, with minimal investment?
The answer will, of course, depend on the scope of the ambitions. For example, an oven manufacturer that wants to improve functionality in order to increase the potential for customer engagement, could add a feature that would enable users to remotely monitor an oven bake on their phone. The manufacturer could then engage with users through the oven’s companion app.
In terms of the technical requirements for this feature, it would simply involve the installation of a robust, heat-resistant camera and Wi-Fi connectivity. Without much complexity, it would be possible to allow the user to adjust temperatures and timings, all through an app.
Imagine, however, that the manufacturer wanted to add a camera to enable automation instead – so it would be the oven that was detecting what was baking, discerning the progress and adjusting the temperature accordingly.
This would require the use of Computer Vision and ML – in order to detect changes to colour and structure. It would also need a more sophisticated camera – one equipped with depth perception and infrared capabilities.
Steps before deployment
The greater the level of complexity, the greater the costs tend to be. And, as these costs will ultimately need to be passed onto the customer, OEMs should assess market appetite first. Deployments must also be practically applicable, so manufacturers need to understand how new installations will impact their existing tech stack.
As with any product enhancement, it would make sense to conduct a feasibility study initially and develop a minimal viable product (MVP) to demonstrate proof of concept. These prototypes will allow manufacturers to quickly assess the practicalities and establish the true cost of enhancing existing products using emerging technologies. It could be that some innovations are found to be worth the investment, while it may pay to wait on others.
There’s no doubt, however, that the convergence of IoT, ML and Cloud computing is providing a great opportunity to reimagine what’s possible – and this is an exciting time for product designers and CTOs that are looking to enhance legacy models.
With many enhancements now within grasp, concerns around complexity shouldn’t stifle the imagination or stop manufacturers from testing what’s feasible when it comes to reinvigorating their products.
Mariusz Stolarski, global head of technology at Mobica, a Cognizant company
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