Is it possible to supercharge products with minimal investment?

Historically, it would have been difficult for manufacturers to increase the potential of their products without significant design changes, and major investment. But, the convergence of the Internet of Things (IoT), Machine Learning (ML) and Cloud computing has made this possible.

This confluence of emerging technologies is allowing product developers and CTOs to deploy simple solutions that will enrich their products. With minimal design alterations, they can add functionality, such as advanced human machine interfaces (HMIs), greater computing intelligence and feature upgrades, while products are still in the field. 

This is providing numerous benefits, including:

• Increased revenue. If manufacturers can offer additional features, services and upgrades over-the-air, they can open up after sales opportunities and new income streams.
• Reduced costs. The ability to update devices remotely minimises the resources required to maintain and update products – and reduces the risk of costly recalls.
• Enhanced customer satisfaction. These simple solutions can improve product quality and provide enhancements, which will enrich the user experience, increase satisfaction and, ultimately, build brand loyalty.

Just how simple are simple solutions? 

In our latest industry paper we discuss seven of these simple solutions: camera detection; gesture-based user interface (UI); voice commands; Cloud processing; OTA updates; abstraction layers; and overpowered silicon. 

But, in reality, how easy is it to deploy these technologies? Can they really be implemented with minimal investment? The answer to this is that it depends what manufacturers want to achieve. 

For example, if an oven manufacturer wanted to provide users with the ability to remotely monitor a bake in progress, this could be achieved with minimal investment. They would simply need a robust camera, and consideration would also need to be given to the requirement of Wi-Fi connectivity and a companion app, but this would not add a huge amount of complexity. 

If the manufacturer wanted to add automation to the oven, however, by having the camera detect what was being baked, identifying when it was ready and adjusting the temperature accordingly – this would be entirely possible, but it would add layers of complexity. 

For instance, in order to detect changes to the state of the food, the manufacturer would need to incorporate Computer Vision and Machine Learning. The choice of camera would also need to include depth and infrared capabilities.

Making these enhancements would add cost but, when the competitive advantage gained is evaluated, it may well be worth it. Any solution needs to be both economically and practically applicable, which is why we often conduct a feasibility study and develop a Minimal Viable Product (MVP) for manufacturers, to provide them with a proof of concept. 

However, the starting point has to be whether these simple solutions could be implemented without the manufacturer needing to replace their entire stack or make major design changes. Ultimately, is there a way to deliver major product enhancements at a relatively low cost? 

So, if they are not already, manufacturers should be investigating whether simple solutions, such as those highlighted in our latest guide, could be added to their products. 

To learn more about the solutions mentioned in the Mobica guide, take a look at Seven simple solutions that are supercharging manufacturers’ products.