September 28, 2016 | Written by: Adrian Whitfield
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For many of us, the Internet of Things (IoT) is becoming a part of our lives. This may be in the form of a wearable device for you or your dog, perhaps a shiny connected car, or even a connected appliance such as a washing machine. These are all cool and interesting products that can provide a richer, more complete user experience compared with traditional, non-connected products.
Companies developing IoT solutions often collect data from connected products which are then used to develop new revenue streams by offering additional services on top of the product itself, or to improve the product in its next iteration.
IoT and product development
But can the IoT and its technologies be applied within the product development lifecycle itself to improve the way all products, whether connected or not, are developed? Let’s examine this question with an example:
All products must be tested thoroughly before they are released for sale with a variety of different types of testing performed at different development phases. With advances in engineering software some testing can be virtualised, but eventually the physical product will require “real world testing” to ensure it meets system requirements and operational needs. In the automotive industry, this means real vehicles must be tested on real roads.
For example, vehicles are tested in extreme hot and cold climates. They are tested on a variety of different road surfaces and conditions to ensure they don’t shake, rattle and roll. However, due to increasing product innovation and rising vehicle system complexity with smart infotainment systems, advanced driver assistance systems (ADAS) and autonomous driver systems, there is a need to perform ever more real world vehicle testing. Governments and industry regulators will demand it. This means more testers and engineers, more test vehicles and, of course, more cost to the manufacturer.
IoT can enable enriched testing
Such testing can be both time-consuming and logistically challenging. Test locations are often far from a manufacturer’s engineering facility. Both testing and results reporting processes may be manual and cumbersome, becoming even more challenging when problems are encountered and further investigations are required. For the engineering organisation, analysing test data out of context can be challenging, with no opportunity to access additional data unless a further test is designed and conducted.
Using an IoT approach, it is possible to streamline and simplify this process, which can both accelerate development and reduce testing costs. Test vehicles can utilise connected test equipment to collect data from the various vehicle systems and subsystems. Using an IoT platform (such as the Watson IoT Platform) the data can be collected and fed back in real time to the manufacturer’s engineering environment for analysis. It can be analysed for inconsistencies, corruption or out of range values. Actual results can be compared with expected results and, in the event of an issue, the platform can raise product defect reports and assign them to the correct engineer automatically. When product software updates are released, either to fix defects or add new features, the new software can be deployed to vehicles in remote testing environments via the network, further adding to efficiency.
Real time monitoring quantifies previously subjective testing measures
A particular benefit of introducing the IoT into vehicle testing is that it becomes easier to add and enrich testing capabilities. For example, a team testing a new infotainment system may wish to add real time video monitoring of facial expression to their testing efforts, to ensure that driver distraction is kept within industry regulatory guidelines. An IoT platform could be used to collect the video in real time and an analytics solution (such as IBM Intelligent Video Analytics) used to detect when driver distraction levels are no longer acceptable. Such an approach will not only help to improve the speed and efficiency of the testing process; the use of analytics can help provide a more quantified analysis of traditionally subjective parameters, such as driver distraction. This can help product engineering organizations move to a new optimum in the engineering “iron triangle” of quality, cost and time-to-market.
Curious to know more?
Whether you’re developing the next supercar or the next generation of connected appliance, perhaps now is the time to embrace the IoT in your product development lifecycle? Learn more about engineering for the IoT with IBM.