The future of IoT and machine learning – what role will humans play? - Industrial Internet Now

"What we are seeing today is that there typically exists a bit of a delay when companies start connecting assets and collecting information to be able to rely on machine learning algorithms and their accuracy," says Salminen. "The training of these algorithms requires large amounts of data and thus time. It takes time for any individual company to move through the cycle of starting with very basic use cases and moving onto more complex algorithms and dependencies, and eventually introducing machine learning." He recognizes companies that require warehouses – or those whose supply chains do – currently expect sophisticated IoT solutions from a production and manufacturing point of view. Salminen encourages companies who have examined the cost of IoT solutions for manufacturing or supply chain management over recent years to do so again. "Things are changing at such a pace that it is now very cost efficient even for smaller companies to deploy off-the-shelf IoT solutions for their supply chains as the price of hardware, connectivity and software has dramatically reduced over the last 5 years," he reasons.