There is more to discuss related to IoT asset management than simply keeping track of the physical location of each component. Some IoT devices can benefit from predictive analytics to help identify when an asset requires maintenance and also detect in real time when an asset has gone offline. By incorporating new data analytic techniques into an IoT ecosystem, organizations can benefit from these new capabilities and apply them to the IoT assets themselves.
When imaging a device such as an autonomous connected vehicle working on a construction site, or perhaps a robot on a manufacturing floor, the ability to predict failure becomes significant. Prediction is only the first step, however, as the IoT matures with new capabilities to automatically respond to failures and even autonomously swap out broken components for new replacements.
Consider a set of drones used in security and surveillance applications. Each drone is essentially an IoT endpoint that must be managed by the...