As I wrote recently, the Internet of Things (IoT) has been experiencing, at a minimum, some serious growing pains. This is particularly true for consumer IoT where a lot of old issues (interoperability) remain, while others (security) are becoming more concerning. With a few bright exceptions, many consumer IoT products solve first-world problems, often representing a marginal improvement over existing solutions.
But the IoT was always meant to be more ambitious and exciting than just the smart home, the factory or other discreet “single-player mode” use cases. The internet of things was always about networks, where connected objects could be tracked and activated across wide geographic areas, supply chains, health systems and other contexts representing trillions of dollars of economic value.
Rather than IoT, perhaps we should start using the expression “intelligent infrastructure” more frequently to describe those networks. With the parallel progress of machine learning at the edge, intelligent infrastructure will enable software-based intelligence to permeate the physical world, enabling real-time optimization and orchestration of connected “things” (objects, vehicles, machines, buildings), at a system level. Uber, Lyft and others give us perhaps the closest approximation what such networks could look like at scale, except that, in an intelligent infrastructure paradigm, such communications would be machine-to-machine, with no human in the loop.