Enterprise IoT: turning connected devices into operational intelligence

IoT (Internet of Things) refers to a network of physical devices embedded with sensors, software, and connectivity that allows them to collect and exchange data over the internet or other networks. In an enterprise context, this typically means industrial equipment, fleet vehicles, or facility systems generating operational data.

IoT refers to the connected devices and the data they generate. Edge computing refers to processing that data locally, near the device, rather than sending all of it to the cloud. Most enterprise IoT deployments use edge computing for time-sensitive processing and cloud computing for aggregated analytics and storage.

Costs vary widely by scope: a connectivity pilot on a limited number of devices can range from tens of thousands of dollars, while a full multi-site deployment with predictive maintenance and edge computing typically ranges into the hundreds of thousands, depending on device count, connectivity type, and integration complexity.

A focused pilot deployment on a single site typically takes 6–12 weeks. A full multi-site rollout with edge computing, device management, and predictive analytics generally takes 4–9 months depending on device scale and existing infrastructure.

Predictive maintenance uses sensor data from equipment - vibration, temperature, pressure - analyzed by machine learning models to detect early signs of failure before it happens. IoT enables this by continuously collecting the sensor data needed to train and run those predictive models in near real time.