Unifying IoT across the Digital Enterprise

Enterprises can decouple themselves from multiple vendor IoT platforms by implementing their own master IoT platform that captures sensor data from across the enterprise. Access to funding may be given a boost if IT teams can present senior management with enterprise-wide, business-driven use cases regardless of the number of data types and sources.

Moreover, a single data model can be used for data attributed across multiple vendors. For example, in the case of the two bulldozer suppliers, one vendor may use gallons for fuel levels and the other liters. Having a single data store allows data to be transformed on collection to the units used by the enterprise, creating an apples-to-apples comparison.

Further, companies in this position can achieve data consistency with the use of distributed computing. In a distributed model, IoT sensors are technically independent of the location where they report data. They can be programmed to report directly master IoT platform, the vendor’s platform, or both. In the latter case, cloud-to-cloud integrations are used to pull data from the source systems in nearly real time.

IoT sensors are programmed to send their data “home,” which most often means the cloud.[1] Although some device suppliers don’t have a platform, when they do, it is likely that customer data will be directed back to them. Alternatively, companies can work with their suppliers to update their device-sensor firmware to have them point data to the customer cloud platform rather than the vendor cloud platform. As another example, companies using cellular backhaul technology can purchase and manage their own SIM cards for their devices. These SIM cards can be programmed to send data back to the company cloud IOT platform. 

In both cases, data bypasses the vendor cloud all together. The main advantage here is access to real-time data directly from the devices themselves. It is important to bear in mind, however, that there are some drawbacks to this model, including the technical challenges of maintaining SIM cards and potential network costs without economies of scale.

For scenarios where device makers cannot change the destination of device data or where it is preferred to use the pre-installed sensors that report into their proprietary web cloud, cloud-to-cloud integrations are used to extract sensor data and stream it into the enterprise IoT platform on a regular basis. This model is quick to set up and easy to maintain. 

Cloud-to-cloud integrations are typically achieved with RESTful APIs. Calls are made to these APIs on a regular schedule to pull the latest IoT data for each device stored in the vendor’s cloud platform. Using the bulldozer example above, if the two vendors already have tightly integrated IoT sensors that report into their proprietary cloud platforms, the enterprise can periodically pull this data from each respective cloud, say every 15 minutes, to get the latest IoT data for each machine. IT teams can pick and choose select data elements to store in their platforms, clearing away copious amounts of unneeded data, which saves bandwidth and disk space.

1. Devices can also report into Edge computing devices. Edge computing is out of scope for this report.