There is tremendous interest from industrial enterprises to understand the nuances of the two most debated IoT data communications protocols: MQTT and LWM2M. MQTT and LWM2M are protocols that create a standard way to get device data to systems, platforms, applications, and other devices.Let’s talk a little about each protocol and when it’s best used in an enterprise IoT deployment.MQTT and when to use it
Message queuing telemetry transport (MQTT) is an ISO standard which describes a publish/subscribe (pub/sub) messaging protocol. Nearly all IoT platforms support MQTT communication, making it the de facto standard for device-to-platform IoT communication.To read this article in full, please click here
Almost every week we speak with an enterprise that is curious about building its own IoT application enablement platform (AEP) or IoT device management (DM) platform. The idea is straight-forward – an enterprise wants total control over the technology it deploys, so it chooses to hire developers to build the perfect, inexpensive platform.Then what happens? Sometimes everything goes exceedingly well and the IoT platform delivers as anticipated. Other times, the enterprise determines
it takes more time and money to build a platform that anticipated
it takes more staff to support the platform on-going than anticipated
it is very hard to keep the platform features up-to-date compared to the features offered from best-in-class vendors’ IoT platforms
the initial in-house platform was great, but scaling and modifying the platform to meet future requirements is exceedingly difficult due to the chosen platform architecture
So, what are the total enterprise costs of building an enterprise-grade IoT platform versus buying IoT platform services from a third-party AEP or DM vendor? It really depends on the IoT solution that the enterprise wants to deploy.To read this article in full, please click here
Everyone talks about the excitement of collecting reams of Internet of Things (IoT) data and performing Herculean statistical gyrations on them. IoT data management and analytics are very important: this is how we can accomplish predictive maintenance on factory assets, help robots interact better with humans, and get cars to drive themselves more safely than my 17 year old son behind the wheel.The wise know that IoT data management is relatively easy to implement, but successfully accomplishing IoT device management for heterogeneous devices in-bulk is like navigating your canoe past the sea monsters Scylla and Charybdis.What makes great IoT device management?To read this article in full, please click here
Steve Hilton