Consumer IoT has shown enormous growth in recent years, either by becoming connected –
for example, speed sensors on a bike – or in other instances, rapid deployment across the
IoT application development requires many, disparate technologies. IoT solutions are
typically composed of a complex, heterogeneous mix of IoT endpoints, platforms, back-end
systems and data (e.g. sensors, actuators, processors, embedded software, local and long-
range connectivity, middleware, apps, analytics, machine learning, etc.).
There are countless use cases where IoT can be deployed, such as in manufacturing, vehicles
and even future cases such as smart cities and energy.
Manufacturing, as an example, has been operating shop floor equipment for decades with
sensors that control machine processes, but these sensors have relatively limited functionality
as compared to IOT devices. In addition, building IOT applications requires scarce, hard-to-
find specialist skills. Developers must not only be versed in their organization’s IoT platform
and its underlying services but also understand the big data and machine learning
technologies required to make sense of real-time data streams.
IoT today, represents uncharted territory, developers must collaborate with the business to
experiment with new ideas and bring new solutions to market through rapid iteration.
All this results in a lot of time and effort to build IoT applications. On top of that, the
accelerating pace of change is making it hard for enterprise IT teams to keep up with new
capabilities and advancements.
The WEM platform is the fastest and easiest way to build IoT software and applications. The
IoT app platform’s visual, model-driven approach enables both pro and less technical
developers to consume IoT services from best-in-class IoT platforms.
Through this platform-agnostic strategy, WEM enables organizations to build rich
experiences on top of connected devices to transform their operations, products and business