IIoT Starter Package: 2-Wk Proof of Concept


With the Industrial Internet of Things Starter Package, BearingPoint offers a quick- launch solution to connect machines to the cloud and visualize their condition in a central cloud dashboard.

Competition put pressure on operational cost. Condition monitoring helps to increase the transparency about the machine health status and to detect machine failures early. By increasing the machine availability and better steering of maintenance activities cost can significantly be reduced. Our clients shows that operation efficiency is a top priority. Even so mature solutions in the IoT are available, the complexity overwhelms our clients. Reducing the time to value helps our customer and BearingPoint to position us as experts in management and as well in technology consultants. The IIoT starter package provides the opportunity to claim ground early in the IoT consulting and in the maintenance business. Our solution consists of the following building blocks: A hardware box to easily connect machines to the cloud A vibration sensor to monitor machines A Cloud architecture with all necessary services (e.g., data pipeline including the IoT Hub, Data Lake Storage and DataBricks for data analytics) Machine health status dashboard Input form, based on "IoT swarm" to leverage the crowd intelligence of the shop floor Machine learning algorithm to predict unplanned down times

Consulting Service:

• Ready-to-use hardware installation and set up • Microsoft Azure cloud integration and configuration • Ready-to-use Microsoft Azure IoT Central Dashboard • Ready-to-use IIoT swarm intelligence forms • Workshops to define your individual IIoT roadmap

Azure Services:

-Routing of Sensor Data into Azure Data Lake via IoT Hub -Sensor Data Insertion over IoT Central -Data Visualization of Machine Condition via IoT Central Visualization Capabilities -Alert Message Storage in Data Lake Gen 2 -Storage Crowd Intelligence by BearingPoint SWARM in SQL Database -Visualization and Documentation of failures in Azure DEVOPS -Use of Azure Data Bricks to process Sensor Data to automatically detect down times -Storage of machine downtime events in Azure PostgreSQL database