Automation is any technology that augments or replaces human capabilities in the workforce. Multiple technologies are needed to cover the entire spectrum of IoT solution development.

Automation acts as the invisible underlying glue that brings all the pieces together. Automation in data collection means automated pre-processing of raw IoT events and data’ automation in analytics means operationalizing the analytical models in production;  automation in value delivery means sharing insights across the organization by automating integrated data workflows between IoT and IT.

This eBook is for Application Developers, Enterprise Architects and Innovation Managers who are involved in building, packaging and commercializing IoT solutions.

  • PART I explains why you should be using a rules engine from the get-go rather than hard coding rules when implementing automation logic for IoT applications.
  • PART II defines a seven-point benchmark to help Enterprise Solution Architects to choose the right rules engine technology to match their IoT use case.
  • PART III evaluates eight most popular types of rules engines that can be used in the IoT domain against the benchmark defined in PART I, giving them a 0-100 score.