A Practical Framework To Turn IoT Technology Into Operational Capability
These assets or “ things ” typically have instrumentation or sensors that collect operational data and information . Plant transformation and orchestration capabilities to not only integrate but also process and transform the near real-time
Figure 2 - I2OC ( IoT to Operational Capability ) framework
historians or time-series databases are often used to aggregate this operational data . The framework can be adapted to cater to the specific infrastructure in an organization . The industrial assets and data sources represent the big data component where the raw data is collected and streamed or stored before it is integrated into a business use case or application .
An enhanced integration approach is central to the framework . The integration “ middleware ” acts as the centralized integration library that contains OT , IT and business application integration components . This middleware is enhanced with event stream processing ( ESP ), data data from the industrial assets before it is integrated into existing and new business workflows .
Gartner refers to this type of real-time integration and processing capability as Operations Intelligence platforms 14 that use standard adapters to read and write information from different devices , systems and applications . The level of processing capability differs among the different types of operations intelligence platforms , but it typically includes the ability to stream or poll data from real-time systems , perform some level of event stream processing and orchestration before integrating the processed data back into operations . This
14 https :// www . gartner . com / doc / 3540217 / market-guide-operations-intelligence-platforms
IIC Journal of Innovation - 37 -