Real time Analytics for the Internet of Things

Business Problem and Example Use Case

This use case focuses on using machine/senor generated data to monitor and proactively identify problems and send real-time alerts. Data from sensors and other connected devices can be used to proactively identify and prevent problems. KPI trends provide early warning signals of failure. Real-time monitoring of this data reduces downtime resulting in significant cost savings and improved productivity.

InfoSphere Streams receives data (variously called records, messages, events or tuples) from a wide variety of sources. The analytics that can be performed include filtering, correlation and summarization. These capabilities enable InfoSphere Stream applications to be considered Complex Event Processing (CEP) applications. With support of unstructured data types like audio and video, and its parallel and pipeline processing architecture for scale out, InfoSphere Streams as a platform extends beyond traditional CEP offerings. The InfoSphere Streams Log Analysis Benchmark includes a driver to emit simulated log messages and software to perform a set of nine CEP tests. Descriptions, code and results can be found at: https://www.ibm.com/developerworks/community/forums/html/topic?id=a1796cd1-5682-4829-b927-04e608598ae3.

Suggested Hacks

1. Where can we leverage sensor data or other IoT data sets to increase efficiency in governments and corporations?
2. A good source for IoT data - http://www.sense-os.nl/-/internet-of-things-public-sensor-feeds
3. Reference the “Mining in Microseconds” hack above for additional data sets.

The InfoSphere Streams Log Analysis Benchmark includes a driver to emit simulated log messages and software to perform a set of nine CEP tests. Descriptions, code and results can be found at: https://www.ibm.com/developerworks/community/forums/html/topic?id=a1796cd1-5682-4829-b927-04e608598ae3