Internet of Things - Data Analytics in Industrial Networks
Written by: Dewire Labs Team
September 12, 2016
Currently, large amounts of data from numerous sensors stream rapidly into interconnected IT systems for processing and storage. Gartner project that the 0.9 billion sensors and 1.6 billion personal devices that were connected via the Internet in 2009 will become up to 75 billion devices in 2020, constituting the Internet of Things.
Process industries can significantly benefit from the distributed data availability in both, productivity and energy efficiency, if the knowledge that is hidden within the diverse and rapidly growing data can be mined and can be appropriately applied to the business. To make a case, imagine smart grids that base their decisions on live data from smart meters and sensors on machines or vehicles which can lead to a substantially more efficient use of energy.
Unlike today’s "big-data" analysis systems which are commonly operating on manually preprocessed empirical data, the data analysis systems for the Internet of Things have to address some unique challenges. The continuous big-data analysis has to be scalable to support millions or even billions of sensors and still provide real time guarantees. Moreover, the system is required to be highly secure, for instance with respect to privacy. No existing system can so far satisfy those requirements as of today.
Within the context of the project, we will focus on researching and developing data analysis systems for large-scale networks of sensors. Our plan is to find solutions which can dramatically increase the data handling capability for industry by developing a new data mining algorithm and integrating the data analysis with an Internet of Things platform.
- How can relations among attributes be revealed on live sensor data and the causal factors are reduced to ensure a correct and feasible live data analysis?
- How is it possible to leverage distribution techniques in order to decentralize the analysis on large scale industry networks?