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Pre-processing and data-cleansing of energydata in the IoT

Type: Master's Assignment
Programme: Embedded Systems, Computer Science or Mathematics
Contact: Johann Hurink


The company ICT has developed the Smart Energy Service Platform (SESP), which is used to collect energy related data from households and offices and to apply demand response. ICT's SESP consists of an embedded gateway. The gateway is connect to the cloud, where further processing is done. The data is obtained from multiple different systems using different channels, e.g., a pulse counter. For further analysis, control and optimization it is of the utmost importance that data is correctly combined and that errors are correct, or at least detected, early on in the process. In the assignment the goal is to find a suitable, generic framework for pre-processing and data-cleansing to be used inside the SESP. In particular the challenges lie with determining where in the pipeline to apply the various techniques available. Examples of such techniques are re-sampling, sample rate conversion, filtering, conditioning, and error-detection and error-handling.

Concrete goals within the project are:

  • A literature study on the available algorithms
  • Definition of the algorithms to be aplied
  • Implementation of the algorithms within the SESP
  • Field test and result analysis

The project is in combination with the company ICT which has offices in both Deventer and Groningen. You will be supervised by some from ICT as well as a faculty member of the UT.