Abstract
Internet of Things (IoT) devices can collect diverse amount of data, which can be represented as timeseries data. Such data sent can be aggregated and again sent by intermediate parties. Often the properties of a data set are related to physical phenomena. It would be useful to take advantage of similarities and signal aggregations in order to reduce the size of data transfers. Presented herein are techniques through which multiple data measurements can be clustered together as a two-dimensional matrix. By clustering data measurements in such a manner, simple image processing techniques can be applied to the data such that the data can be transferred under an improved compressed form.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Vegas, Thomas and Karmakar, Anirban, "FREQUENCY ANALYSIS TO FACILITATE THE LIGHTWEIGHT TRANSFER OF TIMESERIES DATA", Technical Disclosure Commons, (April 20, 2022)
https://www.tdcommons.org/dpubs_series/5075