Time series data analysis of wireless sensor network measurements of temperature

Siddhartha Bhandari, Neil Bergmann*, Raja Jurdak, Branislav Kusy

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

24 Citations (Scopus)
103 Downloads (Pure)


Wireless sensor networks have gained significant traction in environmental signal monitoring and analysis. The cost or lifetime of the system typically depends on the frequency at which environmental phenomena are monitored. If sampling rates are reduced, energy is saved. Using empirical datasets collected from environmental monitoring sensor networks, this work performs time series analyses of measured temperature time series. Unlike previous works which have concentrated on suppressing the transmission of some data samples by time-series analysis but still maintaining high sampling rates, this work investigates reducing the sampling rate (and sensor wake up rate) and looks at the effects on accuracy. Results show that the sampling period of the sensor can be increased up to one hour while still allowing intermediate and future states to be estimated with interpolation RMSE less than 0.2C and forecasting RMSE less than 1C.

Original languageEnglish
Article number1221
Pages (from-to)1-16
Number of pages16
Issue number6
Publication statusPublished - Jun 2017
Externally publishedYes

Bibliographical note

Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.


  • Environmental monitoring
  • Forecasting
  • Interpolation
  • Temperature
  • Time series analysis
  • Wireless sensor networks


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