Relational-Based Sensor Data Cleansing

Nadeem Iftikhar, Xiufeng Liu, Finn Ebertsen Nordbjerg

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

    Abstract

    Today sensors are widely used in many monitoring applications. Due to some random environmental effects and/or sensing failures, the collected sensor data is typically noisy. Thus, it is critical to cleanse the sensor data before using it to answer queries or conduct data analysis. Popular data cleansing approaches, such as classification, prediction and moving average are not suited for embedded sensor devices, due to the limited storage and processing capabilities. In this paper, we propose a sensor data cleansing approach using the relational-based technologies, including constraints, triggers and granularity-based data aggregation. The proposed approach is simple but effective to cleanse different types of dirty data, including delayed data, incomplete data, incorrect data, duplicate data and missing data. We evaluate the proposed strategy to verify its efficiency, effectiveness and adaptability.
    Original languageEnglish
    Title of host publicationProceedings. 19th East-European Conference on Advances in Databases and Information Systems
    Number of pages14
    Publication date2015
    Publication statusPublished - 2015
    Event19th East-European Conference on Advances in Databases and Information Systems - Futuroscope, Poitiers, France
    Duration: 8 Sep 201511 Sep 2015
    Conference number: 19
    http://adbis2015.ensma.fr/index.html

    Conference

    Conference19th East-European Conference on Advances in Databases and Information Systems
    Number19
    LocationFuturoscope
    CountryFrance
    CityPoitiers
    Period08/09/201511/09/2015
    Internet address

    Keywords

    • Data cleansing
    • Sensor data
    • Relational-based
    • Simple
    • Effective

    Cite this

    Iftikhar, N., Liu, X., & Nordbjerg, F. E. (2015). Relational-Based Sensor Data Cleansing. In Proceedings. 19th East-European Conference on Advances in Databases and Information Systems