<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This study examines outlier detection in time-series sensor data from PurpleAir low-cost sensors in Athens, Greece. Focusing on key environmental parameters such as temperature, humidity, and particulate matter (PM) levels, the study utilizes the Interquartile Range (IQR) and Generalized Extreme Studentized Deviate (GESD) methods on hourly and daily basis. GESD detected more outliers than IQR, most of them in PM, while temperature and humidity data had fewer outliers; applying filters before outlier detection and adjusting alpha values based on time scales were crucial, and outliers significantly affected spatial interpolation, emphasizing the need for spatial statistics in smart city air quality management.</p>
</abstract>

This study examines outlier detection in time-series sensor data from PurpleAir low-cost sensors in Athens, Greece. Focusing on key environmental parameters such as temperature, humidity, and particulate matter (PM) levels, the study utilizes the Interquartile Range (IQR) and Generalized Extreme Studentized Deviate (GESD) methods on hourly and daily basis. GESD detected more outliers than IQR, most of them in PM, while temperature and humidity data had fewer outliers; applying filters before outlier detection and adjusting alpha values based on time scales were crucial, and outliers significantly affected spatial interpolation, emphasizing the need for spatial statistics in smart city air quality management.

Comparison of outlier detection approaches in a Smart Cities sensor data context

International Journal on Smart Sensing and Intelligent Systems

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

{"article-title":"Comparison of outlier detection approaches in a Smart Cities sensor data context"}

This study examines outlier detection in time-series sensor data from PurpleAir low-cost sensors in Athens, Greece. Focusing on key environmental parameters...

Comparison of outlier detection approaches in a Smart Cities sensor data context

Article Category: Research article

Publié en ligne: 14 févr. 2024

Pages: -

Reçu: 06 sept. 2023

DOI: https://doi.org/10.2478/ijssis-2024-0004

Mots clés
Outlier detection, smart cities, IoT, sensors, environmental data

© 2024 Sofia Zafeirelli et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Comparison of outlier detection approaches in a Smart Cities sensor data context

Article Category: Research article

Publié en ligne: 14 févr. 2024

Pages: -

Reçu: 06 sept. 2023

DOI: https://doi.org/10.2478/ijssis-2024-0004

Mots clésOutlier detection, smart cities, IoT, sensors, environmental data

© 2024 Sofia Zafeirelli et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Outlier detection, smart cities, IoT, sensors, environmental data