Tracing Data Origins in Smart Cities: An IoT Perspective

With the increasing number of connected Internet of Things (IoT), complex and diverse heterogeneous data are generated every second, and they face big data processing and security challenges. This study discusses the important role of data provenance in smart cities and IoT ecosystems. An important task solved by data provenance is tracking the entire lifecycle of the data: their creation, transmission, storage, and processing. This paper addresses the importance of data quality to ensure the trustworthiness of IoT applications. The review provides a comprehensive analysis of current IoT provenance methods and technologies, and we propose a taxonomy that classifies the key components of IoT data provenance systems in smart cities. The findings aim to assist researchers and practitioners in the development and implementation of effective data provenance strategies for smart city applications. Additionally, a case study on secure air quality monitoring demonstrates how provenance mechanisms can be implemented in a real-world IoT network.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3591277
Primary Topic
Big Data Technologies and Applications
Type
article
Field-Weighted Citation Impact
0.00
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article

Tracing Data Origins in Smart Cities: An IoT Perspective

Wael M. S. Yafooz, Basemah Alshemali, Ali Abd Almisreb, Binara Imankulova et al.
1 links
IEEE Access
Big Data Technologies and Applications
article

Tracing Data Origins in Smart Cities: An IoT Perspective

Wael M. S. Yafooz, Basemah Alshemali, Ali Abd Almisreb, Binara Imankulova, Abdulsamad Ebrahim Yahya, Kaznah Alshammari
article en

Abstract

With the increasing number of connected Internet of Things (IoT), complex and diverse heterogeneous data are generated every second, and they face big data processing and security challenges. This study discusses the important role of data provenance in smart cities and IoT ecosystems. An important task solved by data provenance is tracking the entire lifecycle of the data: their creation, transmission, storage, and processing. This paper addresses the importance of data quality to ensure the trustworthiness of IoT applications. The review provides a comprehensive analysis of current IoT provenance methods and technologies, and we propose a taxonomy that classifies the key components of IoT data provenance systems in smart cities. The findings aim to assist researchers and practitioners in the development and implementation of effective data provenance strategies for smart city applications. Additionally, a case study on secure air quality monitoring demonstrates how provenance mechanisms can be implemented in a real-world IoT network.

IEEE AccessVol. 13
Northern Border University (SA), International University of Sarajevo (BA), Taibah University (SA), International Information Technologies University (KZ)
Sustainable cities and communities
Openalex Percentile: Top 82%
Big Data Technologies and Applications
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Tracing Data Origins in Smart Cities: An IoT Perspective — Wael M. S. Yafooz, Basemah Alshemali, et al. · IEEE Access (2025) | TGRS Research Map | TGRS