Smart City Gnosys

Smart city article details

Title	'Where Am I?': Unraveling Challenges In Smart City Data Cleaning To Establish A Ground Truth Framework
ID_Doc	55
Authors	Asad S.; Powell B.; Long C.; Nicklas D.; Lagesse B.
Year	2024
Published	2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events, PerCom Workshops 2024
DOI	http://dx.doi.org/10.1109/PerComWorkshops59983.2024.10503068
Abstract	In the growing era of smart cities, data-driven decision-making is pivotal for urban planners and policymakers. Crowd-sourced data is a cost-effective means to collect this information, enabling more efficient urban management. However, ensuring data accuracy and establishing trustworthy 'Ground Truth' in smart city sensor data presents unique challenges. Our study contributes by documenting the intricacies and obstacles associated with overcoming MAC randomization, sensor unpredictability, unreliable signal strength, and Wi-Fi probing inconsistencies in smart city data cleaning. We establish a framework for three different types of experiments: Counting, Proximity, and Sensor Range. Our novel approach incorporates the spatial layout of the city, an aspect often overlooked. We propose a database structure and metrics to enhance reproducibility and trust in the system. By presenting our findings, we aim to facilitate a deeper understanding of the nuances involved in handling sensor data, ultimately paving the way for more accurate and meaningful data-driven decision-making in smart cities. © 2024 IEEE.
Author Keywords	counting people; MAC randomization; occupancy estimation; Wi-Fi probing

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