| Title |
Where Am I?: Unraveling Challenges in Smart City Data Cleaning to Establish a Ground Truth Framework |
| ID_Doc |
38578 |
| Authors |
Asad, S; Powell, B; Long, C; Nicklas, D; Lagesse, B |
| Title |
Where Am I?: Unraveling Challenges in Smart City Data Cleaning to Establish a Ground Truth Framework |
| Year |
2024 |
| Published |
|
| DOI |
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. |
| Author Keywords |
counting people; occupancy estimation; MAC randomization; Wi-Fi probing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S) |
| EID |
WOS:001216220000138 |
| WoS Category |
Computer Science, Artificial Intelligence; Computer Science, Information Systems; Computer Science, Theory & Methods; Telecommunications |
| Research Area |
Computer Science; Telecommunications |
| PDF |
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