@inproceedings{7fda5574bc13474ea90aceb0d502db76,
title = "Integrating IoT-sensing and crowdsensing for privacy-preserving parking monitoring",
abstract = "Data sensing and gathering is essential for diverse information-driven services in smart cities. On the one hand, Internet of Things (IoT) sensors can be deployed at certain fixed locations to capture data reliably but suffering from limited sensing coverage. On the other hand, data can be gathered dynamically by crowdsensing contributed from voluntary users but suffering from its unreliability and the lack of incentives for users' contributions. In this paper, we explore an integrated paradigm called {"}hybrid sensing{"}that aims to harness both IoT-sensing and crowdsensing in a complementary and privacy-preserving manner. We implemented our hybrid sensing system and conducted some initial empirical evaluations.",
keywords = "IoT, crowdsensing, hybrid sensing, privacy protection, smart cities, smart parking system",
author = "Hanwei Zhu and Chau, {Sid Chi Kin}",
note = "Publisher Copyright: {\textcopyright} 2021 Owner/Author.; 8th ACM International Conference on Systems for Energy-Efficient Built Environments, BuildSys 2021 ; Conference date: 17-11-2021 Through 18-11-2021",
year = "2021",
month = nov,
day = "17",
doi = "10.1145/3486611.3492229",
language = "English",
series = "BuildSys 2021 - Proceedings of the 2021 ACM International Conference on Systems for Energy-Efficient Built Environments",
publisher = "Association for Computing Machinery, Inc",
pages = "226--227",
booktitle = "BuildSys 2021 - Proceedings of the 2021 ACM International Conference on Systems for Energy-Efficient Built Environments",
}