Integrating IoT-Sensing and Crowdsensing with Privacy: Privacy-Preserving Hybrid Sensing for Smart Cities

Abstract

Data sensing and gathering is an essential task for various 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 suffer from limited sensing coverage. On the other hand, data can also be gathered dynamically through crowdsensing contributed by voluntary users but suffer from its unreliability and the lack of incentives for users’ contributions. In this paper, we explore an integrated paradigm called “ hybrid sensing ” that harnesses both IoT-sensing and crowdsensing in a complementary manner. In hybrid sensing, users are incentivized to provide sensing data not covered by IoT sensors and provide crowdsourced feedback to assist in calibrating IoT-sensing. Their contributions will be rewarded with credits that can be redeemed to retrieve synthesized information from the hybrid system. In this paper, we develop a hybrid sensing system that supports explicit user privacy – IoT sensors are obscured physically to prevent capturing private user data, and users interact with a crowdsensing server via a privacy-preserving protocol to preserve their anonymity. A key application of our system is smart parking, by which users can inquire and find the available parking spaces in outdoor parking lots. We implemented our hybrid sensing system for smart parking and conducted extensive empirical evaluations. Finally, our hybrid sensing system can be potentially applied to other information-driven services in smart cities.

LoRaCELL-Driven IoT Smart Lighting Systems: Sustainability in Urban Infrastructure

“…Different researchers have provided innovative solutions to address these challenges [ 13 ]. For instance, Zhu et al [ 14 ] explored a hybrid sensing paradigm that combines IoT and crowd sensing. In this approach, users are incentivized to provide data not covered by IoT sensors and to offer feedback for calibrating IoT sensing.…”

“…LoRaCELL overcomes this by employing LoRa technology, independent of extensive cellular infrastructure, offering a more cost-effective and less complex solution. The integration of IoT-sensing and crowdsensing shown by Zhu et al [ 14 ] and Anand et al [ 15 ] could encounter issues in data precision and user involvement. Note that the device proposed in this work simplifies this process, ensuring efficient data transmission without the complexities associated with these approaches.…”

A Development of an IoT-Based Connected University System: Progress Report

“…The authors in [ 19 ] proposed privacy-preserving hybrid sensing for smart cities. They explored an integrated paradigm called “hybrid sensing” that harnesses both IoT-sensing and crowd-sensing in a complementary manner.…”