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OPTIMIZING URBAN MONITORING BETWEEN STATIONARY, OPPORTUNISTIC VEHICULAR, AND HYBRID SENSING

W. Hu,S. Winter,K. Khoshelham

Published 2022 in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences

ABSTRACT

Abstract. Urban monitoring based on wireless sensor networks is a recent paradigm that exploits a large number of low-cost sensors deployed in certain places or/and on mobile devices to collect data ubiquitously at a large scale. In this study, we explore and compare the coverage of stationary and opportunistic vehicular sensing methods with respect to the requirements of a task at hand. We distinguish spatial granularity, temporal granularity, and budget constraints. First we compare the spatio-temporal coverage of stationary sensing and opportunistic vehicular sensing for various tasks, which demonstrates that these two sensing methods are suitable for different tasks. Then we propose a hybrid sensing deployment framework integrating a genetic algorithm to achieve the maximum spatio-temporal coverage for specific tasks. Experiments with a real-world vehicle trajectory dataset demonstrate that the proposed hybrid sensing framework achieves the maximum spatio-temporal coverage in various tasks. Our results provide fundamental guidelines on network planning for urban monitoring applications.

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