Abstract
This research focuses on an ontology-based context-aware framework for providing services such as smart surveillance and intelligent traffic monitoring, which employ IoT technologies to ensure better quality of life in a smart city. An IoT network combines the working of Closed-circuit television (CCTV) cameras and various sensors to perform real-time computation for identifying threats, traffic conditions and other such situations with the help of valuable context information. This information is perceptual in nature and needs to be converted into higher-level abstractions that can further be used for reasoning to recognize situations. Semantic abstractions for perceptual inputs are possible with the use of a multimedia ontology which helps to define concepts, properties and structure of a possible environment. We have used Multimedia Web Ontology Language (MOWL) for semantic interpretation and handling inherent uncertainties in multimedia observations linked with the system. MOWL also allows for a dynamic modeling of real-time situations by employing Dynamic Bayesian networks (DBN), which suits the requirements of an intelligent IoT system. In this paper, we show the application of this framework in a smart surveillance system for traffic monitoring. Surveillance is enhanced by not only helping to analyze past events, but by predicting anomalous situations for which preventive actions can be taken. In our proposed approach, continuous video stream of data captured by CCTV cameras can be processed on-the-fly to give real-time alerts to security agencies. These alerts can be disseminated via e-mail, text messaging, on-screen and alarms not only to pedestrians and drivers in the locality but also the nearest police station and hospital in order to prevent and decrease the loss incurred by any event.
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Pahal, N., Goel, D., Chaudhury, S. (2019). Environment Monitoring System for Smart Cities Using Ontology. In: Ben Ahmed, M., Boudhir, A., Younes, A. (eds) Innovations in Smart Cities Applications Edition 2. SCA 2018. Lecture Notes in Intelligent Transportation and Infrastructure. Springer, Cham. https://doi.org/10.1007/978-3-030-11196-0_5
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DOI: https://doi.org/10.1007/978-3-030-11196-0_5
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