Abstract

Smart systems which operate in Intelligent Environments (IE) are complex. They analyse the large volumes of various contextual data on-line and often in real time to obtain, autonomously and reliably, the required pro-activeness of a system which operates pervasively. We proposed both a development framework for context-aware systems and a context-based decision making scheme for the system of managing police interventions, focusing on providing support for police patrols in life threatening situations. This system, owing to the symultaneous collection of rich contextual information from many police officers, which constitute the mobile network, as well as the complex processes of contextual reasoning, takes automatic decisions on supporting officers in emergency. We implemented the initial, yet not trivial, simulations of the system behaviour within the whole city. The results obtained prove the feasibility of the framework.

Recommended Citation

Klimek, R. (2022). Police Interventions as a Context-aware System. A Case of a Contextual Data Modelling. In R. A. Buchmann, G. C. Silaghi, D. Bufnea, V. Niculescu, G. Czibula, C. Barry, M. Lang, H. Linger, & C. Schneider (Eds.), Information Systems Development: Artificial Intelligence for Information Systems Development and Operations (ISD2022 Proceedings). Cluj-Napoca, Romania: Risoprint. ISBN: 978-973-53-2917-4. https://doi.org/10.62036/ISD.2022.34

Paper Type

Full Paper

DOI

10.62036/ISD.2022.34

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Police Interventions as a Context-aware System. A Case of a Contextual Data Modelling

Smart systems which operate in Intelligent Environments (IE) are complex. They analyse the large volumes of various contextual data on-line and often in real time to obtain, autonomously and reliably, the required pro-activeness of a system which operates pervasively. We proposed both a development framework for context-aware systems and a context-based decision making scheme for the system of managing police interventions, focusing on providing support for police patrols in life threatening situations. This system, owing to the symultaneous collection of rich contextual information from many police officers, which constitute the mobile network, as well as the complex processes of contextual reasoning, takes automatic decisions on supporting officers in emergency. We implemented the initial, yet not trivial, simulations of the system behaviour within the whole city. The results obtained prove the feasibility of the framework.