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Abstract
Physics-based simulation (PBS) is now widely utilized to maximize the usage of real-time sensory information in surveillance applications. Since agent-based simulation (ABS) helps in analyzing human behaviors under different scenarios, the combination of PBS and ABS can provide a better situational awareness capability by considering both the sensory inputs and human decisions. Furthermore, advances in sensory detection and tracking technologies allow for real-time planning and control of the surveillance system in the broader area. This paper aims to devise an optimal planning and control policy for surveillance systems, which will process different types of sensory data including videos, seismic data, as well as behavior models. To consider different scenarios in the surveillance area, we formulate this problem as a Markov Decision Process (MDP) by utilizing various sensory data for parameter selection. We then develop a Digital Twin (DT) of the surveillance using both PBS and ABS to calibrate and validate our proposed MDP framework. The resulting multi-paradigm simulation framework with DT can be an attractive approach to handle uncertainties in a system caused by the heterogeneity and velocity of the sensory data.
Keywords
Physics-based simulation, Agent-based simulation, Markov Decision Process, Digital Twins, Surveillance
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1.Introduction
The latest surveillance system using IoT smart city seeks to implement information and communication technologies to improve the efficiency, sustainability, and security of urban spaces while reducing costs and resource consumption [1]. Various types of sensors have been strategically deployed around urban landscapes to collect data pertaining to different types of environmental and societal factors of urban living. Along with modeling and simulations, these sensors are expected to form a smart surveillance system to collect, transmit, aggregate, and analyze the data, creating a data-rich environment. Such a data-rich environment provides governments and other local authorities additional means to extrapolate information about the challenges faced by cities in sectors such as crime prevention, traffic management, energy use, and waste reduction. This will help in facilitating effective policies for public services and provide a safer urban environment to its civilians.
The smart surveillance system proposed in this work consists of multiple interconnected surveillance units, including immobile units (e.g., camera), and moving units (e.g., drones) quipped with heterogeneous on-board sensors, different types of simulations (agent-based and physics-based),...