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The WiseNET ontology is the kernel of the WiseNET system. WiseNET is a semantic-based system that fuses heterogeneous sources of data such as data coming from sensors and the different contextual information. Due to the application of the paper (Panoptes building), we will focus in a specific type of sensor: smart cameras; however, the system is defined to include other type of sensors such as temperature, humidity, depth sensor, etc. The main goal of WiseNET is to improve classical computer vision and deep learning systems by considering the contextual information of the environment and by performing real-time reasoning. As a result, WiseNET may overcome some limitations of computer vision (e.g., false detections and missed detections), some drawbacks of deep learning (e.g., the need of large amount of training and testing data) and limitations of multi-camera based system (presented in Section 1) while allowing real-time event/anomalies detection and system reconfiguration.
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