The Context-Aware Manager component supports workers’ safety and comfort by leveraging location information as well as media and gesture recognition data. The context-aware manager component includes three enabling modules, namely the Localization Manager, the Multiple-Media Manager and the Gesture & Content Recognition Manager. 1) Localization Manager: The Localization Manager (LM) component guarantees worker’s safety functionalities leveraging accurate positioning service and virtual fencing logics. The position information is estimated by UWB wearable devices. Furthermore, hybrid and cooperative approaches are used to get a more robust positioning service. The Localization Manager is able to generate geo-fencing events/alerts when a worker approaches a forbidden/dangerous area as well as data history related to localization data. This module supports Use Case (UC) applications regarding to the online recognition of workers activities, identification of worker’s and equipment’s location and monitoring and decision support of operations and maintenance procedures. Moreover, the LM supplies information to the SatisFactory knowledge-based so as to enable the platform services. 2) Multi-Media Manager: The Multiple-Media Manager is a component responsible for handling information concerning video streams. If necessary and required, the video can propagate contextual information as metadata embedded in the video streams. Privacy preservation is also in scope of this component, where required. 3) Gesture & Content Recognition Manager: The Gesture & Content Recognition Manager (GCRM) is devoted to the analysis of video streams (both RGB and depth) at the level of the Smart Assembly Station (SAS). It provides high level information that can be leveraged by other modules of the SatisFactory ecosystem to deliver advanced services for an effective support of workers. the GCRM can reliably identify the presence of workers in the SAS in conjunction with other relevant statistics. Services offered include a) Presence detection and people count, b) Safety gear detection (assessment if the worker is wearing safety equipment such as helmet, gloves and jacket), c) Fall detection and d) Gestures detection.
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