Abstract
Eye contact represents a fundamental element of human social interactions, providing essential non-verbal signals. Traditionally, it has played a crucial role in fostering social bonds during in-person gatherings. However, in the realm of virtual and online meetings, the capacity for meaningful eye contact is often compromised by the limitations of the platforms we use. In response to this challenge, we present an application framework that leverages webcams to detect and share eye gaze attention among participants. Through the framework, we organized 13 group meetings involving a total of 43 participants. The results highlight that the inclusion of gaze attention can enrich interactive experiences and elevate engagement levels in online meetings. Additionally, our evaluation of two levels of gaze sharing schemes indicates that users predominantly favor viewing gaze attention directed toward themselves, as opposed to visualizing detailed attention, which tends to lead to distraction and information overload.
Enhancing Online Meeting Experience through Shared Gaze-Attention (fraunhofer.de)
A method and system for generating and managing virtual industrial devices in an industrial network is disclosed. The method includes capturing data packets associated with ongoing industrial communication between an industrial application and an industrial device. The method further includes segregating the captured data packets into one or more requests and one or more responses by analyzing the information included in the data packets. The method also includes storing one or more requests along with one or more responses for the ongoing industrial communication in memory. The method includes dynamically generating a virtual industrial device emulating the industrial device based on the stored one or more requests and the stored one or more responses. The method includes establishing a communication session between the generated virtual industrial device and the industrial application for performing one or more test operations on the generated virtual industrial device.
The intelligent HVAC system uses an artificial neural network to automatically control the heating, ventilation, and air conditioning conditions based on the number of occupants in an enclosure. It includes an occupant detection unit that determines the number of occupants and adjusts the HVAC settings accordingly. This system aims to enhance energy efficiency by adjusting the HVAC output in real-time based on occupancy. A control unit processes data from the sensors and manages the HVAC system to maintain the desired conditions inside the enclosure.
WO2017076433A1 - Intelligent heat, ventilation, and air conditioning system - Google Patents