Abstract:
Disclosed herein is an interaction monitoring system, comprising an environment collection module, interaction monitoring module, interaction segmentation module, and display module. The environment collection module detects surrounding environment and generates a data stream. The interaction monitoring module generates a feature data stream by extracting feature value of the data stream. The interaction segmentation module determines a target situation, which indicates a user's state or condition, from the feature data stream and generates a target image or video stream, which indicates the target situation. The display module displays the target image. Other embodiments are described and shown.
Abstract:
Disclosed herein is an accurate and efficient, yet non-obtrusive system and method (using same) for detecting interpersonal touch, such as a high-five, which is prevalent in people's daily lives, so as to promote everyday interactions at diverse settings. Based on ubiquitous computing technology, one embodiment of the system for detecting interpersonal touch comprises a pre-motion filter for filtering a pre-motion prior to the interpersonal touch, a sensor for sensing electrical properties of skin, an evaluator for analyzing and determining the interpersonal touch based on the pre-motion and the electrical properties of skin, and a communicator for communicating information analyzed by the evaluator. Other embodiments are described and shown.
Abstract:
A mobile apparatus includes a cooperator detector, a cooperation planner and a cooperation processor. The cooperator detector selects a cooperating mobile apparatus among adjacent mobile apparatuses. The cooperation planner determines a cooperation plan for operating cooperative context monitoring with the cooperating mobile apparatus. The cooperation processor operates the context monitoring based on the cooperation plan. Accordingly, the resource may be efficiently used and the range of the context monitoring may be enlarged.
Abstract:
Disclosed herein is a communication device, which comprises a user trace manager, a power emulator, and a power impact estimator. The user trace manager manages a user's sensor usage trace and device usage trace, which shows the user's mobile device usage pattern. The power emulator executes an executable file of the mobile application to generate hardware usage statistics based on the sensor usage trace and the device usage trace. And the power impact estimator computes an increase in power consumption of the mobile application based on the hardware usage statistics.
Abstract:
Disclosed herein is an accurate and efficient, yet non-obtrusive system and method (using same) for detecting interpersonal touch, such as a high-five, which is prevalent in people's daily lives, so as to promote everyday interactions at diverse settings. Based on ubiquitous computing technology, one embodiment of the system for detecting interpersonal touch comprises a pre-motion filter for filtering a pre-motion prior to the interpersonal touch, a sensor for sensing electrical properties of skin, an evaluator for analyzing and determining the interpersonal touch based on the pre-motion and the electrical properties of skin, and a communicator for communicating information analyzed by the evaluator. Other embodiments are described and shown.
Abstract:
Disclosed herein is a mobile face-to-face interaction monitoring device and method using the same and system including the same, for supporting accurate and efficient turn monitoring. One embodiment of the mobile face-to-face interaction monitoring device may comprise a conversation group detector for scanning mobile devices in a surrounding area and setting a conversation group, a turn detector for determining (conversational) turn using volume topography created based on sound signals detected in the mobile devices in the conversation group, and a meta-linguistic information processor for extracting meta-linguistic context of participants or interactants in the conversation group based on the turn. Other embodiments are described and shown.
Abstract:
A mobile apparatus includes a cooperator detector, a cooperation planner and a context processor. The cooperator detector selects a cooperating mobile apparatus among adjacent mobile apparatuses. The cooperation planner determines a cooperation plan for operating cooperative context monitoring with the cooperating mobile apparatus. The context processor operates the context monitoring based on the cooperation plan. Accordingly, the resource may be efficiently used and the range of the context monitoring may be enlarged.
Abstract:
Disclosed herein is a mobile face-to-face interaction monitoring device and method using the same and system including the same, for supporting accurate and efficient turn monitoring. One embodiment of the mobile face-to-face interaction monitoring device may comprise a conversation group detector for scanning mobile devices in a surrounding area and setting a conversation group, a turn detector for determining (conversational) turn using volume topography created based on sound signals detected in the mobile devices in the conversation group, and a meta-linguistic information processor for extracting meta-linguistic context of participants or interactants in the conversation group based on the turn. Other embodiments are described and shown.
Abstract:
Disclosed herein is a system for social control and use of an Internet of Things (IoT) device, comprising an actuator, one or more mobile devices, and a control server. The actuator is arranged or disposed in a public or common space. The one or more mobile devices comprises a social control user interface (UI), which includes a voting function. The control server comprises a preference aggregation engine for deriving a consensus by aggregating vote(d) values from the one or more mobile devices, and a device control command generating unit for generating a device control command based on the consensus. Other embodiments are described and shown.
Abstract:
Disclosed herein is a communication device, which comprises a user trace manager, a power emulator, and a power impact estimator. The user trace manager manages a user's sensor usage trace and device usage trace, which shows the user's mobile device usage pattern. The power emulator executes an executable file of the mobile application to generate hardware usage statistics based on the sensor usage trace and the device usage trace. And the power impact estimator computes an increase in power consumption of the mobile application based on the hardware usage statistics.