Showing papers by "Daqing Zhang published in 2010"

Activity recognition on an accelerometer embedded mobile phone with varying positions and orientations

Abstract: This paper uses accelerometer-embedded mobile phones to monitor one's daily physical activities for sake of changing people's sedentary lifestyle. In contrast to the previous work of recognizing user's physical activities by using a single accelerometer-embedded device and placing it in a known position or fixed orientation, this paper intends to recognize the physical activities in the natural setting where the mobile phone's position and orientation are varying, depending on the position, material and size of the hosting pocket. By specifying 6 pocket positions, this paper develops a SVM based classifier to recognize 7 common physical activities. Based on 10-folder cross validation result on a 48.2 hour data set collected from 7 subjects, our solution outperforms Yang's solution and SHPF solution by 5-6%. By introducing an orientation insensitive sensor reading dimension, we boost the overall F-score from 91.5% to 93.1%. With known pocket position, the overall F-score increases to 94.8%.

Extracting social and community intelligence from digital footprints: an emerging research area

Abstract: As a result of the recent explosion of sensor-equipped mobile phone market, the phenomenal growth of Internet and social network users, and the large deployment of sensor network in public facilities, private buildings and outdoor environments, the "digital footprints" left by people while interacting with cyber-physical spaces are accumulating with an unprecedented breadth, depth and scale. The technology trend towards pervasive sensing and large-scale social and community computing is making "social and community intelligence (SCI)", a new research area take shape, that aims at mining the "digital footprints" to reveal the patterns of individual, group and societal behaviours. It is believed that the SCI technology has the potential to revolutionize the field of context-aware computing. The aim of this position paper is to identify this emerging research area, present the research background and some references to the relevant research fields, define the general system framework, predict some potential application areas, and propose some initial thoughts about the future research issues and challenges in social and community intelligence.

GeeAir: a universal multimodal remote control device for home appliances

Abstract: In this paper, we present a handheld device called GeeAir for remotely controlling home appliances via a mixed modality of speech, gesture, joystick, button, and light. This solution is superior to the existing universal remote controllers in that it can be used by the users with physical and vision impairments in a natural manner. By combining diverse interaction techniques in a single device, the GeeAir enables different user groups to control home appliances effectively, satisfying even the unmet needs of physically and vision-impaired users while maintaining high usability and reliability. The experiments demonstrate that the GeeAir prototype achieves prominent performance through standardizing a small set of verbal and gesture commands and introducing the feedback mechanisms.

The architecture design of a cross-domain context management system

Abstract: A new context management framework, which supports the interaction between different domain context managers, is proposed. Two different context producer-consumer patterns are defined to support context-aware applications. To deal with the mobile entity problem in cross-domain context sharing, a transparent query mechanism that enables applications to obtain context information about mobile entities from remote domains is presented. The capability of our framework is demonstrated through a user scenario.

Unobtrusive sleep posture detection for elder-care in smart home

Abstract: Quality of sleep is an important attribute of an elder's health state and its assessment is still a huge issue. The sleep posture is a significant feature to evaluate the quality of sleep, and how to detect elder's sleep posture is a key challenge in elder-care community. This paper proposes an unobtrusive sleep postures detection solution and introduces pressure sensor matrix to monitor the elder's sleep posture in bed. Based on the proposed sleep detection system, the processing methods of experimental data and the classification approaches for sleep posture detection are also discussed.

MagicPhone: pointing & interacting

Abstract: Mobile phones are becoming a kind of must-have portable devices for people. This video demonstrates a mobile phone that can sense what you are pointing to and can act as a physical ubiquitous interaction device in real world, called MagicPhone. If you want to interact with an appliance around you, you just simply point the MagicPhone to it and then operate. The MagicPhone uses both the built-in accelerometer and magnetometer to sense the pointing orientation. Using MagicPhone, you only need to point to a device and sliding your finger, to show a picture on a display, to send a document to a laptop, to share slides on a projector, and to print a photo. In addition, MagicPhone can control a selected device with accelerometer-based gestures, e.g. changing TV channels. It also can serve as a mouse to draw a picture or play clicking games.

Towards non-intrusive sleep pattern recognition in elder assistive environment

Abstract: Quality of sleep is an important attribute of an elder's health state and its assessment is still a challenge. The sleep pattern is a significant aspect to evaluate the quality of sleep, and how to recognize elder's sleep pattern is an important issue for elder-care community. With the pressure sensor matrix to monitor the elder's sleep behavior in bed, this paper presents an unobtrusive sleep postures detection and pattern recognition approaches. Based on the proposed sleep monitoring system, the processing methods of experimental data and the classification algorithms for sleep pattern recognition are also discussed.

GeeAir: Waving in the Air to Control Home Appliances

Abstract: This video is a demonstration of our previous work [5], where we presented a handheld mobile device Gee Air, a gesture-based universal controller for home appliances Combining the speech, gesture, joystick, button, and light, Gee Air allows the users to interact with the appliances via a multi-modal means The users can control varied home appliances just by waving the Gee Air in the air The design of Gee Air is better than the existing universal remote controllers in that it satisfies the requirement of different users group, eg physically disabled and vision-impaired users