Browsing by Author "Chiang, Ting-Hui"

Now showing 1 - 6 of 6

Appliance Control by TDoA-based Localization and Gesture Recognition
(2018-01-01)
Chiang, Ting-Hui
;
Chen, Yan-Ann
;
Chang, Chun-Ting
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
Smart home is one of the major Internet of Things (IoT) applications. When realizing a smart home, designing an intuitive interaction for appliance control has become a crucial issue. A control intention to an appliance comprises two main meanings, identification and control command. But, previous works seldom deliver these two meanings at the same time. To fully convey the control intention, this paper proposes a scheme of intuitive appliance control that tracks and recognizes hand moving trajectory and hand gestures respectively by exploiting acoustic information. We utilize a 3D positioning method based on time difference of arrival (TDoA) of acoustic signals to detect the trajectory of a hand movement for appliance identification and design a gesture recognition method by Doppler effect for control command. We validate the effectiveness of the proposed scheme via real-life experiments. The results show that average locating errors to the targets are 5.24 degrees and 10.35 degrees in the horizontal and vertical planes respectively and the accuracy of gesture recognition is 96.66%. Since human's eyesight is horizontal to the ground, locating an object in the vertical view is error-prone. We also provide a scroll gesture to assist the appliance selection.
Calorie Map: An Activity Intensity Monitoring System based on Wireless Signals
(2017-01-01)
Chiang, Ting-Hui
;
Chuang, Yi-Ta
;
Ke, Chia-Liang
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
Recently, elder care services, especially for those with chronic diseases, have become an important application in the field of IoT. Several studies have reported that the progress of chronic diseases can be slowed down effectively by moderate physical activities. In this paper, we propose an activity intensity monitoring system to support continuous monitoring of indoor calorie consumption. The system uses wireless signals to infer calorie burned in walking. In the proposed system, Bluetooth smart beacons are deployed in various spaces of a house. The elders who wear smart wristbands are continuously monitored for their locations by received wireless signals. The system has the following features. First, it utilizes wireless signals as location and activity intensity indicators; inertial sensors are only used in the training stage. Second, it is semi-training free and only needs relatively short training time to start using the monitoring services. Finally, the system is map-free, in the sense that it can be easily deployed without constructing the interior map of the house. A prototype system is implemented on a smartphone to evaluate the feasibility of the proposed system.
Continuous Human Location and Posture Tracking by Multiple Depth Sensors
(2014)
Qiu, Jun-Wei
;
Chiang, Ting-Hui
;
Lo, Chi Chung
;
Lin, Li-Min
;
Van, Lan-Da
This paper proposes a continuous location and skeletal tracking system using multiple RGB-Depth sensors (such as Kinects) deployed along a corridor with overlapping coverages. First, we transform the coordinates of all sensor into a unified coordinate. Second, the system recognizes users (such as patients under rehabilitation) from different views of these sensors and classifies them by their patient IDs. Third, the patient information can be continuously handed over among sensors when they move around the area. Experiment results show that the skeletal association during handover achieves approximately 90.61% in accuracy and 96.89% in precision in 44,817 experiment trials. By our observation, injured people possess asymmetric gait parameters especially on the ratio of the duration of the swing/stance phase. For example, the injured foot generally has a longer swinging duration than the healthy side. The proposed system has potential in patient rehabilitation monitoring applications.
IoT/M2M Wearable-based Activity-Calorie Monitoring and Analysis for Elders
(2017-01-01)
Soraya, Sabrina I.
;
Chiang, Ting-Hui
;
Chan, Guo-Jing
;
Su, Yi-Juan
;
Yi, Chih-Wei
With the growth of aging population, elder care service has become an important part of the service industry of Internet of Things. Activity monitoring is one of the most important services in the field of the elderly care service. In this paper, we proposed a wearable solution to provide an activity monitoring service on elders for caregivers. The system uses wireless signals to estimate calorie burned by the walking and localization. In addition, it also uses wireless motion sensors to recognize physical activity, such as drinking and restroom activity. Overall, the system can be divided into four parts: wearable device, gateway, cloud server, and caregiver's android application. The algorithms we proposed for drinking activity are Decision Tree (J48) and Random Forest (RF). While for restroom activity, we proposed supervised Reduced Error Pruning (REP) Tree and Variable Order Hidden Markov Model (VOHMM). We developed a prototype service Android app to provide a life log for the recording of the activity sequence which would be useful for the caregiver to monitor elder activity and its calorie consumption.
Sensor Calibration for Floor Detection by D2D Communications
(2017-01-01)
Chiang, Ting-Hui
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
Recent advances in technology have led to the rapid development of the Internet of Things (IoT) and the use of smartphones. The phenomenon has been widely influenced by the use of smart sensors, the accuracy of which is critical to the quality of service provided. Hence, it is vital that sensors are calibrated at both the device and software levels. Some applications even rely on environment-dependent sensing results. Floor detection by barometers is one example, where the pressure of a floor actually depends on the base reference pressure. This observation motivates us to study the floor detection problem by using barometers with device-to-device (D2D) communications. In this paper, we propose the Floor Calibration Protocol (FCP), which enables a mobile device to be calibrated with other mobile devices and anchor devices by considering both temporal and spatial factors. We conducted trace-based simulations to evaluate the proposed scheme and compared its performance with that of state-of-the-art approaches to validate the efficacy of our protocol.
Wireless Location Tracking by a Sensor-Assisted Particle Filter and Floor Plans in a 2.5-D Space
(2018-01-01)
Lo, Chi-Chung
;
Chiang, Ting-Hui
;
Lee, Tsu-Kuang
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
Indoor localization systems have attracted considerable attention recently. A lot of works have used wireless signals from existing base stations to track users' locations. The major challenge to such systems is the signal-drifting problem. A promising direction to conquer this problem is to fuse the tracked wireless signals with inertial sensing data. In this work, we consider location tracking in a multi-floor building, which we call a 2.5-D space, by taking wireless signals, inertial sensing data, and indoor floor plans of a 2.5-D space as inputs and building a SPF (sensor-assisted particle filter) model to fuse these data. Inertial sensors are to capture human mobility, while particles reflect our belief of the user's potential locations. Our work makes the following contributions. First, we propose a model to partition a 2.5-D space into multiple floors connected by stairs and elevators and further partition each floor, according to its floor plan, into logical units connected by passages. Second, based on the 2.5D space model, we then propose particle sampling and resampling mechanisms over the logical units using wireless signal strengths and inertial sensing data to adjust our beliefs of the user's potential locations. Third, to conquer the signal-drifting problem, we propose a weighting mechanism to control the distribution of particles based on user's activities of walking on grounds/stairs and taking elevators. A prototype has been developed and tested to verify the model and its accuracy.