Tsu-Tian Lee

Embedded Driver-Assistance System Using Multiple Sensors for Safe Overtaking Maneuver

Advanced driver-assistance systems have recently become one of the most active topics related to intelligent vehicles. Such assistance facilitates vehicular operation by allowing drivers increased control and an enhanced driving experience, and it even comes in the form of automated assistance for autonomous vehicle operation. This paper presents a driver-assistance system that uses a low-cost embedded digital signal processor, with the overall system installed in a commercial vehicle. Based on driving information supplied by multiple sensors, such as a real-time vision system, a vehicle-to-vehicle communication system, and in-vehicle sensors, the proposed system can facilitate decision making and the performing of driving tasks while executing overtaking maneuvers. This paper developed a data fusion stage based on a collision warning algorithm in which the overtaken vehicle and other vehicles in the neighboring lane are accounted for to avoid collisions. The system employs fuzzy control in the steering and speed automation to emulate the driving tasks performed by humans. The applicability of the proposed system was examined in a real-road environment, and a set of experimental results demonstrate the feasibility of using the involved coordination strategies while conducting various driving maneuvers.

Real-time eye detection and event identification for human-computer interactive control for driver assistance

Eye movements can provide important information for human-computer interactive applications. Due to the progress of computer technology, the detecting accuracy and speed of pattern recognition are promoted. Additionally, according to research advances in embedded systems, the applications of digital cameras, such as internet cameras, smart phones and smart TV, and smart cars, are widely used in nowadays. Therefore, we propose a set of real-time human-eye detection and tracking systems with human-computer interaction applications. This technique can obtain eye movements and can be adopted as interactive control commands on driver assistance systems. The proposed system is implemented on an OMAP4430 for embedded applications, and experimental results show that the proposed architecture is capable of effective and real-time eye position detection and event identification for human-computer interactive applications on driver assistance systems.

Intuitive IoT-based H2U healthcare system for elderly people

The development on newer healthcare services for the elderly citizens has become an immediate necessity today. There have been distinctive health challenges focused in the society through technical innovations. Most of the elderly people today experiences loneliness and psychological depressions, either as a result of living alone/ abandonment or due to reduced connection with their children and relatives. To enhance the quality of services in the elderly healthcare system we have developed a ubiquitous intuitive IoT-based (Internet of Things) Help to You (H2U) healthcare system to integrate various technologies of wearable devices, biosensors and wireless sensor networks in order to provide an intensive service management platform. This method would support the real time activity and monitor the healthcare system for the elderly citizens. In this method the information collected by various wearable devices in real time are stored in the central database which thereby connects people, doctors, and practitioner at the time of an emergency for the right information. This way the system could increase accessibility, efficiency, and also lower the health expenses to improve the comfort and safety as well as management of daily routines of an elderly life.

Using voice and gesture to control living space for the elderly people

To elevate the imperativeness and reinforce the fitness of elders, assisting a home care system can be an admittance that provides comprehensive nursing and monitoring them in the regular interim. In order to provide an interactive service management platform to the elders a smart environment of numerous sensors are clubbed together to establish an intuitive platform that can control the home appliances and gadgets within the living space of elders. The proposed system used voice and gesture to control the home appliances like turning on/off the light, closing/opening of curtains, TV, and fan or AC within the living spaces. The system also supports the real-time activity and monitor the healthcare system for the elderly citizens like heart rate and body temperature. In the case of emergency, for instance, anomalous behaviors like heart stroke occur, the proposed system set-up triggers an alarm and the emergency bulb will be on to alert to their kin. This smart environment can set the temperature and help control the living parameters of light based on the users comfort and their health conditions. The whole design is to provide modest support systems for the elder to live healthily and safety in the independent living of elders.

Structure From Motion Technique for Scene Detection Using Autonomous Drone Navigation

A method is presented for scene detection and estimation using high-resolution imagery acquired through autonomous drone navigation aided with landmark detection and recognition. The proposed system comprises a drone platform that facilitates efficient autonomous flight; it can capture images and provide real-time video streaming of the ground cover using a camera equipped with a 14-megapixel CMOS sensor and a fish-eye lens. In addition, landmark detection and recognition was performed by applying the histogram of oriented gradients and linear support vector machine methods on each frame of the video stream. The high spatial resolution of the acquired drone images makes the detection and interpretation of environments less complicated. First, through image processing, orthomosaic images and 3-D environment reconstruction (point clouds) of the scene are generated from a set of drone images by using an automatic photogrammetric technique called “structure from motion.” Subsequently, an unsupervised classification method is used to detect and differentiate environmental classes (scene interpretation) in the target or investigated area by using the high-resolution images. Finally, the results of the proposed method are evaluated by comparing them against ground-truth points.

Early detection of driver drowsiness by WPT and FLFNN models

This paper presents a method that can detect drivers drowsiness by using the wavelet packet transform (WPT) and functional link-based fuzzy neural network (FLFNN) models. Drowsy drivers have been reported to be vulnerable to car accidents. Early detection of drowsiness can help alert drivers or passengers to provide a safety drive on the road. For those old models or cars without equipped with advanced high technologies, there is a dire need to install sensor devices that can effectively detect drowsy status of drivers at an early stage. Photoplethysmography (PPG) is a non-invasive optical technique that measures relative blood volume changes in the blood vessels and has been universally used for research and physiological study. We develop such PPG sensor devices to be installed on the steering wheel to detect the physiological conditions (such as normal to drowsy) by using parameters extracted from the heart rate variability (HRV) obtained from PPG signal calculation. Experimental results revealed that the proposed model is effective in assessing the drowsy levels of drivers.

Design and realization of a knowledge-based framework for personalized home healthcare systems

This paper proposes an integrated knowledge-based framework to design an intelligent personalized home healthcare system. To support numerous healthcare tasks according to individuals with many personalized services, this system integrates an efficient rule-based inference mechanism and flexible knowledge rules for determining efficiently and rapidly the necessary physiological and medication treatment procedures. Based on several key techniques realization and integration, the proposed system can support the extensible, customizable, and configurable demands of the ubiquitous healthcare systems to meet the different demands of patients and caregivers under various rehabilitation and nursing conditions. Finally, our experimental evaluations show the feasibility and validness of human-system interaction in a home testing environment.

Development of hand-cleaning service-oriented autonomous navigation robot

This paper proposes the development of an autonomous navigation robot with hand-cleaning service in indoor environments. To navigate in unknown environments and provide service, the robot is with several intelligent behaviors including wall-following, obstacle avoidance, autonomous navigation, and human detection. A laser-sensor-based approach is used in the wall-following and obstacle avoidance behavior controllers. A preliminary map-matching algorithm is applied in the localization strategy of autonomous navigation in which the robot can acquire the current location and then move toward to the target position. In this study a hand-cleaning mechanism is embedded into the robot and the service will activate while a human is recognized within the designated range. The overall robotic system is carried out using a two-wheeled driving mobile robot with LabVIEW as an integration tool. The experimental results demonstrate the practicable application of the proposed approach.