Fall detection is a major challenge in the public healthcare domain, especially for the elderly as the decline of their physical fitness, and timely and reliable surveillance is necessary to mitigate the negative effects of falls. This paper develops a novel fall detection system based on a wearable device. The system monitors the movements of human body, recognizes a fall from normal daily activities by an effective quaternion algorithm, and automatically sends request for help to the caregivers with the patient's location.
Abstract. The atmospheric effects, especially the ionosphere, are the key limiting factors for real-time high accuracy positioning using the network RTK technique with a medium-to-long-range baseline separation. To investigate suitable approaches to improve ionospheric modeling towards a real-time CMlevel positioning using the Victorian continuously operating reference stations network (i.e. GPSnet) system under various ionospheric conditions, this paper investigates both temporal and spatial variations of the ionospheric total electrons content (TEC) over Victoria through analysing GPS dual frequency data from the GPSnet over a period of two years. Diurnal and seasonal ionospheric variations, and winter anomaly of the ionosphere in Victoria are investigated based on GPSderived TEC values. Results suggest that the temporal and spatial TEC variations over Victoria are complicated. This complex nature of the ionosphere suggests that it is a challenging task to precisely represent the behaviours of the ionosphere if only a single and simple ionospheric model is used for all the time for RTK uses. It is therefore, necessary to develop new mathematical models or new procedures for precise representation of the ionospheric TEC variations in Victoria using a long period of GPS dual frequency observations, particularly the predictability of the ionosphere changes. It is expected that the new approach will provide a better guidance for the state-wide network-RTK solutions.
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