Combined Sensor–Sensorless Control of PMDC Motor for HD Camera of Unmanned Monitoring System

2019 ◽  
Vol 15 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Dong-Hee Lee
Keyword(s):  
Monitoring System ◽  
Sensorless Control ◽  
Combined Sensor

scholarly journals Combining low sampling frequency smartphone sensors and video for a Wearable Mobility Monitoring System

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 170
Author(s):  
Hui-Hsien Wu ◽  
Edward Lemaire ◽  
Natalie Baddour
Keyword(s):  
Monitoring System ◽  
Contextual Information ◽  
Sampling Rate ◽  
False Positives ◽  
Video Data ◽  
Consecutive Series ◽  
Accelerometer Data ◽  
Walking Activity ◽  
Outdoor Walking ◽  
Combined Sensor

A proof-of-concept Wearable Mobility Monitoring System (WMMS) was developed to identify daily activities and provide environmental context, using integrated BlackBerry Smartphone low sensor and video data. Integrated accelerometer data were used to identify mobility changes-of-state (CoS) in real-time, trigger BlackBerry video capture at each CoS, and save activity outcomes on the Smartphone. System evaluation involved collecting WMMS output and (separate) camcorder video under realistic conditions for five able-bodied subjects.  The subjects each performed a consecutive series of mobility tasks; including, walking, sitting, lying, stairs, ramps, elevator, bathroom activities, kitchen activities, dining activities and outdoor walking. Activity, timing and contextual information were obtained from the camcorder for comparison. Sensitivity results for sensor-based CoS identification were 97-100% for standing, sitting, lying and taking an elevator; 67-73% for walking-related CoS (stairs, ramps); 40-93% between walking and small movements (brushing teeth, etc.); and below 27% for daily living activities. False positives occurred in less than 12% of all activities, with less than 5% false positives for half the measures. Better classification results were achieved when using both acceleration features and Smartphone integrated video for all activities except sitting. The evaluation demonstrated that the WMMS algorithm and BlackBerry platform were effective for detecting mobility activities, even with low sampling rate sensors. The combined sensor and video analysis enhanced mobility task identification and contextual information.

scholarly journals Combining low sampling frequency smartphone sensors and video for a Wearable Mobility Monitoring System

F1000Research ◽  
2015 ◽  
Vol 3 ◽  
pp. 170
Author(s):  
Hui-Hsien Wu ◽  
Edward Lemaire ◽  
Natalie Baddour
Keyword(s):  
Monitoring System ◽  
Contextual Information ◽  
Sampling Rate ◽  
False Positives ◽  
Video Data ◽  
Consecutive Series ◽  
Accelerometer Data ◽  
Walking Activity ◽  
Outdoor Walking ◽  
Combined Sensor

A proof-of-concept Wearable Mobility Monitoring System (WMMS) was developed to identify daily activities and provide environmental context, using integrated BlackBerry Smartphone low sensor and video data. Integrated accelerometer data were used to identify mobility changes-of-state (CoS) in real-time, trigger BlackBerry video capture at each CoS, and save activity outcomes on the Smartphone. System evaluation involved collecting WMMS output and (separate) camcorder video under realistic conditions for five able-bodied subjects.  The subjects each performed a consecutive series of mobility tasks; including, walking, sitting, lying, stairs, ramps, elevator, bathroom activities, kitchen activities, dining activities and outdoor walking. Activity, timing and contextual information were obtained from the camcorder for comparison. Sensitivity results for sensor-based CoS identification were 97-100% for standing, sitting, lying and taking an elevator; 67-73% for walking-related CoS (stairs, ramps); 40-93% between walking and small movements (brushing teeth, etc.); and below 27% for daily living activities. False positives occurred in less than 12% of all activities, with less than 5% false positives for half the measures. Better classification results were achieved when using both acceleration features and Smartphone integrated video for all activities except sitting. The evaluation demonstrated that the WMMS algorithm and BlackBerry platform were effective for detecting mobility activities, even with low sampling rate sensors. The combined sensor and video analysis enhanced mobility task identification and contextual information.

Monitoring des Arzneimittelmissbrauchs 2006 bei Klienten von Suchtberatungsstellen (PHAR-MON)

2007 ◽  
Vol 53 (7) ◽  
pp. 65-77 ◽  
Author(s):  
Susanne Roesner ◽  
Heinrich Küfner
Keyword(s):  
Monitoring System

<span class="fett">Hintergrund und Zielsetzung:</span> PHAR-MON ist ein Monitoring-System, das die auf dem deutschen Markt befindlichen Arzneimittel in ihrer Bedeutung für die Entwicklung von Missbrauch und Abhängigkeit in Suchtberatungsstellen überwacht. </p><p> <span class="fett">Methodik:</span> Klienten ambulanter Beratungsstellen werden im Rahmen der Standarddokumentation zu ihrem Arzneimittelkonsum befragt und Fälle eines abhängigen Konsums, eines schädlichen Gebrauchs oder eines Missbrauchs in PHAR-MON dokumentiert. </p><p> <span class="fett">Ergebnisse:</span> Im Jahr 2006 wurden insgesamt 448 Meldungen von 276 überwiegend alkohol- und drogenabhängigen Klienten in das Monitoring einbezogen. Tranquilizer vom Benzodiazepin-Typ wurden in allen Klientengruppen mit Anteilen zwischen 29,1 % und 35,3 % am häufigsten dokumentiert. An benzodiazepinabhängige Klienten werden zunehmend auch Nicht-Benzodiazepin-Hypnotika verordnet. Bei opioidabhängigen Klienten war im Zeitraum der letzten fünf Jahre ein Anstieg im missbräuchlichen Substitutionsmittelkonsum von 14,9 % auf 33,8 % zu verzeichnen. </p><p> <span class="fett">Schlussfolgerungen:</span> Das Risiko gefährlicher Wechselwirkungen zwischen Arzneimitteln mit Alkohol und Drogen sollte stärker als bisher in die ärztliche Verordnungsentscheidung einbezogen werden.

Commercial Drivers' Initial Attitudes toward an On-Board Monitoring System

2012 ◽  
Author(s):  
Yiyun Peng ◽  
Mahtab Ghazizadeh ◽  
Linda Ng Boyle ◽  
John D. Lee
Keyword(s):  
Monitoring System ◽  
Commercial Drivers ◽  
Board Monitoring

An experimental I.L.S. echo-monitoring system

1966 ◽  
Vol 32 (6) ◽  
pp. 357
Author(s):  
J.G. Flounders
Keyword(s):  
Monitoring System
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