https://mw.hh.se/caisr/api.php?action=feedcontributions&feedformat=atom&user=Roland 2026-04-04T15:07:24Z User contributions MediaWiki 1.35.13 https://mw.hh.se/caisr/index.php?title=SA3L_-_Situation_Awareness_for_Ambient_Assisted_Living&diff=2413 2016-01-15T06:51:21Z

<p>Roland: </p> <hr /> <div>{{ResearchProjInfo<br /> |Title=SA3L - Situation Awareness for Ambient Assisted Living<br /> |ContactInformation=Roland Thörner<br /> |ShortDescription=This project focuses on data mining methods and sensors to model human behavior in home environments and techniques to infer knowledge from such models.<br /> |Description=A demographic change is occurring in many areas of the world. The population share in which people<br /> in age over 60 years has been increasing for the last decades and estimations predict that this<br /> group of elderly population will near quadruple in the year 2050 ref1. This change will bring exponentially<br /> increasing costs of health care ref3, which will be supported by the decreasing share of younger<br /> people. One solution to this challenge is through technological developments aiming at reducing the<br /> costs of health care. Smart environments, ref2, targeted for ambient assisted living, enable people to<br /> remain independent at their own home and to live in a decent way longer. Key functions of such environments<br /> are:<br /> * Answering queries (where is the person, for example).<br /> * Activity recognition (what the person is doing).<br /> * Detection of specific behaviour and potentially dangerous situations.<br /> * Fall monitoring.<br /> Camera sensors have been used for the detection of human activities of daily living (ADL). However,<br /> the privacy issues of such camera-based solutions motivates the usage of other sensors such as wearable<br /> inertial sensors and accelerometers. A wearable sensor is dependent on several aspects of human<br /> behavior such as remembering to put on the sensors and doing so properly. Other, often used,<br /> sensors in ubiquitous computing are switches, motion detectors and electromechanical sensors, which<br /> do not, at the same extent, breach the privacy of individuals. Because of the large variety of sensor<br /> types and settings, information processing approaches, and individuals living in the environments, finding an accurate, robust and economically efficient solution to the problem is a hard task.<br /> This project focuses on data mining methods and sensors to model human behavior in home environments and techniques to infer knowledge from such models.<br /> |LogotypeFile=Procedure.png<br /> |ProjectResponsible=Roland.Thorner@hh.se<br /> |ProjectDetailsPDF=ExtAbsSAAAL.pdf<br /> |ProjectStart=2012/01/01<br /> |ProjectEnd=2018/12/31<br /> |ApplicationArea=Health Technology<br /> |Lctitle=No<br /> }}<br /> {{AssignProjPartner<br /> |projectpartner=Neat Electronics AB<br /> }}<br /> {{ShowResearchProject}}</div>

Roland