کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4957558 | 1445083 | 2016 | 24 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Detecting abnormal events on binary sensors in smart home environments
ترجمه فارسی عنوان
تشخیص رویدادهای غیر عادی در سنسورهای باینری در محیط خانه های هوشمند
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کلمات کلیدی
هستی شناسی، خانه هوشمند، تشخیص گسل، معناشناسی، دانش دامنه،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
شبکه های کامپیوتری و ارتباطات
چکیده انگلیسی
With a rising ageing population, smart home technologies have been demonstrated as a promising paradigm to enable technology-driven healthcare delivery. Smart home technologies, composed of advanced sensing, computing, and communication technologies, offer an unprecedented opportunity to keep track of behaviours and activities of the elderly and provide context-aware services that enable the elderly to remain active and independent in their own homes. However, experiments in developed prototypes demonstrate that abnormal sensor events hamper the correct identification of critical (and potentially life-threatening) situations, and that existing learning, estimation, and time-based approaches to situation recognition are inaccurate and inflexible when applied to multiple people sharing a living space. We propose a novel technique, called CLEAN, that integrates the semantics of sensor readings with statistical outlier detection. We evaluate the technique against four real-world datasets across different environments including the datasets with multiple residents. The results have shown that CLEAN can successfully detect sensor anomaly and improve activity recognition accuracies.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Pervasive and Mobile Computing - Volume 33, December 2016, Pages 32-49
Journal: Pervasive and Mobile Computing - Volume 33, December 2016, Pages 32-49
نویسندگان
Juan Ye, Graeme Stevenson, Simon Dobson,