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10.1016/j.patrec.2020.05.016 http://scihub22266oqcxt.onion/10.1016/j.patrec.2020.05.016 32406416!7217772!32406416     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Pattern+Recognit+Lett 2020 ; 135 (ä): 346-353 Nephropedia Template TP {{tp|p=32406416|t=2020. Trends in IoT based solutions for health care: Moving AI to the edge |pdf=|usr=}}{{32406416}} gab.com Text Trends in IoT based solutions for health care: Moving AI to the edge JO: Pattern Recognit Lett http://www.kidney.de/pget.php?&tw=1&pmid=32406416 #FOAvip In recent times, we assist to an ever growing diffusion of smart medical sensors and Internet of things devices that are heavily changing the way healthcare is approached worldwide. In this context, a combination of Cloud and IoT architectures is often exploited to make smart healthcare systems capable of supporting near realtime applications when processing and performing Artificial Intelligence on the huge amount of data produced by wearable sensor networks. Anyway, the response time and the availability of cloud based systems, together with security and privacy, still represent critical issues that prevents Internet of Medical Things (IoMT) devices and architectures from being a reliable and effective solution to the aim. Lately, there is a growing interest towards architectures and approaches that exploit Edge and Fog computing as an answer to compensate the weaknesses of the cloud. In this paper, we propose a short review about the general use of IoT solutions in health care, starting from early health monitoring solutions from wearable sensors up to a discussion about the latest trends in fog/edge computing for smart health. Twit Text FOAVip Trends in IoT based solutions for health care: Moving AI to the edge ????Pattern Recognit Lett http://www.kidney.de/pget.php?&tw=1&pmid=32406416 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32406416 #FOAvip English Wikipedia <ref>{{Cite pmid|32406416}}</ref> Trends in IoT based solutions for health care: Moving AI to the edge #MMPMID32406416 Greco L; Percannella G; Ritrovato P; Tortorella F; Vento M Pattern Recognit Lett 2020[Jul]; 135 (ä): 346-353 PMID32406416show ga In recent times, we assist to an ever growing diffusion of smart medical sensors and Internet of things devices that are heavily changing the way healthcare is approached worldwide. In this context, a combination of Cloud and IoT architectures is often exploited to make smart healthcare systems capable of supporting near realtime applications when processing and performing Artificial Intelligence on the huge amount of data produced by wearable sensor networks. Anyway, the response time and the availability of cloud based systems, together with security and privacy, still represent critical issues that prevents Internet of Medical Things (IoMT) devices and architectures from being a reliable and effective solution to the aim. Lately, there is a growing interest towards architectures and approaches that exploit Edge and Fog computing as an answer to compensate the weaknesses of the cloud. In this paper, we propose a short review about the general use of IoT solutions in health care, starting from early health monitoring solutions from wearable sensors up to a discussion about the latest trends in fog/edge computing for smart health. äTrends in IoT based solutions for health care: Moving AI to the edge (epmc).pdf DeepDyve Pubget Overpricing