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10.3390/s16020215 http://scihub22266oqcxt.onion/10.3390/s16020215 C4801591!4801591 !26861345     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 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 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 247.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\26861345 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Sensors+(Basel) 2016 ; 16 (2 ): 215 Nephropedia Template TP {{tp|p=26861345 |t=2016. Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges |pdf=|usr=}}{{26861345 }} gab.com Text Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges JO: Sensors (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=26861345 #FOAvip The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. Twit Text FOAVip Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges ????Sensors (Basel) http://www.kidney.de/pget.php?&tw=1&pmid=26861345 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26861345 #FOAvip English Wikipedia <ref>{{Cite pmid|26861345 }}</ref> Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges #MMPMID26861345 Chen Y ; Lee GM ; Shu L ; Crespi N Sensors (Basel) 2016[Feb]; 16 (2 ): 215 PMID26861345 show ga The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. äIndustrial Internet of Things-Based Collaborative Sensing Intelligence(epmc).pdf DeepDyve Pubget Overpricing