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1.
公开(公告)号:US20170374436A1
公开(公告)日:2017-12-28
申请号:US15631870
申请日:2017-06-23
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor: Steven T. AWISZUS , Eric C. LOBNER , Michael G. WURM , Kiran S. KANUKURTHY , Jia HU , Matthew J. BLACKFORD , Keith G. MATTSON , Ronald D. JESME , Nathan J. ANDERSON
CPC classification number: H04Q9/00 , A61F9/06 , A62B9/00 , A62B18/00 , A62B27/00 , A62B99/00 , G06F17/30516
Abstract: In some examples, a system includes an article of personal protective equipment (PPE) having at least one sensor configured to generate a stream of usage data; and an analytical stream processing component comprising: a communication component that receives the stream of usage data; a memory configured to store at least a portion of the stream of usage data and at least one model for detecting a safety event signature, wherein the at least one model is trained based as least in part on a set of usage data generated by one or more other articles of PPE of a same type as the article of PPE; and one or more computer processors configured to: detect the safety event signature in the stream of usage data based on processing the stream of usage data with the model, and generate an output in response to detecting the safety event signature.
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公开(公告)号:US20180107169A1
公开(公告)日:2018-04-19
申请号:US15782645
申请日:2017-10-12
Applicant: 3M INNOVATIVE PROPERTIES COMPANY
Inventor: Jia HU , Matthew J. BLACKFORD , Keith G. MATTSON , Ronald D. JESME , Nathan J. ANDERSON
CPC classification number: G05B9/02 , A62B35/0043 , A62B35/0093 , G05B6/02 , G05B17/02
Abstract: In some examples, a system includes a self-retracting lifeline (SRL) comprising one or more electronic sensors, the one or more electronic sensors configured to generate data that is indicative of an operation of the SRL; and at least one computing device comprising one or more computer processors and a memory comprising instructions that when executed by the one or more computer processors cause the one or more computer processors to: receive the data that is indicative of the operation of the SRL; apply the data to a safety model that predicts a likelihood of an occurrence of a safety event associated with the SRL; and perform one or more operations based at least in part on the likelihood of the occurrence of the safety event.
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