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公开(公告)号：US20180224350A1
公开(公告)日：2018-08-09
申请号：US15800990
申请日：2017-11-01
发明人： Brett Story , Dinesh Rajan , Joseph Camp , Matthew Napier-Jameson
IPC分类号： G01M5/00
CPC分类号： G01M5/005 , G01M5/0008 , G01M5/0066 , H04M1/0202 , H04M1/72522 , H04M2250/12
摘要： The present invention includes a method for detecting impairments of a structure in the absence of permanent sensor systems comprising: obtaining time-varying sensor data on a user device; filtering the time-varying sensor data obtained by the user device to determine a vibration response from structural infrastructure; and estimating structural responses of the structure by comparing at least one of: dynamic (short-term) sensor data to an analytical model of the structure; or dynamic sensor data from different user devices at different points in time (long-term), to determine if there has been any significant change in the structure with time.
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公开(公告)号：US20220244133A1
公开(公告)日：2022-08-04
申请号：US17725195
申请日：2022-04-20
发明人： Brett Story , Dinesh Rajan , Joseph Camp , Matthew Napier-Jameson
IPC分类号： G01M5/00
摘要： The present invention includes a method for detecting impairments of a structure in the absence of permanent sensor systems comprising: obtaining time-varying sensor data on a user device; filtering the time-varying sensor data obtained by the user device to determine a vibration response from structural infrastructure; and estimating structural responses of the structure by comparing at least one of: dynamic (short-term) sensor data to an analytical model of the structure; or dynamic sensor data from different user devices at different points in time (long-term), to determine if there has been any significant change in the structure with time.
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公开(公告)号：US20170195892A1
公开(公告)日：2017-07-06
申请号：US15399940
申请日：2017-01-06
发明人： Matthew Tonnemacher , Dinesh Rajan , Joseph Camp
IPC分类号： H04W16/22 , H04W24/08 , H04W24/02 , H04B17/318 , H04W4/02
摘要： The present invention includes an apparatus and method for determining cell coverage in a region with reduced in-field propagation measurements comprising: obtaining geographical features of the region; predicting the number of measurements required to accurately characterize its path loss; determining the path loss prediction accuracy of wardriving and crowdsourcing by oversampling a suburban and a downtown region from cell measurements that comprise signal strength and global positioning system coordinates; and using statistical learning to build a relationship between these geographical features and the measurements required, thereby reducing the number of measurements needed to determine path loss accuracy.
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公开(公告)号：US20180300849A1
公开(公告)日：2018-10-18
申请号：US15951632
申请日：2018-04-12
发明人： Dinesh Rajan , Brett Story , Joseph Camp
摘要： The present invention includes an apparatus and method for determining time-varying stress experienced by a structure comprising: obtaining images that include the structure; segmenting the second and any subsequent images to include the “static” portions that are identified from the first image; computing with a processor the affine transformations between the first and second, and optionally subsequent images, sequence of images; estimating a deformation (i.e. translation and rotation) undergone by the structure; and converting the deformation to estimate the structural stress by using one or more scaling functions) to generate the time-varying stress experienced by the structure.
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公开(公告)号：US09913146B2
公开(公告)日：2018-03-06
申请号：US15399940
申请日：2017-01-06
发明人： Matthew Tonnemacher , Dinesh Rajan , Joseph Camp
摘要： The present invention includes an apparatus and method for determining cell coverage in a region with reduced in-field propagation measurements comprising: obtaining geographical features of the region; predicting the number of measurements required to accurately characterize its path loss; determining the path loss prediction accuracy of wardriving and crowdsourcing by oversampling a suburban and a downtown region from cell measurements that comprise signal strength and global positioning system coordinates; and using statistical learning to build a relationship between these geographical features and the measurements required, thereby reducing the number of measurements needed to determine path loss accuracy.
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