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公开(公告)号：US10425912B1
公开(公告)日：2019-09-24
申请号：US16250043
申请日：2019-01-17
Applicant: Cisco Technology, Inc.
Inventor： Abhishek Mukherji , Santosh Ghanshyam Pandey , Abhishek Bhattacharyya , Vinay Raghuram , Balaji Gurumurthy , Prasad Walawalkar
Abstract: In one embodiment, a device receives location estimates for a wireless node in a network, each location estimate having an associated timestamp. The device applies hierarchical clustering to the received location estimates and their associated timestamps, to identify locations and points in time in which the wireless node was stationary. The device performs sequence modeling on the identified locations and points in time in which the wireless node was stationary, to form a sequence of locations and associated time periods in which the wireless node was stationary. The device associates the wireless node with a behavioral profile based on the sequence of locations and associated time periods in which the wireless node. The device generates, based in part on the behavioral profile for the wireless node, a predictive model that predicts a location of the wireless node at a particular point in time.
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公开(公告)号：US20210112624A1
公开(公告)日：2021-04-15
申请号：US16599309
申请日：2019-10-11
Applicant: Cisco Technology, Inc.
Inventor： Abhishek Bhattacharyya , Abhishek Mukherji , Balaji Gurumurthy , Jenny Marie Yoshihara , Chayan Bhaisare , Prasad Walawalkar
Abstract: In one embodiment, a traffic analysis service receives payload data from packets sent by a sensor tag in a network. The service forms a payload signature for the sensor tag, based on the payload data. The payload signature is indicative of one or more bytes in the payload that vary across the packets. The service identifies a portion of the payload data as potentially including a sensor measurement, based on the payload signature. The service uses a machine learning classifier to assign a sensor measurement type to the identified portion of the payload data.
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公开(公告)号：US10542517B1
公开(公告)日：2020-01-21
申请号：US16539359
申请日：2019-08-13
Applicant: Cisco Technology, Inc.
Inventor： Abhishek Mukherji , Santosh Ghanshyam Pandey , Abhishek Bhattacharyya , Vinay Raghuram , Balaji Gurumurthy , Prasad Walawalkar
Abstract: In one embodiment, a device receives location estimates for a wireless node in a network, each location estimate having an associated timestamp. The device applies hierarchical clustering to the received location estimates and their associated timestamps, to identify locations and points in time in which the wireless node was stationary. The device performs sequence modeling on the identified locations and points in time in which the wireless node was stationary, to form a sequence of locations and associated time periods in which the wireless node was stationary. The device associates the wireless node with a behavioral profile based on the sequence of locations and associated time periods in which the wireless node. The device generates, based in part on the behavioral profile for the wireless node, a predictive model that predicts a location of the wireless node at a particular point in time.
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公开(公告)号：US10959290B1
公开(公告)日：2021-03-23
申请号：US16599309
申请日：2019-10-11
Applicant: Cisco Technology, Inc.
Inventor： Abhishek Bhattacharyya , Abhishek Mukherji , Balaji Gurumurthy , Jenny Marie Yoshihara , Chayan Bhaisare , Prasad Walawalkar
Abstract: In one embodiment, a traffic analysis service receives payload data from packets sent by a sensor tag in a network. The service forms a payload signature for the sensor tag, based on the payload data. The payload signature is indicative of one or more bytes in the payload that vary across the packets. The service identifies a portion of the payload data as potentially including a sensor measurement, based on the payload signature. The service uses a machine learning classifier to assign a sensor measurement type to the identified portion of the payload data.
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