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MX2016003107A - Recapitulacion de datos de multiples sensores. - Google Patents

Recapitulacion de datos de multiples sensores.

Info

Publication number
MX2016003107A
MX2016003107A MX2016003107A MX2016003107A MX2016003107A MX 2016003107 A MX2016003107 A MX 2016003107A MX 2016003107 A MX2016003107 A MX 2016003107A MX 2016003107 A MX2016003107 A MX 2016003107A MX 2016003107 A MX2016003107 A MX 2016003107A
Authority
MX
Mexico
Prior art keywords
sensor
rules
clusters
sensor data
sensors
Prior art date
Application number
MX2016003107A
Other languages
English (en)
Other versions
MX368053B (es
Inventor
Puneet Agarwal
Gautam Shroff
Saikia Sarmimala
Ashwin Srinivasan
Original Assignee
Tata Consultancy Services Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tata Consultancy Services Ltd filed Critical Tata Consultancy Services Ltd
Publication of MX2016003107A publication Critical patent/MX2016003107A/es
Publication of MX368053B publication Critical patent/MX368053B/es

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/906—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/22—Indexing; Data structures therefor; Storage structures
    • G06F16/2228—Indexing structures
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28—Databases characterised by their database models, e.g. relational or object models
    • G06F16/284—Relational databases
    • G06F16/285—Clustering or classification
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computing arrangements using knowledge-based models
    • G06N5/02—Knowledge representation; Symbolic representation
    • G06N5/022—Knowledge engineering; Knowledge acquisition
    • G06N5/025—Extracting rules from data
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04Q—SELECTING
    • H04Q9/00—Arrangements in telecontrol or telemetry systems for selectively calling a substation from a main station, in which substation desired apparatus is selected for applying a control signal thereto or for obtaining measured values therefrom

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Software Systems (AREA)
  • Evolutionary Computation (AREA)
  • Computing Systems (AREA)
  • Mathematical Physics (AREA)
  • Artificial Intelligence (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Computational Linguistics (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Medical Informatics (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
  • Television Signal Processing For Recording (AREA)
  • Testing Or Calibration Of Command Recording Devices (AREA)

Abstract

Se proporcionan un sistema 200 y un procedimiento para recapitular datos de múltiples sensores. En una realización, el procedimiento incluye calcular una pluralidad de histogramas a partir de datos de sensores asociados a una pluralidad de sensores. Los respectivos histogramas de cada sensor son agrupados en una primera pluralidad de agrupaciones de sensores, y se extrae de los mismos un primer conjunto de reglas. El primer conjunto de reglas define patrones de histogramas de un conjunto de sensores que aparecen frecuentemente durante un periodo de tiempo. Dos o más agrupaciones de sensores, entre la primera pluralidad de agrupaciones de sensores, se funden selectivamente para obtener una segunda pluralidad de agrupaciones de sensores. El segundo conjunto de reglas se extraen a partir de la segunda pluralidad de agrupaciones de sensores, y un conjunto de sensores correlacionados son identificados a partir de las mismas, en base al segundo conjunto de reglas. El tercer conjunto de reglas se extraen del conjunto de sensores correlacionados, donde el tercer conjunto de reglas recapitula los datos de múltiples sensores para representar prominentes comportamientos concurrentes de sensores.
MX2016003107A 2015-10-17 2016-03-09 Recapitulacion de datos de multiples sensores. MX368053B (es)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
IN3945MU2015 2015-10-17

Publications (2)

Publication Number Publication Date
MX2016003107A true MX2016003107A (es) 2017-04-17
MX368053B MX368053B (es) 2019-09-18

Family

ID=55453051

Family Applications (1)

Application Number Title Priority Date Filing Date
MX2016003107A MX368053B (es) 2015-10-17 2016-03-09 Recapitulacion de datos de multiples sensores.

Country Status (7)

Country Link
US (1) US10332030B2 (es)
EP (1) EP3157264B1 (es)
JP (1) JP6219428B2 (es)
AU (1) AU2016201330B2 (es)
BR (1) BR102016005511B1 (es)
CA (1) CA2923563C (es)
MX (1) MX368053B (es)

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US10380204B1 (en) 2014-02-12 2019-08-13 Pinterest, Inc. Visual search
US10506380B2 (en) * 2016-12-22 2019-12-10 Nokia Solutions And Networks Oy User motion profiling based on user equipment cell location
US10755198B2 (en) * 2016-12-29 2020-08-25 Intel Corporation Data class analysis method and apparatus
WO2019143889A1 (en) * 2018-01-19 2019-07-25 Robert Bosch Gmbh System and method for optimizing energy use of a structure using a clustering-based rule-mining approach
US10929505B1 (en) * 2018-03-19 2021-02-23 EMC IP Holding Company LLC Method and system for implementing histogram-based alarms in a production system
JP7176385B2 (ja) * 2018-12-06 2022-11-22 富士通株式会社 分析プログラム、分析方法および分析装置
JP7298870B2 (ja) * 2019-03-15 2023-06-27 慶應義塾 分子動力学データ解析装置及びプログラム
US10887928B2 (en) * 2019-04-24 2021-01-05 Here Global B.V. Lane aware clusters for vehicle to vehicle communication
US11693924B2 (en) * 2019-06-06 2023-07-04 Hitachi, Ltd. System and method for maintenance recommendation in industrial networks
JP2022085374A (ja) * 2020-11-27 2022-06-08 京セラ株式会社 電子機器、電子機器の制御方法、及びプログラム
CN113282645A (zh) * 2021-07-23 2021-08-20 广东粤港澳大湾区硬科技创新研究院 一种卫星时序参数分析方法、系统、终端以及存储介质
US20250061097A1 (en) * 2021-12-20 2025-02-20 Continental Autonomous Mobility Germany GmbH Method for creating a database for recognizing driving context

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7580912B2 (en) 2001-06-12 2009-08-25 Alcatel-Lucent Usa Inc. Performance data mining based on real time analysis of sensor data
US7143352B2 (en) * 2002-11-01 2006-11-28 Mitsubishi Electric Research Laboratories, Inc Blind summarization of video content
US7715961B1 (en) * 2004-04-28 2010-05-11 Agnik, Llc Onboard driver, vehicle and fleet data mining
US7937167B1 (en) * 2006-08-12 2011-05-03 Hewlett-Packard Development Company L. P. Methodology to program sensors into collaborative sensing groups
JP4686438B2 (ja) 2006-11-28 2011-05-25 日本電信電話株式会社 データ分類装置、データ分類方法およびデータ分類プログラムならびに記録媒体
US9270518B2 (en) * 2010-05-17 2016-02-23 Hitachi, Ltd. Computer system and rule generation method
US20120224711A1 (en) 2011-03-04 2012-09-06 Qualcomm Incorporated Method and apparatus for grouping client devices based on context similarity
JP5301717B1 (ja) 2012-08-01 2013-09-25 株式会社日立パワーソリューションズ 設備状態監視方法およびその装置
JP6057786B2 (ja) 2013-03-13 2017-01-11 ヤフー株式会社 時系列データ解析装置、時系列データ解析方法、およびプログラム
CN103344941B (zh) * 2013-06-13 2015-08-12 北京空间飞行器总体设计部 基于无线传感器网络的实时目标检测方法
JP6082341B2 (ja) 2013-12-05 2017-02-15 株式会社日立ソリューションズ 異常検出装置及び異常検出方法
JP6207405B2 (ja) 2014-01-10 2017-10-04 三菱電機株式会社 データ処理装置
EP2916260A1 (en) * 2014-03-06 2015-09-09 Tata Consultancy Services Limited Time series analytics
US20160371363A1 (en) 2014-03-26 2016-12-22 Hitachi, Ltd. Time series data management method and time series data management system

Also Published As

Publication number Publication date
CA2923563C (en) 2020-04-21
MX368053B (es) 2019-09-18
JP2017076359A (ja) 2017-04-20
CA2923563A1 (en) 2017-04-17
EP3157264B1 (en) 2019-02-20
BR102016005511A2 (pt) 2017-05-30
US20170109653A1 (en) 2017-04-20
BR102016005511B1 (pt) 2021-04-13
US10332030B2 (en) 2019-06-25
AU2016201330A1 (en) 2017-05-04
AU2016201330B2 (en) 2018-05-10
EP3157264A1 (en) 2017-04-19
JP6219428B2 (ja) 2017-10-25

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