SELECTION DEVICE AND INFORMATION PROCESSING SYSTEM

To improve the determination accuracy of the position of a wireless tag.SOLUTION: A selection device of an embodiment includes an acquisition unit and a selection unit. The acquisition unit acquires tag data of a reference wireless tag at a plurality of positions of an antenna measured by a communic...

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1. Verfasser: ISHIKAWA HIROYOSHI
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description To improve the determination accuracy of the position of a wireless tag.SOLUTION: A selection device of an embodiment includes an acquisition unit and a selection unit. The acquisition unit acquires tag data of a reference wireless tag at a plurality of positions of an antenna measured by a communication device having the antenna. The selection unit selects a trained model from a plurality of trained models based on the tag data of the reference wireless tag. The plurality of trained models are models according to environments of the communication device, and are models generated by machine learning based on multiple pieces of learning data. The multiple pieces of learning data include tag data of a plurality of learning target wireless tags and data indicating a range in which each of the plurality of learning target wireless tags exists.SELECTED DRAWING: Figure 11 【課題】無線タグの位置の判定精度を向上させる。【解決手段】実施形態の選択装置は、取得部と、選択部とを含む。取得部は、アンテナを備える通信装置により計測されたアンテナの複数の位置における基準無線タグのタグデータを取得する。選択部は、基準無線タグのタグデータに基づいて、複数の学習済モデルから学習済モデルを選択する。複数の学習済モデルは、通信装置の環境に応じたモデルであって、複数の学習データに基づく機械学習により生成されたモデルである。複数の学習データは、複数の学習対象の無線タグのタグデータ及び複数の学習対象の無線タグのそれぞれが存在する範囲を示すデータを含む。【選択図】図11
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The acquisition unit acquires tag data of a reference wireless tag at a plurality of positions of an antenna measured by a communication device having the antenna. The selection unit selects a trained model from a plurality of trained models based on the tag data of the reference wireless tag. The plurality of trained models are models according to environments of the communication device, and are models generated by machine learning based on multiple pieces of learning data. The multiple pieces of learning data include tag data of a plurality of learning target wireless tags and data indicating a range in which each of the plurality of learning target wireless tags exists.SELECTED DRAWING: Figure 11 【課題】無線タグの位置の判定精度を向上させる。【解決手段】実施形態の選択装置は、取得部と、選択部とを含む。取得部は、アンテナを備える通信装置により計測されたアンテナの複数の位置における基準無線タグのタグデータを取得する。選択部は、基準無線タグのタグデータに基づいて、複数の学習済モデルから学習済モデルを選択する。複数の学習済モデルは、通信装置の環境に応じたモデルであって、複数の学習データに基づく機械学習により生成されたモデルである。複数の学習データは、複数の学習対象の無線タグのタグデータ及び複数の学習対象の無線タグのそれぞれが存在する範囲を示すデータを含む。【選択図】図11</description><language>eng ; jpn</language><subject>ANALOGOUS ARRANGEMENTS USING OTHER WAVES ; CALCULATING ; COMPUTING ; COUNTING ; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES ; HANDLING RECORD CARRIERS ; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES ; MEASURING ; PHYSICS ; PRESENTATION OF DATA ; RADIO DIRECTION-FINDING ; RADIO NAVIGATION ; RECOGNITION OF DATA ; RECORD CARRIERS ; TESTING</subject><creationdate>2023</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20230614&amp;DB=EPODOC&amp;CC=JP&amp;NR=2023082574A$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&amp;date=20230614&amp;DB=EPODOC&amp;CC=JP&amp;NR=2023082574A$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>ISHIKAWA HIROYOSHI</creatorcontrib><title>SELECTION DEVICE AND INFORMATION PROCESSING SYSTEM</title><description>To improve the determination accuracy of the position of a wireless tag.SOLUTION: A selection device of an embodiment includes an acquisition unit and a selection unit. The acquisition unit acquires tag data of a reference wireless tag at a plurality of positions of an antenna measured by a communication device having the antenna. The selection unit selects a trained model from a plurality of trained models based on the tag data of the reference wireless tag. The plurality of trained models are models according to environments of the communication device, and are models generated by machine learning based on multiple pieces of learning data. The multiple pieces of learning data include tag data of a plurality of learning target wireless tags and data indicating a range in which each of the plurality of learning target wireless tags exists.SELECTED DRAWING: Figure 11 【課題】無線タグの位置の判定精度を向上させる。【解決手段】実施形態の選択装置は、取得部と、選択部とを含む。取得部は、アンテナを備える通信装置により計測されたアンテナの複数の位置における基準無線タグのタグデータを取得する。選択部は、基準無線タグのタグデータに基づいて、複数の学習済モデルから学習済モデルを選択する。複数の学習済モデルは、通信装置の環境に応じたモデルであって、複数の学習データに基づく機械学習により生成されたモデルである。複数の学習データは、複数の学習対象の無線タグのタグデータ及び複数の学習対象の無線タグのそれぞれが存在する範囲を示すデータを含む。【選択図】図11</description><subject>ANALOGOUS ARRANGEMENTS USING OTHER WAVES</subject><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES</subject><subject>HANDLING RECORD CARRIERS</subject><subject>LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>PRESENTATION OF DATA</subject><subject>RADIO DIRECTION-FINDING</subject><subject>RADIO NAVIGATION</subject><subject>RECOGNITION OF DATA</subject><subject>RECORD CARRIERS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2023</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZDAKdvVxdQ7x9PdTcHEN83R2VXD0c1Hw9HPzD_J1BAsHBPk7uwYHe_q5KwRHBoe4-vIwsKYl5hSn8kJpbgYlN9cQZw_d1IL8-NTigsTk1LzUknivACMDI2MDCyNTcxNHY6IUAQDa0CeA</recordid><startdate>20230614</startdate><enddate>20230614</enddate><creator>ISHIKAWA HIROYOSHI</creator><scope>EVB</scope></search><sort><creationdate>20230614</creationdate><title>SELECTION DEVICE AND INFORMATION PROCESSING SYSTEM</title><author>ISHIKAWA HIROYOSHI</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_JP2023082574A3</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng ; jpn</language><creationdate>2023</creationdate><topic>ANALOGOUS ARRANGEMENTS USING OTHER WAVES</topic><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES</topic><topic>HANDLING RECORD CARRIERS</topic><topic>LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>PRESENTATION OF DATA</topic><topic>RADIO DIRECTION-FINDING</topic><topic>RADIO NAVIGATION</topic><topic>RECOGNITION OF DATA</topic><topic>RECORD CARRIERS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>ISHIKAWA HIROYOSHI</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>ISHIKAWA HIROYOSHI</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>SELECTION DEVICE AND INFORMATION PROCESSING SYSTEM</title><date>2023-06-14</date><risdate>2023</risdate><abstract>To improve the determination accuracy of the position of a wireless tag.SOLUTION: A selection device of an embodiment includes an acquisition unit and a selection unit. The acquisition unit acquires tag data of a reference wireless tag at a plurality of positions of an antenna measured by a communication device having the antenna. The selection unit selects a trained model from a plurality of trained models based on the tag data of the reference wireless tag. The plurality of trained models are models according to environments of the communication device, and are models generated by machine learning based on multiple pieces of learning data. The multiple pieces of learning data include tag data of a plurality of learning target wireless tags and data indicating a range in which each of the plurality of learning target wireless tags exists.SELECTED DRAWING: Figure 11 【課題】無線タグの位置の判定精度を向上させる。【解決手段】実施形態の選択装置は、取得部と、選択部とを含む。取得部は、アンテナを備える通信装置により計測されたアンテナの複数の位置における基準無線タグのタグデータを取得する。選択部は、基準無線タグのタグデータに基づいて、複数の学習済モデルから学習済モデルを選択する。複数の学習済モデルは、通信装置の環境に応じたモデルであって、複数の学習データに基づく機械学習により生成されたモデルである。複数の学習データは、複数の学習対象の無線タグのタグデータ及び複数の学習対象の無線タグのそれぞれが存在する範囲を示すデータを含む。【選択図】図11</abstract><oa>free_for_read</oa></addata></record>
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language eng ; jpn
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subjects ANALOGOUS ARRANGEMENTS USING OTHER WAVES
CALCULATING
COMPUTING
COUNTING
DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES
HANDLING RECORD CARRIERS
LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION ORRERADIATION OF RADIO WAVES
MEASURING
PHYSICS
PRESENTATION OF DATA
RADIO DIRECTION-FINDING
RADIO NAVIGATION
RECOGNITION OF DATA
RECORD CARRIERS
TESTING
title SELECTION DEVICE AND INFORMATION PROCESSING SYSTEM
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