JP2013500538A - 存在検出のための方法およびシステム - Google Patents
存在検出のための方法およびシステム Download PDFInfo
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Abstract
【選択図】図1
Description
本出願は、“Method And System For Location‐Triggered Interactivity In Offline Environments(オフライン環境における位置トリガによるインタラクティビティのための方法およびシステム)”という名称で2009年7月29日に出願された米国仮特許出願番号61/273,040、および“Method And System For Location‐Triggered Interactivity In Offline Environments"という名称で2009年10月19日に出願された米国仮特許出願番号61/253,009の優先権を主張するものであり、これらは、その全体が参照により本明細書に組み込まれる。
小売店での体験は、実小売界における店舗の訪問から実際の購入へのコンバージョン・レートが、通常、小売業者の種別に応じて25‐60%の間であることを示しており、これに対して、オンライン小売サイトの場合のコンバージョンは通常1‐3%である。つまり、消費者は、ひとたび実店舗に入れば、実際に購入する可能性が高い。従って、実小売業者の最大の課題は、店舗内でより多くの購買を生み出すために、消費者が店舗を訪れるようにさせることである。購買に至るようにする最も有効な方法の1つは、適切な消費者に適切なオファーを提示することであり、すなわち、“誰にでも同じ無関係なオファー”ではなく、関係のあるオファーを提示することである。
Justin Shumaker著“Designing an Ultrasonic Modem for Robotic Communications(ロボティック通信のための超音波モデムの設計)” 陸軍研究所刊行物ARL‐TR‐4754;
T.L.Murphy著“Ultrasonic Digital Communication System for a Steel Wall Multipath Channel: Methods and Results(鋼壁多経路チャネルのための超音波デジタル通信システム:方法と結果)”レンセラー工科大学、2005年12月;
Vadim Gerasimov著“Things that Talk”マサチューセッツ工科大学、1996年6月;
Vadim Gerasimov等著“Things that Talk: Using Sound for Device‐to‐Device and Device‐to‐Human Communication” IBM Systems Journal、39巻、3‐4号(2000年7月);
Chuan Li等著“Short‐Range Ultrasonic Digital Communications in Air” IEEE Transactions on Ultrasonics,Ferroelectrics,and Frequency Control、55巻、4号(2008年4月)。
これらは全て、その全体が全ての目的のために参照により本明細書に組み込まれる。
消費者は実店舗に入ると購買の可能性が高いので(一般に、オンライン小売ウェブサイトを訪れる場合より可能性が20〜50倍高い)、店舗訪問に関連する活動へのインセンティブが与えられる。本発明のシステムは、消費者の位置を特定し、入店したときを判断することができる。一実施形態では、購買の可能性が高くなる活動に対してポイントが与えられ、このポイントは、全ての加盟小売店で割引と引き換えることができ、あるいはバーチャルグッズと交換することができる。オファーまたは割引を受け取るために、購買の必要はない。入店と、店内での滞在時間と、福引(スウィープステイクス)と、サプライズ・オファーと、消費者が店に居るときの、場合によっては指定された時間および/またはエリアでのゲームと、を含む行動に対して、ポイントを与えることができる。
店内の特定の商品、通路、または場所の前で、位置ベースの特別なオファーを提示することもできる。商品に特定のオファーの場合、システムは、ユーザがその商品に近接していることを判断することができる。例えば、顧客が音楽売り場で検出された場合、CDを2枚買えば1枚は50%引きのオファーを送信することができる。あるいは、顧客が大型家庭電化商品エリアを歩いているときには、宅配送料無料を提示することができる。顧客が、2度目、3度目と戻ってきたときには、(例えば、インセンティブを増加または減少させるなど)オファーを変更することができる。オファーは、前述のように個人化することで、顧客と商品に応じて異なっていてもよい。
オファーは、利用可能な個人プロファイル・データセットのマッチングにより個人化される。個人プロファイル・データの例には、位置;好きな店および品目、ウィッシュリストの商品といった明記されている好み;好きな商品カテゴリまたは品目または店など、品目または店のクリックに基づいて暗に推測されるユーザの好み、が含まれる。また、個人プロファイル・データは、“歩行”履歴を含むこともできる。例えば、続けて高級店に入る消費者は、高額を使う人であるか、あるいは“ファッショニスタ”すなわちファッショントレンドに興味がある人であるか、いずれかである。また、個人プロファイル・データは、年齢、性別、およびデモグラフィック(属性)を含むこともできる。これは、オファーを提示するに当たって重要となり得る。例えば、子供のいない若者は、一般に幼児用品についてのオファーを求めていない。プロファイル・データは、さらに、過去の購買履歴、および、生年月日、所得、配偶者の有無、住所、その他の情報を含むデモグラフィック情報などのユーザ登録情報を含むこともできる。一実施形態では、プロファイル・データを用いて、最も適切なオファーおよびリワードを決定することができ、このオファーおよびリワードは、個人のプロファイル・データセットに基づいて各オファーに加重スコアを割り当てるマッチング・アルゴリズムにより、消費者に受け入れられる可能性が最も高いとされるものである。
重み付きマッチングスコア(WMS:Weighted Matching Score)=30%A+20%B+15%C+5%D+20%E+5%F+5%G
ただし、
A=distance_from_store
B=gender_factor_for_product
C=age_match_to_product
D=favorite_category
E=favorite_product
F=previous_clicks_on_product
G=friend_recommendations
Daniel Lemire等著“Slope One Predictors for Online Rating‐Based Collaborative Filtering(オンライン評価に基づく協調フィルタリングためのスロープワン予測器)”SIAM Data Mining ’05(2005年4月);
Yehuda Koren著“The BellKor Solution to the Netflix Grand Prize(ネットフリックス・グランプリのBellKorによるソリューション)”Netflix Corporation(2009年8月);
Amar Saric等著“Alternative Formulas for Rating Prediction Using Collaborative Filtering(協調フィルタリングを用いた評価予測のための代替公式)” Proceedings of ISMIS(Springer出版,2009年);
Jonathan L.Herlocker等著“Evaluating Collaborative Filtering Recommender Systems(協調フィルタリングによるレコメンダシステムの評価)” ACM Transactions on Information Systems,22巻,1号(2004年1月);
G.Adomavicius等著“Toward the Next Generation of Recommender Systems: a Survey of the State‐of‐the‐Art and Possible Extensions(次世代のレコメンダシステムに向けて:最新技術と可能な拡張に関する概説)” IEEE Transactions on Knowledge and Data Engineering,17巻,6号(2005年6月)。
これらは全て、その全体が全ての目的のために参照により本明細書に組み込まれる。
研究によると、信頼する友人にアドバイスを求める消費者は、実際に購入に至る可能性が高いだけではなく、自身の購買経験をより楽しんでいる。顧客とその友人を引き込むため、本発明のシステムは、追加の“ソーシャル・オファー”が可能であり、これは顧客の友人によって共有されるものであって、これにより、小売業者の顧客基盤のバイラルな拡大をもたらすことができる。購買に関するコミュニケーションを促すため、発明のシステムは、顧客による、店、商品、および購買に関連するソーシャル・ネットワーク活動に対してポイントを与えることができる。
図1を参照すると、本発明のシステムはサーバ201を備えており、これはインターネット222、携帯電話網219、LAN、Wi‐Fiなどを含む1つ以上のネットワークを介して、消費者が所有する携帯機器101と通信する。サーバは、ソフトウェアのダウンロード、および上記システムのオファー/リワード/ソーシャル・ネットワーク機能を含む様々なサービスを提供することができる。上記機能を実行するため、システムサーバ201は、いくつかのデータベース203に接続されており、その中には、顧客データベース、購買データベース、店舗データベース、オファー・データベースなどを含むことができる。消費者は、システム会員になると、アプリケーション・サーバ201により提供される必要なソフトウェアを、電話機101にダウンロードする。ユーザは、ユーザの携帯機器101に対応したシステム・アプリケーションを、ソフトウェアを通して閲覧し、選択することができる。ソフトウェアが選択されると、サーバ201は、ソフトウェア・データベース203にアクセスして、そのソフトウェアを伝送する。電話機101はコンピュータ115に接続することができ、これは、オペレーティング・システム316およびソフトウェア318を実行するマイクロプロセッサ314と、ソフトウェアおよびデータを格納するメモリ320とを備えている。一実施形態において、システムソフトウェアは、ユーザのコンピュータ115にネットワークを介してダウンロードすることができる。あるいは、ソフトウェアは、携帯機器のグラフィカル・ユーザ・インタフェースを利用して、携帯電話網で携帯機器101に直接送信することができる。
図1を参照すると、ルールエンジン117は、システムサーバ201の一部であり、消費者に提供されるオファーおよび割引を管理する。ルールエンジン117は、インタフェースの背後にあるソフトウェアおよびプログラミングであり、これは、アプリケーションの実行中もしくは認証中のどちらか、または累積システムポイントの交換の時点で、システムユーザに物理的に表示される。
本発明のシステムは、柔軟性があり、記載したタスクのいずれかを実行するように構成することができる。本発明のシステムの典型的な実施形態は、顧客が入店するためのインセンティブであるオファーおよび割引を単に提供するためのものとすることができる。例えば、顧客は特定の商品を必要とすることがあり、この場合、顧客は店に入って、システムプログラム識別情報を提供する。一実施形態では、この情報は、消費者が店に入るときに自身の携帯電話機でボタンを押すことによって、消費者により送信することができる。あるいは、会員の識別情報は、携帯電話番号、クレジット/デビット/ストアカード番号、ストア・ロイヤルティ・カードなどにより提供することができる。識別プロセスを簡単化するため、カードから識別情報を読み取るためにカードリーダを利用することができる。
Claims (72)
- 存在指示子を送信する方法であって、
位置に関連付けられた識別子を生成し、
超音波信号送信機を用いて、オープンエア環境において前記識別子を送信する
方法。 - 前記識別子の暗号化をさらに含む請求項1に記載の方法。
- 前記識別子は時間的に変化する成分を含む請求項1に記載の方法。
- リアルタイム・クロックを用いて、前記時間的に変化する成分の調整を、さらに含む請求項3に記載の方法。
- 前記時間的に変化する成分を調整するためのブロードキャスト時刻信号の受信を、さらに含む請求項3に記載の方法。
- 前記時間的に変化する成分はナンスを含んでいる請求項3に記載の方法。
- 前記時間的に変化する成分は時間の刻印を含んでいる請求項3に記載の方法。
- 前記時間的に変化する成分は循環鍵を含んでいる請求項3に記載の方法。
- 前記位置は小売店に関連付けられている請求項1に記載の方法。
- 前記位置は前記小売店内の売り場に関連付けられている請求項9に記載の方法。
- 前記識別子は、サーバから受信した成分に関連付けられている請求項1に記載の方法。
- チャレンジを受信し、このチャレンジに対するレスポンスの返信を、さらに含む請求項1に記載の方法。
- 前記超音波信号送信機を用いて、前記オープンエア環境において前記識別子を送信することは、周波数偏移変調を用いた前記識別子の送信を含む請求項1に記載の方法。
- 前記超音波信号送信機を用いて、前記オープンエア環境において前記識別子を送信することは、位相偏移変調を用いた前記識別子の送信を含む請求項1に記載の方法。
- 前記超音波信号送信機を用いて、前記オープンエア環境において前記識別子を送信することは、振幅偏移変調を用いた前記識別子の送信を含む請求項1に記載の方法。
- 前記超音波信号送信機を用いて、前記オープンエア環境において前記識別子を送信することは、多重周波数シグナリングを用いた前記識別子の送信を含む請求項1に記載の方法。
- 前記多重周波数シグナリングはスペクトル拡散通信を含む請求項16に記載の方法。
- 前記識別子は、ソースデータから計算された誤り訂正符号を含む請求項1に記載の方法。
- 前記誤り訂正符号はターボ符号である請求項18記載の方法。
- 前記誤り訂正符号は畳み込み符号である請求項18記載の方法。
- 前記誤り訂正符号はリード・ソロモン符号である請求項18に記載の方法。
- 前記識別子は、ソースデータから計算された誤り検出符号を含む請求項1に記載の方法。
- 前記誤り検出符号は、巡回冗長検査を含む請求項22に記載の方法。
- 前記超音波信号送信機は、トランスデューサを含む請求項1に記載の方法。
- 前記超音波信号送信機は、19KHzから22KHzの間の少なくとも1つの周波数を用いて送信する請求項1に記載の方法。
- 存在指示子を送信するためのシステムであって、
オープンエア環境において19KHz超の周波数で信号を伝送することができる超音波トランスデューサと、
位置に関連付けられた識別子に対応する超音波信号であって、19KHz超の少なくとも1つの周波数を含む超音波信号を生成するように構成された信号発生器と
を備えるシステム。 - 前記超音波トランスデューサは、圧電トランスデューサである請求項26に記載のシステム。
- 前記信号発生器はプログラマブル・プロセッサを含み、このプログラマブル・プロセッサは前記識別子に対応する波形を生成するように構成されている請求項26に記載のシステム。
- 前記信号発生器はメモリを含み、このメモリは前記識別子に対応する波形に関するデータを保存する請求項26に記載のシステム。
- 前記識別子を暗号化するように構成された暗号器をさらに備える請求項26に記載のシステム。
- リアルタイム・クロックをさらに備える請求項26に記載のシステム。
- 時変成分発生器をさらに備え、前記識別子は、前記時変符号発生器により生成される成分であって時間的に変化する成分を含む請求項26に記載のシステム。
- 時刻受信機をさらに備える請求項26に記載のシステム。
- 前記位置は小売店に関連付けられている請求項26に記載のシステム。
- 前記位置は前記小売店内の売り場に関連付けられている請求項34に記載のシステム。
- 前記識別子は、ネットワーク・インタフェースにより受信した受信成分に関連付けられている請求項26に記載のシステム。
- 前記プロセッサは、さらに、チャレンジを受信し、このチャレンジに対するレスポンスを返信するように構成されている請求項28に記載のシステム。
- 前記信号発生器は、周波数偏移変調を用いて前記識別子を生成するように構成されている請求項26に記載のシステム。
- 前記信号発生器は、位相偏移変調を用いて前記識別子を生成するように構成されている請求項26に記載のシステム。
- 前記信号発生器は、振幅偏移変調を用いて前記識別子を生成するように構成されている請求項26に記載のシステム。
- 前記信号発生器は、多重周波数シグナリングを用いて前記識別子を生成するように構成されている請求項26に記載のシステム。
- 前記多重周波数シグナリングは、スペクトル拡散通信を含む請求項41に記載のシステム。
- 誤り訂正符号発生器をさらに備え、前記識別子は誤り訂正符号を含み、前記誤り訂正符号発生器は、ソースデータから前記誤り訂正符号を計算するように構成されている請求項26に記載のシステム。
- 前記誤り訂正符号は、ターボ符号である請求項43に記載のシステム。
- 前記誤り訂正符号は、畳み込み符号である請求項43に記載のシステム。
- 前記誤り訂正符号は、リード・ソロモン符号である請求項43に記載のシステム。
- 誤り検出符号発生器をさらに備え、前記識別子は誤り検出符号を含み、前記誤り検出符号発生器は、ソースデータから前記誤り検出符号を計算するように構成されている請求項26に記載のシステム。
- 前記誤り検出符号は、巡回冗長検査を含む請求項47に記載のシステム。
- 存在指示子を受信する方法であって、
オープンエア環境において、マイクロフォンを用いて、19KHz超の少なくとも1つの周波数を含む超音波信号を受信し、
前記超音波信号に符号化された識別子を復号化し、
前記識別子に関連付けられている位置における存在を推定する
方法。 - 携帯電話機において実行される請求項49に記載の方法。
- 前記識別子を復号化することは、前記超音波信号に関連するデータのサーバへの送信と、前記サーバからの応答の受信とを含む請求項49に記載の方法。
- 前記識別子を復号化することは、周波数偏移変調の復号化を含む請求項49に記載の方法。
- 前記識別子を復号化することは、位相偏移変調の復号化を含む請求項49に記載の方法。
- 前記識別子を復号化することは、振幅偏移変調の復号化を含む請求項49に記載の方法。
- 前記識別子を復号化することは、多重周波数シグナリングの復号化を含む請求項49に記載の方法。
- 前記多重周波数シグナリングを復号化することは、スペクトル拡散通信を含む請求項55に記載の方法。
- 前記識別子に誤り訂正符号を適用することを、さらに含む請求項49に記載の方法。
- 前記誤り訂正符号は、ターボ符号を含む請求項57に記載の方法。
- 前記誤り訂正符号は、畳み込み符号を含む請求項57に記載の方法。
- 前記誤り訂正符号は、リード・ソロモン符号を含む請求項57に記載の方法。
- 前記識別子に誤り検出符号を適用することを、さらに含む請求項49に記載の方法。
- 前記誤り検出符号は、巡回冗長検査を含む請求項61に記載の方法。
- 前記位置は小売店に関連付けられている請求項49に記載の方法。
- 前記位置は前記小売店内の売り場に関連付けられている請求項63に記載の方法。
- 前記識別子の暗号を復号することをさらに含む請求項49に記載の方法。
- 前記識別子からの時変成分の抽出と、前記時変成分が許容可能であることの確認とを、さらに含む請求項49に記載の方法。
- 前記時変成分が許容可能であることを確認することは、クロック・スキューの許容を含む請求項66に記載の方法。
- 前記時変成分が許容可能であることを確認することは、非同期化したクロックの検出と、この非同期化したクロックの補正とを含む請求項66に記載の方法。
- チャレンジの送信と、前記チャレンジに対するレスポンスの受信と、前記チャレンジに対する前記レスポンスが許容可能であることの確認とを、さらに含む請求項49に記載の方法。
- 前記超音波信号は、22KHz未満の少なくとも1つの周波数を含む請求項49に記載の方法。
- 前記位置における存在の推定に応じたリワードの提供を、さらに含む請求項49に記載の方法。
- 前記位置における存在の推定に応じた個人化された割引の提供を、さらに含む請求項49に記載の方法。
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| RU2012107430A (ru) | 2013-09-10 |
| US20110029364A1 (en) | 2011-02-03 |
| JP2016174394A (ja) | 2016-09-29 |
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| KR20120049306A (ko) | 2012-05-16 |
| US8489112B2 (en) | 2013-07-16 |
| US20210166257A1 (en) | 2021-06-03 |
| US9159066B2 (en) | 2015-10-13 |
| US11507968B2 (en) | 2022-11-22 |
| US20110029362A1 (en) | 2011-02-03 |
| US20110029370A1 (en) | 2011-02-03 |
| US9886696B2 (en) | 2018-02-06 |
| WO2011014292A1 (en) | 2011-02-03 |
| US20110028160A1 (en) | 2011-02-03 |
| CN102713955A (zh) | 2012-10-03 |
| EP2460126A4 (en) | 2014-09-24 |
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