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I-Corps: Business Analytics for Large Scale Intelligence

I-Corps: Business Analytics for Large Scale Intelligence
I-Corps:大规模智能业务分析
批准号:
1530914
负责人:
Yung-Hsiang Lu
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-04-15 至 2016-09-30

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中文摘要
翻译
在过去的20年里,传统的“实体”商店一直在努力寻找与在线商店竞争的策略,以了解顾客的行为和偏好。在线商店可以根据顾客购买和看到的东西轻松创建个性化广告。相比之下,传统商店没有这些信息,无法提供个性化的体验,吸引顾客进入商店,并鼓励顾客在商店后购买。通过调查、焦点小组、店内观察员、销售记录和市场趋势来了解客户当前的需求。调查和焦点小组的成本很高,而且会扰乱客户的购买过程。店内观察员是劳动密集型的,不能同时记录许多顾客的活动。销售记录显示销售了什么,而没有任何关于客户购买或不购买产品的原因的信息。该研究小组创建了大规模智能商业分析(BALSI)系统,该系统允许零售商制作实时、动态和个性化的广告和促销活动,以吸引顾客进入商店。BALSI系统通过对店内摄像头系统的视频流进行视觉分析来观察购物者的行为、动作、目光和其他动作。从这些数据中,可以挖掘信息,帮助零售商更好地吸引、留住和满足客户。BALSI的软件解决方案在不干扰顾客的情况下分析商店中捕获的视频,也不需要任何额外的员工。该软件将分析客户的特点,向客户呈现趋势和模式,并创建动态广告,以吸引客户进入商店。在店内,该软件可以自适应地尝试增加购物者购买的可能性。BALSI的软件还通过提醒店员帮助似乎在找东西的顾客来增强销售人员的能力。这项技术不识别人脸,与那些试图在零售区域追踪顾客手机信号的技术相比,它提供了更好的隐私保护。
英文摘要
For the last 20 years, traditional "brick-and-mortar" stores have been trying to find strategies to compete with on-line store in understanding customers' behaviors and preferences. An on-line store can easily create personalized advertisements, based on what a customer has purchased and seen. In contrast, traditional stores do not have such information and cannot provide personalized experience attracting customers into the stores and encouraging customers to buy after they are in the stores. Understanding customers' needs are currently met by surveys, focus groups, in-store observers, sales records, and market trends. Surveys and focus groups are costly and disrupt customers' buying process. In-store observers are labor-intensive and cannot record many customers' activities at once. Sales records show what has been sold, without any information about why customers do or do not purchase products. This research team has created the Business Analytics for Large-Scale Intelligence (BALSI) system that allows retailers to make real time, dynamic, and personalized advertisements and promotions to attract customers into the stores.The BALSI system uses visual analysis of video stream from in-store camera systems to observe a shopper's behavior, movement, gaze and other actions. From such data, information can be mined to help the retailer better attract, retain, and satisfy customers. BALSI's software solution analyzes the videos captured in stores without interfering with the customers and does not require any additional employees. The software will analyze the characteristics of customers to presents trends and patterns to the clients and to create dynamic advertisements to attract the customers into stores. Inside the store, the software can adaptively try to increase the likelihood of a purchase by a shopper. BALSI's software also augments human sales people by alerting a store associate to help a customer that appears to be looking for something. The technology does not recognize faces and offers better privacy protection when compared with technologies that attempt do similar things within the retail area by tracking the signals coming from a customer's phone.
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Collaborative Research: OAC Core: Advancing Low-Power Computer Vision at the Edge
  • 批准号:
    2107230
  • 项目类别:
    Standard Grant
  • 资助金额:
    $25.0万
  • 财政年份:
    2021
  • 负责人:
    Yung-Hsiang Lu
  • 依托单位:
Collaborative Research: CCRI:NEW: Research Infrastructure for Real-Time Computer Vision and Decision Making via Mobile Robots
  • 批准号:
    2120430
  • 项目类别:
    Standard Grant
  • 资助金额:
    $91.97万
  • 财政年份:
    2021
  • 负责人:
    Yung-Hsiang Lu
  • 依托单位:
CDSE: Collaborative: Cyber Infrastructure to Enable Computer Vision Applications at the Edge Using Automated Contextual Analysis
  • 批准号:
    2104709
  • 项目类别:
    Standard Grant
  • 资助金额:
    $22.5万
  • 财政年份:
    2021
  • 负责人:
    Yung-Hsiang Lu
  • 依托单位:
Collaborative:RAPID:Leveraging New Data Sources to Analyze the Risk of COVID-19 in Crowded Locations.
  • 批准号:
    2027524
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.0万
  • 财政年份:
    2020
  • 负责人:
    Yung-Hsiang Lu
  • 依托单位:
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