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Capturing and analyzing data from SensorSuite's sevices using big data analytics techniques

Capturing and analyzing data from SensorSuite's sevices using big data analytics techniques
使用大数据分析技术从 SensorSuite 服务捕获和分析数据
批准号:
477440-2014
负责人:
Raahemi, Bijan
金额:
$1.82万
依托单位:
依托单位国家:
加拿大
项目类别:
Engage Grants Program
财政年份:
2014
资助国家:
加拿大
项目状态:
已结题
起止时间:
2014-01-01 至 2015-12-31

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中文摘要
翻译
Sensorsuite公司参与设计和制造交钥匙,低成本无线传感器和软件解决方案,专注于中小型多住宅和商业市场。该公司的解决方案捕获、处理并向物业管理人员和业主提供实时信息。
英文摘要
Sensorsuite company is involved in the design and manufacturing of turnkey, low cost wireless sensor and software solutions, focused on medium-to-small size multi-residential and commercial markets. The company's solutions capture, process and deliver real-time information to property managers and building owners.
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Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
  • 批准号:
    RGPIN-2017-04192
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $3.5万
  • 财政年份:
    2021
  • 负责人:
    Raahemi, Bijan
  • 依托单位:
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
  • 批准号:
    RGPIN-2017-04192
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2020
  • 负责人:
    Raahemi, Bijan
  • 依托单位:
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
  • 批准号:
    RGPIN-2017-04192
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2019
  • 负责人:
    Raahemi, Bijan
  • 依托单位:
Outlier Detection in High-Dimensional Big Data using Bio-Inspired Methods for Emerging Applications in Engineering, Healthcare, and Business
  • 批准号:
    RGPIN-2017-04192
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2018
  • 负责人:
    Raahemi, Bijan
  • 依托单位:
国内基金
海外基金
Computational Methods for Analyzing Toponome Data