Intelligent bluetooth beacon I/O expansion system
    22.
    发明申请
    Intelligent bluetooth beacon I/O expansion system 审中-公开
    智能蓝牙信标I / O扩展系统

    公开(公告)号:US20170031840A1

    公开(公告)日:2017-02-02

    申请号:US14756054

    申请日:2015-07-27

    Applicant: Geotab Inc.

    Abstract: Apparatus, methods and system relating to a vehicular telemetry environment for an intelligent Bluetooth beacon I/O expansion of the vehicular telemetry hardware system. The intelligent Bluetooth beacon I/O expansion provides a capability to receive beacon data, log beacon data, communicate beacon data and operate on beacon data to determine and further communicate a range of operational conditions, such as damage, hazardous and missing objects in the form of text messages, audio messages or compliance and management reports.

    Abstract translation: 用于车载遥测硬件系统的智能蓝牙信标I / O扩展的车辆遥测环境的装置,方法和系统。 智能蓝牙信标I / O扩展提供接收信标数据,记录信标数据,传送信标数据和操作信标数据的能力,以确定并进一步传达一系列操作条件,例如损坏,危险和丢失的对象 的短信,音频消息或合规性和管理报告。

    EXTREMA-RETENTIVE DATA BUFFERING AND SIMPLIFICATION

    公开(公告)号:US20220166813A1

    公开(公告)日:2022-05-26

    申请号:US17194659

    申请日:2021-03-08

    Applicant: Geotab Inc.

    Abstract: Methods and devices for asset tracking are provided. An example method involves obtaining a stream of raw data, adding data points from the stream of raw data to a data buffer in a first cycle of data, performing a dataset simplification algorithm on the first cycle of data to determine whether one or more data points from the first cycle of data are to be recorded, preparing the data buffer for a second cycle of data, including determining a group of carry-over data points to be included in the second cycle of data, and continuing to add data points from the stream of raw data to the data buffer in the second cycle of data.

    METHODS AND DEVICES FOR FIXED EXTRAPOLATION ERROR DATA SIMPLIFICATION PROCESSES FOR TELEMATICS

    公开(公告)号:US20220035779A1

    公开(公告)日:2022-02-03

    申请号:US17084062

    申请日:2020-10-29

    Applicant: Geotab Inc.

    Abstract: Methods and devices for simplifying data collected from assets are provided. An example method involves obtaining raw data from a data source at an asset, determining that a data logging trigger is satisfied by determining that a recently obtained point in the raw data differs from a corresponding predicted point predicted by extrapolation based on previously saved points included in one or more previously generated simplified sets of data by an amount of extrapolation error that is limited by an upper bound that is fixed as the raw data is collected over time, and, when the data logging trigger is satisfied, performing a dataset simplification algorithm on the raw data to generate a simplified set of data.

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