WO2019024383A1 - 一种体重检测装置识别用户的方法及系统 - Google Patents

一种体重检测装置识别用户的方法及系统 Download PDF

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Publication number
WO2019024383A1
WO2019024383A1 PCT/CN2017/116414 CN2017116414W WO2019024383A1 WO 2019024383 A1 WO2019024383 A1 WO 2019024383A1 CN 2017116414 W CN2017116414 W CN 2017116414W WO 2019024383 A1 WO2019024383 A1 WO 2019024383A1
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Prior art keywords
user
bluetooth
detection data
identified
smart terminal
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PCT/CN2017/116414
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English (en)
French (fr)
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曹瑾亮
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上海斐讯数据通信技术有限公司
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Publication of WO2019024383A1 publication Critical patent/WO2019024383A1/zh

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/44—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing persons
    • G01G19/50—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing persons having additional measuring devices, e.g. for height
    • G—PHYSICS
    • G08—SIGNALLING
    • G08C—TRANSMISSION SYSTEMS FOR MEASURED VALUES, CONTROL OR SIMILAR SIGNALS
    • G08C17/00—Arrangements for transmitting signals characterised by the use of a wireless electrical link
    • G08C17/02—Arrangements for transmitting signals characterised by the use of a wireless electrical link using a radio link
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/70—Services for machine-to-machine communication [M2M] or machine type communication [MTC]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W8/00—Network data management
    • H04W8/005—Discovery of network devices, e.g. terminals
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
    • H04W4/02—Services making use of location information
    • H04W4/023—Services making use of location information using mutual or relative location information between multiple location based services [LBS] targets or of distance thresholds

Definitions

  • the present invention relates to the field of health detection, and in particular to a method and system for identifying a user by a weight detecting device.
  • the weight detecting device is usually used by a plurality of users in the detection. There are issues with multi-user identification and management when generating data.
  • the electronic scale sends the data to all users, allowing users to claim it themselves.
  • the problem with this method is that if the user forgets to claim, it will result in the loss of data and cause trouble to other users.
  • the prior art performs a user identification scheme according to the user's historical weight.
  • the defect is that the identification factor is single, and it is easy for a plurality of users with similar weights to simultaneously use one device, and the misrecognition rate is relatively high.
  • the patent of the publication No. CN103263294A provides a health index parameter detector, a detecting device and a detecting system.
  • the health index parameter detecting device comprises a measuring module, a two-dimensional code generating module and a display module
  • the health indicator parameter detecting device comprises
  • the health indicator parameter detector and the mobile terminal comprise a reading unit, an analyzing unit and a display unit
  • the health indicator parameter detecting system comprises an identity verification module and a database.
  • the health indicator parameter detector, the detecting device and the detecting system provided by the invention can conveniently transmit the health index parameter information to a mobile device such as a mobile phone, and use the two-dimensional code display and the encryption verification technology to make the health indicator parameter information more secure and protect.
  • User privacy However, the invention requires scanning by a two-dimensional code, and the operation is complicated.
  • the technical problem to be solved by the present invention is to provide a method for identifying a user by a weight detecting device.
  • the method and system are used to solve the problem that the existing identification technology has a single recognition factor and a high false positive rate.
  • a method for identifying a user by a weight detecting device comprising the steps of:
  • step S2 determining whether the user can be identified by Bluetooth, and if so, sending the detection data to the corresponding smart terminal, and if not, proceeding to step S3;
  • S3. Determine whether the user can be identified by comparing the similarity of the history detection data, and if yes, send the detection data to the corresponding smart terminal.
  • step S2 the determining whether the user can be identified by using Bluetooth includes:
  • Bluetooth intelligent terminal further determining whether there are multiple Bluetooth intelligent terminals, and if not, determining that the user can be identified by Bluetooth;
  • the method further includes:
  • step S3 the determining whether the user can identify the user by comparing the similarity of the history detection data includes:
  • the historical detection data includes historical weight values, historical body fat values, and/or historical bone values.
  • a system for identifying a user by a weight detecting device comprising:
  • a Bluetooth identification module configured to determine whether the user can be identified by Bluetooth, and if so, the number of detections According to the smart terminal sent to the corresponding;
  • the similarity recognition module is configured to determine whether the user can be identified by comparing the similarity of the history detection data, and if so, determine that the user can be identified by comparing the similarity of the history detection data.
  • the Bluetooth identification module includes:
  • a scanning unit configured to scan a Bluetooth smart terminal within a preset distance
  • a first determining unit configured to determine whether a Bluetooth smart terminal exists, and if not, determine that the user cannot be identified through Bluetooth
  • a second determining unit configured to determine whether there is a plurality of Bluetooth intelligent terminals if there is a Bluetooth intelligent terminal, and if not, determine that the user can be identified by using Bluetooth;
  • a calculating unit configured to calculate a signal strength value of the multiple Bluetooth smart terminals if there are multiple Bluetooth intelligent terminals
  • the third determining unit is configured to determine whether a unique signal strength value matches the preset signal strength value, and if yes, determine that the user can be identified by Bluetooth; otherwise, it is determined that the user cannot be identified by Bluetooth.
  • the Bluetooth identification module further includes:
  • a connecting unit configured to connect with a user's smart terminal via Bluetooth
  • a setting unit configured to set a signal strength value of the smart terminal to a preset signal strength value.
  • the similarity recognition module includes:
  • the comparison unit is configured to determine whether the similarity between the detection data and the historical detection data is greater than a preset threshold, and if yes, send the detection data to the corresponding smart terminal.
  • the history detection data of the comparison unit includes a historical weight value, a historical body fat value, and/or a historical bone value.
  • the present invention has the following advantages:
  • the invention is more convenient and the user experience is better, and the recognition rate and recognition accuracy are higher than single body similarity recognition.
  • FIG. 1 is a flow chart of a method for identifying a user by a weight detecting device according to Embodiment 1;
  • FIG. 2 is a system structural diagram of a weight detecting device for identifying a user according to Embodiment 1;
  • FIG. 3 is a flow chart of a method for identifying a user by a weight detecting device according to Embodiment 2;
  • FIG. 4 is a system structural diagram of a weight detecting device for identifying a user according to Embodiment 2;
  • FIG. 5 is a flow chart of a method for identifying a user by a weight detecting device according to Embodiment 3;
  • FIG. 6 is a system structural diagram of a weight detecting device for identifying a user according to Embodiment 3.
  • This embodiment provides a method for identifying a user by a weight detecting device. As shown in FIG. 1, the method includes the following steps:
  • step S12 determining whether the user can be identified by Bluetooth, and if so, sending the detection data to the corresponding smart terminal; if not, proceeding to step S13;
  • S13 Determine whether the user can be identified by comparing the similarity of the history detection data, and if so, send the detection data to the corresponding smart terminal.
  • the weight detecting device includes a body fat scale, an electronic scale and the like.
  • the existing weighing method requires the user to manually obtain data information, for example, acquiring information in a smart terminal or scanning a two-dimensional code through a smart terminal. This type of operation can easily lead to data confusion or data loss.
  • This embodiment provides a series of identity automation schemes for addressing multi-user usage and management issues. It has a better user experience and efficiency than traditional methods.
  • the identity identification of the method provided in this embodiment includes two methods: one is to identify the user identity according to the physical data feature of the user, and intelligently record the measurement data; the second is to perform identity recognition with the Bluetooth intelligent terminal.
  • the basic principle of body data similarity comparison is to compare the historical measurement records of different users with the newly collected data. Since most of the body data does not change too much in a short time, according to the similarity between certain body data. Judging, it can be determined that this new data is most likely to belong to the user. The more types of body data, the more accurate the end result.
  • the principle of judging the distance by the Bluetooth signal strength and identifying and determining the identity of the measurer is: the signal strength value RSSI can be obtained when the Bluetooth smart device is connected, and the signal attenuation factor does not change much when the environment is certain, and the distance between the smart terminals can be based on The signal strength value is calculated by RSSI.
  • the user's smart terminal matches the weight detecting device at the time of detection, and the weight detecting device determines the identity of the user being measured by the distance.
  • step S11 is to generate detection data.
  • the weight detecting device After detecting that the user performs the detection, the weight detecting device generates the detection data of the user.
  • step S12 in this embodiment it is determined whether the user can be identified by Bluetooth, and if so, the detection data is sent to the corresponding smart terminal.
  • user data identification is divided into two processes, and this step implements the first process, and Bluetooth assists recognition.
  • the weight detecting device determines whether the user can be identified by Bluetooth, and if the user can be identified by Bluetooth, the detection data is transmitted to the corresponding smart terminal. That is, the smart terminal currently connected to the body weight detecting device Bluetooth.
  • step S13 if the user cannot be identified by Bluetooth, it is determined whether the similarity of the data can be detected by the comparison history, and if so, the detection data is sent to the corresponding smart terminal.
  • this step is a second step of user data identification. If the Bluetooth assisted recognition fails, historical similarity recognition is performed. The current detection data is compared with the historical data. If the user is identified by the history detection data similarity, it is determined that the identification is successful, and the detection data is sent to the corresponding intelligent terminal, that is, the smart terminal whose current similarity is similar to the historical data.
  • the identification method is more intelligent and more precise, avoiding the problem of misidentification.
  • the embodiment further provides a system for identifying a user by the weight detecting device, as shown in FIG. 2, comprising:
  • a generating module 21 configured to generate detection data
  • the Bluetooth identification module 22 is configured to determine whether the user can be identified by using Bluetooth, and if yes, send the detection data to the corresponding smart terminal;
  • the similarity identification module 23 is configured to determine whether the user can be identified by comparing the similarity of the history detection data, and if so, send the detection data to the corresponding smart terminal.
  • the generating module 21 is configured to generate detection data.
  • the generating module 21 After the weight detecting device detects that the user performs the detection, the generating module 21 generates the detection data of the user.
  • the Bluetooth identification module 22 is configured to determine whether the user can be identified by Bluetooth, and if so, send the detection data to the corresponding smart terminal.
  • the Bluetooth identification module 22 determines whether the user can be identified by Bluetooth, and if the user can be identified by Bluetooth, the detection data is sent to the corresponding smart terminal. That is, the smart terminal currently connected to the body weight detecting device Bluetooth.
  • the similarity identification module 23 is configured to determine whether the data similarity is detected by the comparison history, and if so, the detection data is sent to the corresponding smart terminal.
  • the Bluetooth identification module 22 fails to identify, the historical similarity recognition is performed.
  • the similarity identification module 23 compares the current detection data with the historical data. If the user can be identified by the historical detection data similarity, it is determined that the identification is successful, and the detection data is sent to the corresponding intelligent terminal, that is, the current similarity and historical data. A similar smart terminal.
  • the system provided in this embodiment can intelligently determine the identity of the user and realize automatic identification by multiple users during the use of the weight detecting device.
  • the similarity recognition of body history data and the method of Bluetooth detection assisted recognition are applied to reduce misidentification and become more intelligent.
  • This embodiment provides a method for identifying a user by a weight detecting device. As shown in FIG. 3, the method includes the following steps:
  • S34 Scan the Bluetooth intelligent terminal within the preset distance
  • S35 determining whether there is a Bluetooth intelligent terminal, and if not, determining that the user cannot be identified through Bluetooth;
  • S36 if there is a Bluetooth intelligent terminal, further determining whether there are multiple Bluetooth intelligent terminals, and if not, determining that the user can be identified through Bluetooth;
  • S38 determining whether there is a unique signal strength value that matches the preset signal strength value, and if so, determining In order to be able to identify the user through Bluetooth, otherwise, it is determined that the user cannot be identified through Bluetooth;
  • step S12 includes the step S32 to the step S33 before the sending of the detection data to the corresponding smart terminal, and the step of determining whether the user can identify the user by using the Bluetooth, and the step S34 to the step S38 are specifically included in the step S12. .
  • the weight detecting device can acquire the signal strength value RSSI, and set the signal strength value RSSI to the preset signal strength value RSSI.
  • the weight detecting device scans the Bluetooth intelligent terminal within the preset distance to first determine whether the Bluetooth smart terminal can be scanned. If none of them is available, it is determined that the user cannot be identified through Bluetooth; if the Bluetooth intelligent terminal is scanned, it is further determined whether there is more If the Bluetooth smart terminal scans only one Bluetooth intelligent terminal, it is determined that the user can be identified by Bluetooth, and the Bluetooth smart terminal is a preset Bluetooth intelligent terminal.
  • the signal strength value RSSI of the Bluetooth smart terminal is calculated. Determining whether only one Bluetooth intelligent terminal's signal strength value RSSI matches the preset signal strength value RSSI, and if so, it is determined that the user can be identified by Bluetooth; if there are multiple Bluetooth intelligent terminals, the signal strength values RSSI are similar, and the preset signal is If the strength value RSSI is successfully matched, it is determined that the user cannot be identified by Bluetooth.
  • the detection data is sent to the smart terminal that successfully identifies.
  • the step of comparing the similarity recognition of the history detection data is further performed.
  • the history detection data similarity recognition process can be used to streamline the user range.
  • the embodiment further provides a system for recognizing a user by the weight detecting device, as shown in FIG. 4, comprising:
  • a generating module 41 configured to generate detection data
  • the Bluetooth identification module 42 is configured to determine whether the user can be identified by using Bluetooth, and if yes, send the detection data to the corresponding smart terminal;
  • the similarity identification module 43 is configured to determine whether the user can be identified by comparing the similarity of the history detection data, and if so, send the detection data to the corresponding smart terminal.
  • the Bluetooth identification module 42 includes:
  • the connecting unit 42a is configured to connect with the smart terminal of the user through Bluetooth
  • the setting unit 42b is configured to set a signal strength value of the smart terminal to a preset signal strength value
  • the scanning unit 42c is configured to scan a Bluetooth smart terminal within a preset distance
  • the first determining unit 42d is configured to determine whether there is a Bluetooth smart terminal, and if not, determine that the user cannot be identified through Bluetooth;
  • the second determining unit 42e is configured to further determine whether there are multiple Bluetooth smart terminals if there is a Bluetooth smart terminal, and if not, determine that the user can be identified by using Bluetooth;
  • the calculating unit 42f is configured to calculate a signal strength value of the multiple Bluetooth smart terminals if there are multiple Bluetooth smart terminals;
  • the third determining unit 42g is configured to determine whether a unique signal strength value matches the preset signal strength value, and if so, it is determined that the user can be identified by Bluetooth, otherwise, it is determined that the user cannot be identified by Bluetooth.
  • the weight detecting device can acquire the signal strength value RSSI, and the setting unit 42b sets the signal strength value RSSI to the preset signal strength value RSSI.
  • the weight detecting device in the scanning unit 42c scans the Bluetooth intelligent terminal within the preset distance, and the first determining module 42d first determines whether the Bluetooth smart terminal can be scanned. If none of them is available, it is determined that the user cannot be identified through Bluetooth; if the Bluetooth is scanned The smart terminal, the second determining unit 42e further determines whether there are multiple Bluetooth smart terminals. If only one Bluetooth smart terminal is scanned, it is determined that the user can be identified by Bluetooth, and the Bluetooth smart terminal is a preset Bluetooth smart terminal.
  • the calculating unit 42f calculates the signal strength value RSSI of the Bluetooth smart terminal.
  • the third determining unit 42g determines whether only the signal strength value RSSI of one Bluetooth intelligent terminal matches the preset signal strength value RSSI, and if so, determines that the user can be identified by Bluetooth; if the signal strength values RSSI of multiple Bluetooth intelligent terminals are similar, If the match with the preset signal strength value RSSI is successful, it is determined that the user cannot be identified by Bluetooth.
  • the weight detecting device transmits the detection data to the smart terminal capable of recognizing the user via Bluetooth, if not Further identification of the similarity can be performed by recognizing the user's smart terminal via Bluetooth.
  • This embodiment provides a method for identifying a user by a weight detecting device. As shown in FIG. 5, the method includes the following steps:
  • S52 determining whether the user can be identified by using Bluetooth, and if yes, sending the detection data to the corresponding smart terminal;
  • S53 If the user cannot be identified by Bluetooth, it is determined whether the similarity between the detected data and the historical detection data is greater than a preset threshold, and if so, it is determined that the user can be identified by comparing the similarity of the history detection data.
  • the historical detection data includes historical weight value, historical body fat value and/or historical bone value.
  • step S13 determining whether the user can be identified by comparing the similarity of the history detection data includes: determining whether the similarity between the detection data and the history detection data is greater than a preset threshold, and if greater than a preset threshold, It is determined that the detection data is similar to the preset detection data, and the detection data is transmitted to the smart terminal of the similar detection data. If it is less than or equal to the preset threshold, it is determined that the preset detection data is not similar, and the process of manually claiming the data is entered.
  • the embodiment further provides a system for recognizing a user by the weight detecting device, as shown in FIG. 6, comprising:
  • a generating module 61 configured to generate detection data
  • the Bluetooth identification module 62 is configured to determine whether the user can be identified by using Bluetooth, and if yes, send the detection data to the corresponding smart terminal;
  • the similarity identification module 63 is configured to determine whether the user can be identified by the similarity of the comparison history detection data if the user cannot be identified by Bluetooth, and if so, determine that the user can be identified by comparing the similarity of the history detection data.
  • the similarity recognition module 63 includes:
  • the comparing unit 63a is configured to determine whether the similarity between the detected data and the historical detection data is greater than a preset threshold, and if yes, send the detected data to the corresponding smart terminal.
  • the comparison unit 63a determines whether the similarity between the detection data and the history detection data is greater than a preset threshold. If it is greater than the preset threshold, it is determined to be similar to the preset detection data, and the detection data is sent to the phase. An intelligent terminal that looks like data. If it is less than or equal to the preset threshold, it is determined that the preset detection data is not similar, and the process of manually claiming the data is entered.

Abstract

本发明公开了一种体重检测装置识别用户的方法及系统，用以解决现有的识别技术识别因子单一，误识率较高的问题。该方法包括：S1、生成检测数据；S2、判断是否能通过蓝牙识别用户，若是，将所述检测数据发送至对应的智能终端，若否，进入步骤S3；S3、判断是否能通过比对历史检测数据相似度识别用户，若是，将所述检测数据发送至对应的智能终端。比起用户认领数据的方法或者登陆的方法，本发明更加便捷，用户体验更好，比起单一体重相似度识别，识别率和识别精度更高。

Description

一种体重检测装置识别用户的方法及系统 技术领域
本发明涉及健康检测领域，尤其涉及一种体重检测装置识别用户的方法及系统。
背景技术
体重检测装置在检测中通常会有多个用户使用。产生数据时会面临多用户识别和管理的问题。
传统方式有两种：
一是每次使用电子秤的时候现在设备上进行登录，这种方式用户操作繁琐，如果更换用户，忘记重新登录会导致数据错乱；
二是电子秤将数据发给所有用户，让用户自己认领，这种方式存在的问题是如果用户以遗忘认领，会导致数据的丢失，对其他用户造成困扰。
现有技术根据用户的历史体重进行用户识别的方案，缺陷是识别因子单一，很容易出现多个体重相近的用户同时使用一个设备，这时候误识率比较高。
公开号为CN103263294A的专利提供了一种健康指标参数检测仪、检测装置和检测系统，所述健康指标参数检测仪包括测量模块、二维码生成模块、显示模块，所述健康指标参数检测装置包括所述健康指标参数检测仪和移动终端，所述移动终端包括读取单元、解析单元和显示单元，所述健康指标参数检测系统包括身份验证模块和数据库。该发明提供的健康指标参数检测仪、检测装置和检测系统可以方便的将健康指标参数信息传输到手机等移动设备，利用二维码显示以及加密验证等技术使得健康指标参数信息更加安全，保护了用户隐私。但是该发明需要通过二维码扫描，操作复杂。
发明内容
本发明要解决的技术问题目的在于提供一种体重检测装置识别用户的方 法及系统，用以解决现有的识别技术识别因子单一，误识率较高的问题。
为了实现上述目的，本发明采用的技术方案为：
一种体重检测装置识别用户的方法，包括步骤：
S1、生成检测数据；
S2、判断是否能通过蓝牙识别用户，若是，将所述检测数据发送至对应的智能终端，若否，进入步骤S3；
S3、判断是否能通过比对历史检测数据相似度识别用户，若是，将所述检测数据发送至对应的智能终端。
进一步地，步骤S2中，所述判断是否能通过蓝牙识别用户包括：
扫描预设距离内的蓝牙智能终端；
判断是否存在蓝牙智能终端，若否，判定不能通过蓝牙识别用户；
若存在蓝牙智能终端，进一步判断是否存在多个蓝牙智能终端，若否，判定为能通过蓝牙识别用户；
若存在多个蓝牙智能终端，计算该多个蓝牙智能终端的信号强度值；
判断是否有唯一的信号强度值与预设信号强度值匹配，若是，判定为能通过蓝牙识别用户，否则，判定为不能通过蓝牙识别用户。
进一步地，步骤S2中，所述将所述检测数据发送至对应的智能终端之前，还包括：
与用户的智能终端通过蓝牙连接；
设置所述智能终端的信号强度值为所述预设信号强度值。
进一步地，步骤S3中，所述判断是否能通过比对历史检测数据相似度识别用户包括：
判断所述检测数据与历史检测数据的相似度是否大于预设阈值，若是，则判定为能通过比对历史检测数据相似度识别用户。
进一步地，所述历史检测数据包括历史体重值，历史体脂值和/或历史骨骼值。
一种体重检测装置识别用户的系统，包括：
生成模块，用于生成检测数据；
蓝牙识别模块，用于判断是否能通过蓝牙识别用户，若是，将所述检测数 据发送至对应的智能终端；
相似度识别模块，用于判断是否能通过比对历史检测数据相似度识别用户，若是，则判定为能通过比对历史检测数据相似度识别用户。
进一步地，所述蓝牙识别模块包括：
扫描单元，用于扫描预设距离内的蓝牙智能终端；
第一判断单元，用于判断是否存在蓝牙智能终端，若否，判定不能通过蓝牙识别用户；
第二判断单元，用于若存在蓝牙智能终端，进一步判断是否存在多个蓝牙智能终端，若否，判定能通过蓝牙识别用户；
计算单元，用于若存在多个蓝牙智能终端，计算该多个蓝牙智能终端的信号强度值；
第三判断单元，用于判断是否有唯一的信号强度值与预设信号强度值匹配，若是，判定能通过蓝牙识别用户，否则，判定不能通过蓝牙识别用户。
进一步地，所述蓝牙识别模块还包括：
连接单元，用于与用户的智能终端通过蓝牙连接；
设置单元，用于设置所述智能终端的信号强度值为预设信号强度值。
进一步地，所述相似度识别模块包括：
比对单元，用于判断所述检测数据与历史检测数据的相似度是否大于预设阈值，若是，将所述检测数据发送至对应的智能终端。
进一步地，所述比对单元的历史检测数据包括历史体重值，历史体脂值和/或历史骨骼值。
本发明与传统的技术相比，有如下优点：
比起用户认领数据的方法或者登陆的方法，本发明更加便捷，用户体验更好，比起单一体重相似度识别，识别率和识别精度更高。
附图说明
图1是实施例一提供的一种体重检测装置识别用户的方法流程图；
图2是实施例一提供的一种体重检测装置识别用户的系统结构图；
图3是实施例二提供的一种体重检测装置识别用户的方法流程图；
图4是实施例二提供的一种体重检测装置识别用户的系统结构图；
图5是实施例三提供的一种体重检测装置识别用户的方法流程图；
图6是实施例三提供的一种体重检测装置识别用户的系统结构图。
具体实施方式
以下是本发明的具体实施例并结合附图，对本发明的技术方案作进一步的描述，但本发明并不限于这些实施例。
实施例一
本实施例提供了一种体重检测装置识别用户的方法，如图1所示，包括步骤：
S11：生成检测数据；
S12：判断是否能通过蓝牙识别用户，若是，将检测数据发送至对应的智能终端；若否，进入步骤S13；
S13：判断是否能通过比对历史检测数据相似度识别用户，若是，将检测数据发送至对应的智能终端。
体重检测装置包括体脂秤，电子秤等设备。
现有的称量方法需要用户手动获取数据信息，例如，在智能终端登录或者通过智能终端扫描二维码的方式获取数据信息。这种方式操作易导致数据错乱或者数据丢失的问题。
本实施例提供一系列身份识别自动化方案用于解决多用户使用和管理问题。相比传统方式有着更好的用户体验和使用效率。
本实施例提供的方法的身份识别包括两种方式：一是根据用户的身体数据特征对用户身份进行识别，智能记录测量数据；二是配合蓝牙智能终端进行身份识别。
身体数据相似度比对的基本原理是根据不同用户的历史测量记录和新采集到的数据进行比对，由于大部分身体数据短时间不会变化太大，根据某种身体数据之间的相似度判断，可以确定这个新数据最可能属于用户。身体数据种类越多，最终结果越准确。
通过蓝牙信号强度判断距离，识别判断测量者身份的原理是：蓝牙智能设备连接时可以获取信号强度值RSSI，在环境一定的情况下，信号衰减因子变化不大，智能终端间的距离时可以根据信号强度值RSSI计算的。用户的智能终端在检测时会匹配到体重检测装置，体重检测装置通过距离判断出正在测量的用户身份。
本实施例中，步骤S11为生成检测数据。
具体的，体重检测装置检测到用户进行检测后，生成用户的检测数据。
本实施例中步骤S12为判断是否能通过蓝牙识别用户，若是，将检测数据发送到对应的智能终端。
具体的，用户数据识别分为两个过程，本步骤实现第一个过程，蓝牙辅助识别。当产生检测数据后，体重检测装置判断能否通过蓝牙识别用户，若能够通过蓝牙识别用户，则将检测数据发送至对应的智能终端。即，当前与体重能检测装置蓝牙连接的智能终端。
本实施例中，步骤S13为若不能通过蓝牙识别用户，判断是否能通过对比历史检测数据相似度是被用户，若是，将检测数据发送至对应的智能终端。
具体的，本步骤为用户数据识别的第二个步骤，若蓝牙辅助识别失败，则进行历史相似度识别。将当前检测数据与历史数据进行比对，若能通过历史检测数据相似度识别用户，则判定为识别成功，将检测数据发送至对应的智能终端，即当前相似度与历史数据相似的智能终端。
通过蓝牙辅助识别和历史相似度识别，只要任意一项识别成功就可以达到自动是被的目的，如果都失败，就进入用户手动认领数据的流程。识别方式更加智能，并且更加精准，避免了误识别的问题。
本实施例还提供了一种体重检测装置识别用户的系统，如图2所示，包括：
生成模块21，用于生成检测数据；
蓝牙识别模块22，用于判断是否能通过蓝牙识别用户，若是，将检测数据发送至对应的智能终端；
相似度识别模块23，用于判断是否能通过比对历史检测数据相似度识别用户，若是，将检测数据发送至对应的智能终端。
本实施例中，生成模块21用于生成检测数据。
具体的，体重检测装置检测到用户进行检测后，生成模块21生成用户的检测数据。
本实施例中，蓝牙识别模块22用于判断是否能通过蓝牙识别用户，若是，将检测数据发送到对应的智能终端。
具体的，当产生检测数据后，蓝牙识别模块22判断能否通过蓝牙识别用户，若能够通过蓝牙识别用户，则将检测数据发送至对应的智能终端。即，当前与体重能检测装置蓝牙连接的智能终端。
本实施例中，相似度识别模块23用于判断是否能通过对比历史检测数据相似度是被用户，若是，将检测数据发送至对应的智能终端。
具体的，若蓝牙识别模块22识别失败，则进行历史相似度识别。相似度识别模块23将当前检测数据与历史数据进行比对，若能通过历史检测数据相似度识别用户，则判定为识别成功，将检测数据发送至对应的智能终端，即当前相似度与历史数据相似的智能终端。
本实施例提供的系统功能上能一种智能判断用户身份，实现体重检测装置使用过程中的多用户自动识别。技术上应用了身体历史数据的相似度识别，蓝牙检测辅助识别的方法，减少误识别，更加智能化。
实施例二
本实施例提供了一种体重检测装置识别用户的方法，如图3所示，包括步骤：
S31：生成检测数据；
S32：与用户的智能终端通过蓝牙连接；
S33：设置智能终端的信号强度值为预设信号强度值；
S34：扫描预设距离内的蓝牙智能终端；
S35：判断是否存在蓝牙智能终端，若否，判定为不能通过蓝牙识别用户；
S36：若存在蓝牙智能终端，进一步判断是否存在多个蓝牙智能终端，若否，判定为能通过蓝牙识别用户；
S37：若存在多个蓝牙智能终端，计算该多个蓝牙智能终端的信号强度值；
S38：判断是否有唯一的信号强度值与预设信号强度值匹配，若是，判定 为能通过蓝牙识别用户，否则，判定为不能通过蓝牙识别用户；
S39：若能通过蓝牙识别用户，将检测数据发送至对应的智能终端；
S40：若不能通过蓝牙识别用户，判断是否能通过比对历史检测数据相似度识别用户，若是，将检测数据发送至对应的智能终端。
本实施例与实施例一不同之处在于，步骤S12中将检测数据发送至对应的智能终端之前还包括步骤S32～步骤S33；步骤S12中判断是否能通过蓝牙识别用户具体包括步骤S34～步骤S38。
具体的，智能终端与体重检测装置通过蓝牙连接时体重检测装置可以获取信号强度值RSSI，将该信号强度值RSSI设为预设信号强度值RSSI。
体重检测装置扫描预设距离内的蓝牙智能终端，先判断是否能扫描到蓝牙智能终端，若一个都没有，则判定为不能通过蓝牙识别用户；若扫描到蓝牙智能终端，则进一步判定是否存在多个蓝牙智能终端，若只扫描到一个蓝牙智能终端，则判定为能通过蓝牙识别用户，该蓝牙智能终端为预设蓝牙智能终端。
若扫描到多个蓝牙智能终端，计算蓝牙智能终端的信号强度值RSSI。判断是否只有一个蓝牙智能终端的信号强度值RSSI与预设信号强度值RSSI匹配，若是，判定为能通过蓝牙识别用户；若有多个蓝牙智能终端的信号强度值RSSI相似，都与预设信号强度值RSSI匹配成功，则判定为不能通过蓝牙识别用户。
能通过蓝牙识别用户后，将检测数据发送至识别成功的智能终端。
若不能通过蓝牙识别用户，则进一步进行比对历史检测数据相似度识别的步骤。
若用户没有携带智能终端时，或者测量时有多个用户携带智能终端且距离体重检测装置的位置相差不大，会影响蓝牙识别流程的判断，进入历史检测数据相似度识别流程。在多个用户都符合蓝牙识别要求的情况下，进行历史检测数据相似度识别可以对用户范围进行一次精简。
本实施例还提供了一种体重检测装置识别用户的系统，如图4所示，包括：
生成模块41，用于生成检测数据；
蓝牙识别模块42，用于判断是否能通过蓝牙识别用户，若是，将检测数据发送至对应的智能终端；
相似度识别模块43，用于判断是否能通过比对历史检测数据相似度识别用户，若是，将检测数据发送至对应的智能终端。
与实施例一不同之处在于，蓝牙识别模块42包括：
连接单元42a，用于与用户的智能终端通过蓝牙连接；
设置单元42b，用于设置智能终端的信号强度值为预设信号强度值；
扫描单元42c，用于扫描预设距离内的蓝牙智能终端；
第一判断单元42d，用于判断是否存在蓝牙智能终端，若否，判定为不能通过蓝牙识别用户；
第二判断单元42e，用于若存在蓝牙智能终端，进一步判断是否存在多个蓝牙智能终端，若否，判定为能通过蓝牙识别用户；
计算单元42f，用于若存在多个蓝牙智能终端，计算该多个蓝牙智能终端的信号强度值；
第三判断单元42g，用于判断是否有唯一的信号强度值与预设信号强度值匹配，若是，判定为能通过蓝牙识别用户，否则，判定为不能通过蓝牙识别用户。
具体的，连接单元42a中智能终端与体重检测装置通过蓝牙连接时体重检测装置可以获取信号强度值RSSI，设置单元42b将该信号强度值RSSI设为预设信号强度值RSSI。
扫描单元42c中体重检测装置扫描预设距离内的蓝牙智能终端，第一判断模块42d先判断是否能扫描到蓝牙智能终端，若一个都没有，则判定为不能通过蓝牙识别用户；若扫描到蓝牙智能终端，第二判断单元42e则进一步判定是否存在多个蓝牙智能终端，若只扫描到一个蓝牙智能终端，则判定为能通过蓝牙识别用户，该蓝牙智能终端为预设蓝牙智能终端。
若扫描到多个蓝牙智能终端，计算单元42f计算蓝牙智能终端的信号强度值RSSI。第三判断单元42g判断是否只有一个蓝牙智能终端的信号强度值RSSI与预设信号强度值RSSI匹配，若是，判定为能通过蓝牙识别用户；若有多个蓝牙智能终端的信号强度值RSSI相似，都与预设信号强度值RSSI匹配成功，则判定为不能通过蓝牙识别用户。
体重检测装置将检测数据发送至能通过蓝牙识别用户的智能终端，若没有 能通过蓝牙识别用户的智能终端，则进行进一步地相似度识别。
实施例三
本实施例提供了一种体重检测装置识别用户的方法，如图5所示，包括步骤：
S51：生成检测数据；
S52：判断是否能通过蓝牙识别用户，若是，将检测数据发送至对应的智能终端；
S53：若不能通过蓝牙识别用户，判断检测数据与历史检测数据的相似度是否大于预设阈值，若是，则判定为能通过比对历史检测数据相似度识别用户。
其中，历史检测数据包括历史体重值，历史体脂值和/或历史骨骼值。
与实施例一不同之处在于，步骤S13中，判断是否能通过比对历史检测数据相似度识别用户包括：判断检测数据与历史检测数据的相似度是否大于预设阈值，若大于预设阈值，判定为与预设检测数据相似，将检测数据发送至相似检测数据的智能终端。若小于或等于预设阈值，判定为预设检测数据不相似，进入用户手动认领数据的流程。
若自动识别都不能识别成功，此时需要用户手动认领数据。提高安全性。
本实施例还提供了一种体重检测装置识别用户的系统，如图6所示，包括：
生成模块61，用于生成检测数据；
蓝牙识别模块62，用于判断是否能通过蓝牙识别用户，若是，将检测数据发送至对应的智能终端；
相似度识别模块63，用于若不能通过蓝牙识别用户，判断是否能通过比对历史检测数据相似度识别用户，若是，则判定为能通过比对历史检测数据相似度识别用户。
与实施例一不同之处在于，相似度识别模块63包括：
比对单元63a，用于判断检测数据与历史检测数据的相似度是否大于预设阈值，若是，将检测数据发送至对应的智能终端。
具体的，比对单元63a判断检测数据与历史检测数据的相似度是否大于预设阈值，若大于预设阈值，判定为与预设检测数据相似，将检测数据发送至相 似检测数据的智能终端。若小于或等于预设阈值，判定为预设检测数据不相似，进入用户手动认领数据的流程。
当蓝牙识别以及相似度识别都不能成功时，用户需要手动读取数据。提高了安全性，避免了隐私的泄露。
本文中所描述的具体实施例仅仅是对本发明精神作举例说明。本发明所属技术领域的技术人员可以对所描述的具体实施例做各种各样的修改或补充或采用类似的方式替代，但并不会偏离本发明的精神或者超越所附权利要求书所定义的范围。

Claims (10)

  1. 一种体重检测装置识别用户的方法，其特征在于，包括步骤：
    S1、生成检测数据；
    S2、判断是否能通过蓝牙识别用户，若是，将所述检测数据发送至对应的智能终端，若否，进入步骤S3；
    S3、判断是否能通过比对历史检测数据相似度识别用户，若是，将所述检测数据发送至对应的智能终端。
  2. 根据权利要求1所述的一种体重检测装置识别用户的方法，其特征在于，步骤S2中，所述判断是否能通过蓝牙识别用户包括：
    扫描预设距离内的蓝牙智能终端；
    判断是否存在蓝牙智能终端，若否，判定为不能通过蓝牙识别用户；
    若存在蓝牙智能终端，进一步判断是否存在多个蓝牙智能终端，若否，判定为能通过蓝牙识别用户；
    若存在多个蓝牙智能终端，计算该多个蓝牙智能终端的信号强度值；
    判断是否有唯一的信号强度值与预设信号强度值匹配，若是，判定为能通过蓝牙识别用户，否则，判定为不能通过蓝牙识别用户。
  3. 根据权利要求2所述的一种体重检测装置识别用户的方法，其特征在于，步骤S2中，所述将所述检测数据发送至对应的智能终端之前，还包括：
    与用户的智能终端通过蓝牙连接；
    设置所述智能终端的信号强度值为所述预设信号强度值。
  4. 根据权利要求1所述的一种体重检测装置识别用户的方法，其特征在于，步骤S3中，所述判断是否能通过比对历史检测数据相似度识别用户包括：
    判断所述检测数据与历史检测数据的相似度是否大于预设阈值，若是，则判定为能通过比对历史检测数据相似度识别用户。
  5. 根据权利要求4所述的一种体重检测装置识别用户的方法，其特征在于，所述历史检测数据包括历史体重值，历史体脂值和/或历史骨骼值。
  6. 一种体重检测装置识别用户的系统，其特征在于，包括：
    生成模块，用于生成检测数据；
    蓝牙识别模块，用于判断是否能通过蓝牙识别用户，若是，将所述检测数 据发送至对应的智能终端；
    相似度识别模块，用于判断是否能通过比对历史检测数据相似度识别用户，若是，将所述检测数据发送至对应的智能终端。
  7. 根据权利要求6所述的一种体重检测装置识别用户的系统，其特征在于，所述蓝牙识别模块包括：
    扫描单元，用于扫描预设距离内的蓝牙智能终端；
    第一判断单元，用于判断是否存在蓝牙智能终端，若否，判定为不能通过蓝牙识别用户；
    第二判断单元，用于若存在蓝牙智能终端，进一步判断是否存在多个蓝牙智能终端，若否，判定为能通过蓝牙识别用户；
    计算单元，用于若存在多个蓝牙智能终端，计算该多个蓝牙智能终端的信号强度值；
    第三判断单元，用于判断是否有唯一的信号强度值与预设信号强度值匹配，若是，判定为能通过蓝牙识别用户，否则，判定为不能通过蓝牙识别用户。
  8. 根据权利要求7所述的一种体重检测装置识别用户的系统，其特征在于，所述蓝牙识别模块还包括：
    连接单元，用于与用户的智能终端通过蓝牙连接；
    设置单元，用于设置所述智能终端的信号强度值为预设信号强度值。
  9. 根据权利要求6所述的一种体重检测装置识别用户的系统，其特征在于，所述相似度识别模块包括：
    比对单元，用于判断所述检测数据与历史检测数据的相似度是否大于预设阈值，若是，判定为能通过比对历史检测数据相似度识别用户。
  10. 根据权利要求9所述的一种体重检测装置识别用户的系统，其特征在于，所述比对单元的历史检测数据包括历史体重值，历史体脂值和/或历史骨骼值。
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