CN117241229A - Remote data processing method for intelligent wearable equipment - Google Patents
Remote data processing method for intelligent wearable equipment Download PDFInfo
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Abstract
The application discloses a remote data processing method of intelligent wearable equipment, which particularly relates to the technical field of watches and comprises the following steps: dividing positioning data fed back by the intelligent watch into risk-free data and risk data according to the working state of the intelligent watch, reducing resource waste when the positioning data is risk-free, timely prompting a mobile terminal if the positioning data is risk-free, avoiding frequent alarming caused by data loss of the positioning data, identifying the fed back positioning data by the mobile terminal, alarming according to a preset alarming strategy when the identification result is risk-free data, redefining alarming triggering conditions according to an interval time discrete degree value and a shortest distance of a safety area when the identification result is risk data, correcting alarming conditions when the positioning data fed back by the intelligent watch are intermittently lost every time, reducing false alarming as far as possible, and improving trust and satisfaction degree of a user on the intelligent watch for children.
Description
Technical Field
The application relates to the technical field of watches, in particular to a remote data processing method of intelligent wearable equipment.
Background
The intelligent watch is intelligent wearable equipment integrating information detection and information transmission functions, has remote information processing capability, and can realize remote data transmission and reception. Its functions include display of incoming call information, multiple location services, two-way communication, etc. The characteristics make the intelligent watch a multifunctional intelligent device, is suitable for various professions and daily situations, and provides a more efficient, convenient and intelligent information processing and communication tool for users. The intelligent watch worn by the child has the greatest characteristics that the intelligent watch has a call positioning function, can acquire the geographic position information of the child in real time, transmits the geographic position information to the mobile phone end of the parent, and automatically sends out an alarm signal when the positioning data information fed back by the intelligent watch exceeds a safety area;
the intelligent watch on the current market has different degrees of difference in performance, abnormal unstable states of the intelligent watch occur in actual operation along with long-time use, the electronic device of the intelligent watch can be damaged to different degrees along with time, and under the condition that the electronic device is not replaced in time, indirect loss of feedback data of the intelligent watch can be caused, misjudgment can be made on the received uninterruptedly lost feedback data by a mobile phone terminal, frequent alarm signals are sent, dissatisfaction of a user (parents) is caused, and trust and satisfaction degree of the user to the intelligent watch for children are reduced.
In order to solve the above-mentioned defect, a technical scheme is provided.
Disclosure of Invention
In order to overcome the above-mentioned drawbacks of the prior art, an embodiment of the present application provides a method for processing remote data of an intelligent wearable device, so as to solve the problems set forth in the above-mentioned background art.
In order to achieve the above purpose, the present application provides the following technical solutions:
a remote data processing method of intelligent wearable equipment, which comprises the following steps,
step S1, a mobile terminal and an intelligent watch are in communication connection through a Socket;
step S2, after the connection success is confirmed, the intelligent watch end evaluates the working state of the intelligent watch in real time, and marks positioning data which need to be fed back by the intelligent watch according to the working state of the intelligent watch;
step S3, after marking the positioning data, the intelligent watch end encapsulates the positioning data needing to be fed back to generate a data packet, and the data packet is transmitted to the mobile end in a wireless communication mode;
and S4, after the mobile terminal receives the data packet, the application program operated by the mobile terminal analyzes and identifies the data packet, when the identification result is risk-free data, the mobile terminal alarms according to a preset alarm strategy, and when the identification result is risk data, the alarm triggering condition is redefined.
In a preferred embodiment, in step S2, the specific process of determining the operating state of the smart watch is as follows:
acquiring equipment performance information and surrounding environment interference information of an internal electronic device, wherein the equipment performance information comprises a GPS receiver updated frequency deviation coefficient and an acceleration sensor static offset; the surrounding environment interference information comprises an electromagnetic interference abnormal coefficient;
updating a frequency deviation coefficient, a static offset of an acceleration sensor and an electromagnetic interference abnormal coefficient by a GPS receiver, and obtaining a state index of the intelligent watch through weighted summation calculation;
the state index of the intelligent watch is used for measuring the working state of the intelligent watch.
In a preferred embodiment, in step S2, the positioning data fed back by the smart watch is divided into risk-free data and risk data according to the working state of the smart watch;
if the state index of the intelligent watch is greater than or equal to the state index threshold of the intelligent watch, marking the positioning data fed back by the intelligent watch as risk data;
and if the state index of the intelligent watch is smaller than the state index threshold value of the intelligent watch, marking the feedback positioning data as risk-free data.
In a preferred embodiment, in step S4, when the identification result is risk data, redefining the alarm triggering condition is performed as follows:
caching the received positioning data, numbering the positioning data fed back intermittently to obtain a positioning data set;
acquiring interval time information and positioning data information of existing positioning data in a positioning data set;
the interval time information comprises an interval time discrete degree value, and the positioning data information comprises the shortest distance of the safety area;
and calculating the interval time discrete degree value and the shortest distance of the safety area through weighted summation to obtain an alarm triggering condition coefficient.
In a preferred embodiment, the alarm triggering condition coefficient is compared to an alarm triggering condition coefficient threshold;
if the alarm triggering condition coefficient is greater than or equal to the alarm triggering condition coefficient threshold value, generating an alarm signal;
if the alarm triggering condition coefficient is smaller than the alarm triggering condition coefficient threshold value, no alarm signal is generated.
In a preferred embodiment, the duration T of the state index of the smart watch being equal to or greater than the state index threshold of the smart watch is obtained, taken as an adjustment factor for the alarm triggering condition coefficient threshold, and adjusted.
The application has the technical effects and advantages that:
1. according to the application, the working state of the intelligent watch is evaluated by acquiring the equipment performance information of the internal electronic device and the surrounding environment interference information, the positioning data fed back by the intelligent watch in different working states are marked, the mobile terminal carries out different processing strategies according to the received positioning data, when the positioning data is risk-free, the mobile terminal is reduced to spend more resources to process the data, and if the positioning data is risk-free, the mobile terminal can be timely prompted, so that frequent alarm caused by data loss is avoided.
2. According to the application, the received positioning data are identified, when the identification result is risk-free data, the mobile terminal can alarm according to the preset alarm strategy, when the identification result is risk data, the preset alarm strategy is adjusted, the situation that the positioning data fed back by the intelligent watch are alarmed when the positioning data are intermittently lost is corrected each time, false alarm triggered under the condition that the data are intermittently lost is reduced as much as possible, the dissatisfaction of a user (parents) is reduced, and the trust and satisfaction degree of the user on the intelligent watch for children are improved.
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For the convenience of those skilled in the art, the present application will be further described with reference to the accompanying drawings;
FIG. 1 is a schematic diagram of the method of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Examples
Fig. 1 shows a remote data processing method of an intelligent wearable device, which comprises the following steps:
step S1, a mobile terminal and an intelligent watch are in communication connection through a Socket;
step S2, after the connection success is confirmed, the intelligent watch end evaluates the working state of the intelligent watch in real time, and marks positioning data which need to be fed back by the intelligent watch according to the working state of the intelligent watch;
step S3, after marking the positioning data, the intelligent watch end encapsulates the positioning data needing to be fed back to generate a data packet, and the data packet is transmitted to the mobile end in a wireless communication mode;
step S4, after the mobile terminal receives the data packet, the application program operated by the mobile terminal analyzes and identifies the data packet, when the identification result is risk-free data, the mobile terminal alarms according to a preset alarm strategy, and when the identification result is risk data, the alarm triggering condition is redefined;
global Positioning System (GPS) is a satellite positioning system that determines the precise geographic location of a device through a set of satellites and GPS receivers. Smart watches are often equipped with a GPS receiver that can receive signals from a GPS satellite system for determining the position of the watch. At the same time, a series of sensors, such as accelerometers, gyroscopes and magnetometers, are typically also deployed inside the smart watch to monitor the movement and orientation of the phone, thereby helping to determine position and improve the accuracy of the GPS data. The proper functioning of these electronics is critical to the position location function of the smart watch. If either one of them fails or is damaged, it may result in abnormal loss or inaccuracy of the positioning data.
Socket communication: socket is designed for client/server model, similar to dialing system, client is one end for making telephone call, and number dialed by client is formed from IP and correspondent port. The server end is equivalent to the end receiving the telephone call, and when the telephone call is identified to be the correct number of the client, the server end establishes connection with the client. In the application, the mobile terminal serves as a client terminal, and the intelligent watch terminal serves as a server terminal as one end for verification.
In step S1, the mobile terminal and the smart watch establish communication connection through Socket, and the specific steps are as follows:
socket establishes communication connection initiated by the mobile terminal, the mobile terminal establishes connection by designating IP and port number of the intelligent watch, and fills in ID of the intelligent watch;
the mobile terminal adds the ID to be transmitted with a corresponding operation number, calculates the length of the data packet, adds 6 as a check bit and transmits the check bit to the intelligent watch terminal;
the intelligent watch receives the connection request, detects the operation bit before the data and detects whether the length of the data is complete and meets the requirements;
if the requirements are met, the intelligent watch end sends a feedback signal to prompt that the mobile end is connected successfully;
in step S2, the working state of the smart watch is measured by a smart watch state index, which is determined by the device performance information of the internal electronic device and the surrounding environment interference information;
acquiring equipment performance information and surrounding environment interference information of an internal electronic device;
the device performance information comprises GPS receiver updated frequency deviation coefficient and acceleration sensor static offsetAn amount of; the surrounding environment interference information comprises an electromagnetic interference abnormal coefficient; the GPS receiver is respectively marked with the updated frequency deviation coefficient, the static offset of the acceleration sensor and the electromagnetic interference abnormal coefficient as；
The update frequency of a GPS receiver refers to the frequency at which position information is acquired, typically expressed in units of "hertz" (Hz). The update frequency determines the number of positioning data points acquired by the receiver per second, so it is critical to the positioning accuracy and real-time of the application, e.g. an update frequency of 1 hz means that the receiver acquires position information once per second.
The acquisition logic of the GPS receiver updated frequency deviation coefficient is as follows:
dividing the operation time length of the GPS receiver into a plurality of monitoring intervals, and calculating the interval updating frequency, wherein the expression is as follows:wherein->Representing interval update frequency, & lt & gt>Indicating the total number of acquired position information in the monitoring interval, < >>Representing the duration of the monitoring interval; obtaining a zone update frequency set by the calculation>Wherein i represents the order number of the monitoring interval, < + >>N is a positive integer.
Calculating an updated frequency deviation coefficient of the GPS receiver, wherein the updated frequency deviation coefficient is expressed as follows:wherein->Representing newly added interval update frequency acquired in real time, < >>Representing the existing interval update frequency set +.>The average value of the inter-zone update frequency is expressed as follows: />，/>Representing the existing interval update frequency set +.>The standard deviation of the update frequency of the middle interval is expressed as follows:>；
the larger the GPS receiver updating frequency deviation coefficient is, the larger the probability of abnormal fluctuation of the GPS receiver updating frequency is, the instability of the working state of the GPS receiver is reflected, and the abnormal loss or inaccuracy of positioning data received by a mobile terminal can be caused; on the contrary, the smaller the GPS receiver updating frequency deviation coefficient is, the smaller the probability of abnormal fluctuation of the GPS receiver updating frequency is, and the higher the stability of the working state of the GPS receiver is reflected.
The piezoelectric acceleration sensor is a detection device for converting mechanical quantity into electric quantity, and can be used for measuring vibration impact and linear acceleration. When the piezoelectric acceleration sensor moves along with an object to be measured on the object to be measured, the inertial mass block generates inertial force to act on the piezoelectric element under the action of acceleration, the piezoelectric element generates deformation proportional to the acting force, and charges proportional to the deformation of the piezoelectric element are generated due to the piezoelectric effect of the piezoelectric element;
the static offset of the acceleration sensor refers to zero drift of output when no acceleration is input, namely, the output voltage value under the condition of zero acceleration is supposed to be zero;
the calculation expression of the static offset of the acceleration sensor is as follows:wherein->For the output voltage value under zero acceleration condition, < >>Indicating a period of time without acceleration input.
The larger the static offset of the acceleration sensor is, the worse the working state of the acceleration sensor is, and the GPS position update can not be triggered more accurately by detecting the movement and vibration of the intelligent watch device, so that the acquired positioning data can be lost abnormally or inaccurate when the GPS receiver is in a poor state; otherwise, the smaller the static offset of the acceleration sensor is, the better the working state of the acceleration sensor is, and the position update of the GPS is triggered more favorably.
Electromagnetic interference refers to electromagnetic radiation from electronic devices or other wireless communication devices that not only interfere with the normal operation of the GPS receiver, but may also cause uninterrupted loss of the smart watch when feeding back positioning data; electromagnetic interference can cause the GPS signal to be partially or completely blocked, and electromagnetic interference can also cause multipath effects, i.e., the GPS signal reflects, refracts or scatters during propagation, resulting in the receiver receiving signals from multiple sources; this may lead to errors in the GPS receiver, resulting in inaccurate position; electromagnetic interference may cause GPS signal distortion including distortion, interference, or the introduction of noise. This can make it difficult for the GPS receiver to properly resolve the signal, resulting in inaccuracy in the positioning data.
The acquisition logic of the electromagnetic interference abnormal coefficient is as follows: setting a reference threshold QW of electromagnetic interference intensity, i.e. a maximum upper limit value of electromagnetic interference intensity, the threshold valueThe setting can be comprehensively set according to specifications of the intelligent watch and the geographical position of the intelligent watch by a person skilled in the art, and the detailed description is omitted herein; acquiring actually measured electromagnetic interference intensity QT and calculating electromagnetic interference intensity deviation coefficientAcquiring the time length QR and the number of times QE of occurrence of deviation when the deviation occurs, wherein the deviation refers to that the actually measured electromagnetic interference intensity exceeds a reference threshold value of the electromagnetic interference intensity, and the electromagnetic interference intensity can be measured by arranging an electromagnetic field sensor in the intelligent watch to detect the intensity of nearby wireless communication equipment, electronic equipment or an electromagnetic radiation source in real time; calculating electromagnetic interference anomaly coefficient->；
Comprehensively analyzing the current working state of the intelligent watch according to the updated frequency deviation coefficient of the GPS receiver, the static offset of the acceleration sensor and the electromagnetic interference abnormal coefficient, and marking the feedback data of the intelligent watch according to the analysis result so that the mobile terminal can make different processing strategies according to the feedback data marked differently;
the acquired GPS receiver update frequency deviation coefficient, acceleration sensor static offset and electromagnetic interference abnormal coefficient are processed in a dimensionless manner, after units are removed, a state evaluation model is built to generate a state index of the intelligent watch, and the state index is marked asThe model formula according to the method is as follows: />Wherein->Respectively updating preset proportional coefficients of a frequency deviation coefficient, an acceleration sensor static offset and an electromagnetic interference abnormal coefficient for the GPS receiver, < >>Are all greater than 0.
According to the model formula, the greater the GPS receiver updating frequency deviation coefficient, the greater the acceleration sensor static offset and the electromagnetic interference anomaly coefficient, the greater the state index of the intelligent watch, which indicates that the worse the working state of the intelligent watch is, the greater the probability of indirectly losing the positioning data fed back by the intelligent watch is; on the contrary, the smaller the GPS receiver updates the frequency deviation coefficient, the static offset of the acceleration sensor and the electromagnetic interference anomaly coefficient, the smaller the state index of the intelligent watch is, which indicates that the better the working state of the intelligent watch is, the positioning data fed back by the intelligent watch can be used for normal positioning tracking;
after comprehensively evaluating the working state of the intelligent watch, the quality and the continuity of the positioning data fed back by the intelligent watch are different due to different working states of the intelligent watch, the feedback positioning data are marked by setting corresponding thresholds, and the mobile terminal adopts different processing strategies according to the received different positioning data;
comparing the generated state index of the intelligent watch with a state index threshold value of the intelligent watch, and marking positioning data fed back by the intelligent watch according to a comparison result;
if the state index of the intelligent watch is greater than or equal to the state index threshold of the intelligent watch, marking the positioning data fed back by the intelligent watch as risk data, which indicates that the positioning data fed back by the intelligent watch in the current state may have indirection loss risk, and the mobile terminal needs to further process the received positioning data so as to avoid frequent alarm caused by the loss of the positioning data;
if the state index of the intelligent watch is smaller than the state index threshold of the intelligent watch, marking the feedback positioning data as risk-free data, which indicates that the mobile terminal can perform normal tracking operation according to the feedback positioning data without spending more resources to process the feedback positioning data;
according to the application, the working state of the intelligent watch is evaluated by acquiring the equipment performance information of the internal electronic device and the surrounding environment interference information, the positioning data fed back by the intelligent watch in different working states are marked, the mobile terminal carries out different processing strategies according to the received positioning data, when the positioning data is risk-free, the mobile terminal is reduced to spend more resources to process the data, and if the positioning data is risk-free, the mobile terminal can be timely prompted, so that frequent alarm caused by data loss is avoided.
In step S3, after the smart watch end marks the fed back positioning data, the smart watch end needs to package the positioning data to be fed back to generate a data packet, which specifically includes the following steps:
defining a message format: defining a message format to be used in the data packet, wherein the message format comprises a structure of a message header and a detailed body, the message header comprises metadata (operation number, data length, check bit, tag number), and the message body comprises actual data;
it should be noted that, the operation number is a value for identifying an operation or a request included in the data packet, typically an integer or enumeration, and corresponds to a series of possible operations, for example, operation number 1 may represent "request data", operation number 2 may represent "send notification", and so on.
The data length field indicates the byte length of the data portion, which is typically expressed in bytes and may be an integer value.
The check bits are used to detect whether the data packet has been tampered with or corrupted during transmission, typically by a fixed length value calculated by a check algorithm, such as a CRC (cyclic redundancy check).
The tag number is used to identify risk data and risk-free data in step S2, for example, a tag number of 1 indicates that the positioning data to be fed back by the smart watch is risk data, and a tag number of 0 indicates that the positioning data to be fed back by the smart watch is risk-free data;
and (3) packaging data packets: combining the message header and the message body together, and packaging the message header and the message body into a complete data packet, wherein the data packet is binary data;
after the data packet is packaged, the data packet is transmitted to the mobile terminal in a wireless communication mode;
it should be noted that the use of the wireless communication method may be determined according to practical situations, for example, bluetooth transmission, wi-Fi transmission, NFC transmission, etc., which are not described herein.
In step S4, after receiving the data packet, the mobile terminal analyzes the data packet by using an application program operated by the mobile terminal, identifies the tag number, and distributes different processing strategies according to the identification result;
if the identification result is risk-free data, the mobile terminal can alarm according to a preset alarm strategy;
in an alternative example, the preset alarm strategy is as follows:
safety area definition: a user (parent) defines a security area in an application program of the mobile terminal, such as a school, a family, etc.;
periodic location update: the intelligent watch periodically transmits the positioning data of the child to the mobile terminal application program, and simultaneously transmits other data such as step numbers, heart rate and the like;
judging an alarm strategy: the mobile terminal checks the positioning data of the children in real time and the positioning data do not need to be cached, if the positions of the children are in a set safety area, other data indicate that the health and safety conditions of the children are normal, and an alarm is not needed;
alarm triggering condition: an alarm is triggered if the child's location information leaves the secure area, for example, if the child's location is far from home or school.
If the identification result is risk data, uninterrupted loss of positioning data with risk may occur, and in the judgment of a preset alarm strategy, if the positioning data is lost in a judgment time node of the alarm, the system defines the positioning data as that children leave a safety area, so that the alarm is triggered, false alarm is caused, and the triggering of the alarm times is correspondingly increased along with the increase of the lost times;
therefore, if the identification result is risk data, the preset alarm strategy needs to be adjusted, and the specific steps are as follows: caching the received positioning data, numbering the positioning data fed back intermittently to obtain a positioning data setWhere j represents the order number of each intermittently received positioning data,m is a positive integer;
acquiring interval time information and positioning data information of existing positioning data in a positioning data set to judge whether the positioning data is required to be alarmed when the positioning data is lost in an alarm judging time node, so that frequent false alarms are avoided;
the interval time information comprises an interval time discrete degree value, and the positioning data information comprises the shortest distance of the safety area; respectively marking the interval time discrete degree value and the shortest distance of the safety area as；
The interval time is the interval time between every two pieces of intermittent positioning data, the interval time discrete degree value is used for measuring the change degree of the time interval between the existing positioning data in the whole positioning data set, the lower interval time discrete degree value possibly indicates that the time interval between the positioning data is relatively stable, the higher interval time discrete degree value possibly indicates that the time interval between the positioning data is changed more, and the higher interval time discrete degree value correspondingly improves the alarm probability of the application based on the consideration of the safety of children;
acquiring a duration of an interval between every two intermittent pieces of existing positioning data in a positioning data setThe interval duration average is calculated as follows: />Wherein k represents the sequence number of the interval duration between every two pieces of intermittent positioning data, +.>M is a positive integer; by means of the interval duration average>Calculating a time interval discrete degree value, wherein the expression is as follows: />；
The shortest distance of the safety area is used for judging the relative proximity degree of a determined positioning point (such as the current position of the child) and the safety area, if the current position of the child is longer from the boundary of the safety area, the probability that the child runs out of the safety area is lower, and the probability of alarming is correspondingly reduced;
the shortest distance of the safety area is obtained by the following steps:
a defined set of security area boundary points is obtained,wherein a represents the order number of each boundary point, +.>V is a positive integer, ">The coordinates of a boundary point are included;
acquiring the coordinates of the current position of the child from the m-th positioning data in the positioning data set, and calculating the distance from the current position of the child to the boundary point by using a Euclidean distance formula;
if the m-th positioning data is multiple in coordinates of the current position of the child, the coordinates of the last time node can be selected according to time sequence, and the coordinates of the current position of the child are selected as the coordinates of the current position of the child;
in an alternative example, the Euclidean distance formula is used to calculate the distance from the current location where the child is located to the boundary pointThe expression is as follows: />Wherein (x, y) represents the two-dimensional coordinates of the current position of the child, +.>Two-dimensional coordinates representing one boundary point in the set of boundary points;
calculating the distance from the current position of the child to the boundary point according to the boundary points in the boundary point set of the safety areaRecording the distance, and setting the distance as the shortest distance if the calculated distance of the latter pair is smaller than the recorded distance;
repeating the calculation steps until all boundary points in the boundary point set of the safety area are traversed, and taking the shortest distance finally recorded as the shortest distance of the safety area;
redefining an alarm triggering condition according to the interval time discrete degree value and the shortest distance of the safety area, judging whether the mobile terminal needs to alarm when the next positioning data is lost according to redefined alarm triggering condition standards, and reducing the alarm times when the positioning data is lost each time to the greatest extent, so as to avoid excessive false alarm;
it should be noted that, redefining the alarm triggering condition according to the interval time discrete degree value and the shortest distance of the safety area to obtain redefined alarm triggering condition standard, the redefined alarm triggering condition standard is determined by an alarm triggering condition coefficient CF, the smaller the alarm triggering condition coefficient is, the lower the probability of triggering an alarm is, the number of alarms when the positioning data of each time is lost is reduced to the greatest extent, excessive false alarm is avoided, the alarm triggering condition coefficient is constrained by the interval time discrete degree value and the shortest distance of the safety area together, the constraint rule can be represented by the following formula, for example,wherein->Respectively the interval time discrete degree value and the shortest safety areaThe specific value of the weight factor of the distance can be set according to the actual situation;
the application compares the alarm triggering condition coefficient with the threshold value of the alarm triggering condition coefficient to judge whether the mobile terminal needs to alarm when the next positioning data is lost;
it should be noted that, the determination of the alarm triggering condition coefficient threshold is obtained by actually obtaining a plurality of groups of interval time discrete degree values and the shortest distance of the safety area and simulating the shortest distance through a corresponding software algorithm, and is not described herein again;
if the alarm triggering condition coefficient is greater than or equal to the alarm triggering condition coefficient threshold value, generating an alarm signal, and alarming at a proper time point under the condition that the positioning data fed back by the intelligent watch are intermittently lost based on the consideration of the safety of the child, so that the fault tolerance of the alarm is improved;
if the alarm triggering condition coefficient is smaller than the alarm triggering condition coefficient threshold, no alarm signal is generated, the alarm condition is corrected under the condition that the positioning data fed back by the intelligent watch are intermittently lost every time, excessive false alarm is avoided as much as possible, the dissatisfaction of users (parents) is reduced, and the trust and satisfaction degree of the users to the intelligent watch for children are improved.
If the state index of the intelligent watch is larger than or equal to the state index threshold value of the intelligent watch, the working state of the intelligent watch is unstable, and in order to improve the alarm accuracy and reduce the possibility of false alarm, the application dynamically adjusts the coefficient threshold value of the alarm triggering condition according to the duration;
the method comprises the steps of obtaining duration time T that the state index of the intelligent watch is larger than or equal to the state index threshold of the intelligent watch, taking the duration time T as an adjusting factor of the alarm triggering condition coefficient threshold, and adjusting the alarm triggering condition coefficient threshold according to the following example formula, wherein the expression is as follows: new alarm trigger condition coefficient threshold = initial alarm trigger condition coefficient thresholdWherein->Is an adjusting parameter used for controlling the descending speed of the alarm triggering condition coefficient threshold value and can be set according to actual requirements;
according to the application, the received positioning data are identified, when the identification result is risk-free data, the mobile terminal can alarm according to the preset alarm strategy, when the identification result is risk data, the preset alarm strategy is adjusted, the situation that the positioning data fed back by the intelligent watch are alarmed when the positioning data are intermittently lost is corrected each time, false alarm triggered under the condition that the data are intermittently lost is reduced as much as possible, the dissatisfaction of a user (parents) is reduced, and the trust and satisfaction degree of the user on the intelligent watch for children are improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation.
It should be understood that, in various embodiments of the present application, the sequence numbers of the foregoing processes do not mean the order of execution, and the order of execution of the processes should be determined by the functions and internal logic thereof, and should not constitute any limitation on the implementation process of the embodiments of the present application.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (6)
1. A remote data processing method of intelligent wearable equipment is characterized by comprising the following steps of: comprises the following steps of the method,
step S1, a mobile terminal and an intelligent watch are in communication connection through a Socket;
step S2, after the connection success is confirmed, the intelligent watch end evaluates the working state of the intelligent watch in real time, and marks positioning data which need to be fed back by the intelligent watch according to the working state of the intelligent watch;
step S3, after marking the positioning data, the intelligent watch end encapsulates the positioning data needing to be fed back to generate a data packet, and the data packet is transmitted to the mobile end in a wireless communication mode;
and S4, after the mobile terminal receives the data packet, the application program operated by the mobile terminal analyzes and identifies the data packet, when the identification result is risk-free data, the mobile terminal alarms according to a preset alarm strategy, and when the identification result is risk data, the alarm triggering condition is redefined.
2. The intelligent wearable device remote data processing method according to claim 1, wherein: in step S2, the specific process of determining the working state of the smart watch is as follows:
acquiring equipment performance information and surrounding environment interference information of an internal electronic device, wherein the equipment performance information comprises a GPS receiver updated frequency deviation coefficient and an acceleration sensor static offset; the surrounding environment interference information comprises an electromagnetic interference abnormal coefficient;
updating a frequency deviation coefficient, a static offset of an acceleration sensor and an electromagnetic interference abnormal coefficient by a GPS receiver, and obtaining a state index of the intelligent watch through weighted summation calculation;
the state index of the intelligent watch is used for measuring the working state of the intelligent watch.
3. The intelligent wearable device remote data processing method according to claim 2, wherein: in step S2, dividing the positioning data fed back by the smart watch into risk-free data and risk data according to the working state of the smart watch;
if the state index of the intelligent watch is greater than or equal to the state index threshold of the intelligent watch, marking the positioning data fed back by the intelligent watch as risk data;
and if the state index of the intelligent watch is smaller than the state index threshold value of the intelligent watch, marking the feedback positioning data as risk-free data.
4. The intelligent wearable device remote data processing method according to claim 1, wherein: in step S4, when the identification result is risk data, redefining an alarm triggering condition, and the specific process is as follows:
caching the received positioning data, numbering the positioning data fed back intermittently to obtain a positioning data set;
acquiring interval time information and positioning data information of existing positioning data in a positioning data set;
the interval time information comprises an interval time discrete degree value, and the positioning data information comprises the shortest distance of the safety area;
and calculating the interval time discrete degree value and the shortest distance of the safety area through weighted summation to obtain an alarm triggering condition coefficient.
5. The intelligent wearable device remote data processing method according to claim 4, wherein: comparing the alarm triggering condition coefficient with an alarm triggering condition coefficient threshold;
if the alarm triggering condition coefficient is greater than or equal to the alarm triggering condition coefficient threshold value, generating an alarm signal;
if the alarm triggering condition coefficient is smaller than the alarm triggering condition coefficient threshold value, no alarm signal is generated.
6. A method for processing remote data of an intelligent wearable device according to claim 3, wherein: and acquiring the duration time T of the state index of the intelligent watch which is larger than or equal to the state index threshold of the intelligent watch, taking the duration time T as an adjusting factor of the alarm triggering condition coefficient threshold, and adjusting the alarm triggering condition coefficient threshold.
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