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CN-122024402-A - Parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon

CN122024402ACN 122024402 ACN122024402 ACN 122024402ACN-122024402-A

Abstract

The invention relates to the technical field of remote operation, in particular to a parent-child safety monitoring method based on artificial intelligent emotion synchronization and positioning daemon, which comprises the following steps of collecting bracelet positioning, heart rate and acceleration, performing time alignment integration, generating a child real-time state record, acquiring risks and forming a continuous emotion state according to a positioning mapping geofence, identifying emotion consistent sections and positioning residence by combining tracks, calculating duration differences, determining concerned sections according to thresholds, and writing start-stop information according to time axes to form daemon records.

Inventors

  • Jia Bendong

Assignees

  • 北京地球上的星科技有限公司

Dates

Publication Date
20260512
Application Date
20260210

Claims (10)

  1. 1. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon is characterized by comprising the following steps of: S1, acquiring positioning coordinates, heart rate monitoring and acceleration change information output by a safety monitoring bracelet of a child wearing end, synchronously aligning based on a uniform time mark, integrating heart rate change state and motion state at the same time node, and generating a real-time state combination record of the child; S2, mapping the corresponding positions to the geofence partitions and acquiring risk level identifiers according to the positioning coordinate information in the child real-time state combination record to form a child emotion state continuous record; S3, acquiring the continuous records of the child emotion states, acquiring continuous positioning track records within the same time range, identifying continuous time sections with consistent emotion states, judging whether positioning residence sections are formed in the sections, and establishing emotion and activity consistency section records; S4, calculating the difference value between the emotion duration and the positioning residence duration based on the emotion and activity consistency section record, judging the section according to a preset consistency threshold value, and generating a parent-child daemon concerned section identifier; S5, calling the parent-child conservation concerned section identification, marking the section of the conservation record unit time axis according to the corresponding time section, and writing the start and stop time and the identification of the concerned section in time sequence to form the conservation concerned section record.
  2. 2. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 1 is characterized in that the child real-time state combination record comprises a time node index, a heart rate change label and an exercise activity label, the child emotion state continuous record comprises an emotion level sequence, a risk level identification sequence and a time continuous index, the emotion and activity consistency section record comprises an emotion consistency section start and stop, an activity consistency section start and stop and a section alignment index, the parent-child daemon attention section identification comprises a consistency judgment result, a threshold judgment category and an attention priority label, and the parent-child daemon attention section record comprises a time axis section label, an attention section start and stop time and an identification writing sequence.
  3. 3. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 1, wherein the specific steps of S1 are as follows: s101, acquiring positioning coordinate information, heart rate monitoring information and acceleration change information output by a safety monitoring bracelet at a child wearing end, sequentially arranging the positioning coordinate, heart rate value and acceleration value according to time marks corresponding to the information, and binding the positioning coordinate, heart rate value and acceleration value at the same time mark to generate a multi-source time sequence monitoring data set; s102, based on the multi-source time sequence monitoring data set, comparing the heart rate values at adjacent time points, judging the heart rate change direction, judging the physical activity state according to the acceleration change information, and merging and recording the heart rate change direction and the activity state under the same time mark to obtain a physiological and activity state mark sequence; And S103, calling positioning coordinate information under the corresponding time mark according to the physiological and active state mark sequence, performing time consistency check on the positioning coordinate and the physiological state mark and the active state mark, and sequentially integrating the positioning coordinate and the physiological state mark and the active state mark to generate a real-time state combination record of the child.
  4. 4. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 3, wherein the specific steps of S2 are as follows: S201, calling positioning coordinate information under a corresponding time mark according to the child real-time state combination record, and performing position matching judgment on the positioning coordinate and geofence partition data to generate a position risk area identification sequence; S202, calling a heart rate change state and a motion activity state under the same time mark based on the position risk area identification sequence, and judging a state association result according to the area identification for a time node to obtain an emotion judgment state sequence; and S203, continuously judging the states of the time nodes according to the emotion judging state sequence, and integrating and recording the continuous states according to the time sequence to generate a continuous record of the emotion states of the children.
  5. 5. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 4, wherein the specific steps of S3 are as follows: S301, acquiring the child emotion state continuous records, synchronously acquiring child continuous positioning track records in the same time range, sequentially arranging the two types of records according to time marks, judging whether the emotion state records are consistent with adjacent time nodes, and generating an emotion continuous time section sequence; S302, calling continuous positioning track records of children in a corresponding time range based on the emotion continuous time section sequence, comparing distances of adjacent positioning coordinates in the time section, and judging whether a positioning residence section is formed or not according to a residence distance threshold value to obtain a positioning residence time section sequence; S303, judging whether the time ranges of the two types of sections are aligned according to the positioning residence time section sequence, and correspondingly integrating the sections with the coincident time ranges to generate an emotion and activity consistency section record.
  6. 6. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 5, wherein the specific steps of S4 are as follows: S401, based on the emotion and activity consistency section record, acquiring the emotion duration time and positioning residence duration time corresponding to the section, carrying out pairing arrangement according to the section time sequence, calculating the difference value of the two types of duration time in the same section, and generating a section time difference value sequence; s402, reading the corresponding difference results of the sections one by one according to the section time difference sequence, comparing the difference with a consistency judgment threshold value, judging whether the sections meet consistency conditions, and obtaining a section consistency judgment sequence; S403, based on the section consistency judging sequence, screening section identifiers of which the consistency judging does not meet the threshold value requirement, and carrying out summarization recording according to the section time sequence to generate parent-child conservation concerned section identifiers.
  7. 7. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 6, wherein the specific steps of S5 are as follows: s501, calling the parent-child daemon concerned section identification, obtaining the start-stop time information corresponding to the concerned section, arranging the start-stop time of the sections according to the time mark sequence, respectively recording the start time and the end time of the sections, associating the section numbers, and generating a daemon concerned time section sequence; s502, calling the existing time axis information in the daemon recording unit based on the daemon attention time section sequence, judging the corresponding position of the time section in the time axis, and executing section marking operation on the time axis to obtain a time axis section marking sequence; And S503, reading the start and stop time and the section number corresponding to the section according to the time axis section marking sequence, continuously arranging and integrating according to the time sequence, writing the section marking information into a daemon recording unit, and generating parent-child daemon concerned section records.
  8. 8. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 1, wherein the child wearing end is a non-screen or low-power wearable terminal which is arranged on a child to wear, and is used for continuously acquiring positioning data, physiological data and motion data of the child, and performing basic feature extraction and emotion state judgment on the end side; The positioning coordinate information refers to data which is output by the child wearing end safety monitoring bracelet and used for representing the space position of the child; the heart rate monitoring information refers to information which is output by a child wearing end safety monitoring bracelet and is used for reflecting the heart rate change condition of the child; the acceleration change information refers to information which is output by a child wearing end safety monitoring bracelet and is used for reflecting the movement change state of the child; the unified time mark is a time mark for synchronously arranging positioning coordinate information, heart rate monitoring information and acceleration change information; The heart rate change state refers to a heart rate state marking result obtained under the same time node based on heart rate monitoring information; the motion activity state is a motion state marking result obtained under the same time node based on the acceleration change information; The real-time state combination record of the children is a record generated by integrating marks of heart rate change states and exercise activity states at the same time node.
  9. 9. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 1, wherein the geofence partition data is data for performing partition mapping on a position corresponding to positioning coordinate information; the risk level identification refers to identification information which is acquired according to geofence partition data and used for representing the position risk degree; The emotion level judgment refers to level judgment operation performed on the state of the time node by combining the risk level identification, the heart rate change state and the exercise activity state; the continuous record of the emotion states of the children is formed by organizing emotion level judgment results in time sequence; the continuous positioning track records of the children are the positioning track records of the children, which are acquired in the same time range; the continuous time section refers to a continuous time range in which the identified emotion states are consistent; The positioning residence section refers to a positioning residence time period formed by judging in the corresponding time section; The emotion and activity consistency section record refers to a record established after time alignment of a continuous time section and a positioning residence section.
  10. 10. The parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon according to claim 1, wherein the emotion duration refers to a time length of emotion state retention in a continuous time section; the positioning residence duration refers to the length of time that the position within the positioning residence section is maintained; the consistency judgment threshold value is a threshold value condition for completing consistency judgment of the section; The parent-child conservation concerned section identification refers to a section identification generated after marking a section needing important attention; The daemon recording unit is used for storing and maintaining a time axis; The time axis refers to a time sequence structure for section marking; The daemon attention labeling sequence is a sequence formed by writing the start and stop time of an attention section and corresponding identifiers in time sequence; the parent-child conservation attention section record refers to attention section record results formed in a time-series manner.

Description

Parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon Technical Field The invention relates to the technical field of remote operation, in particular to a parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon. Background The technical field of remote operation refers to the field of a method for carrying out state acquisition, transmission, analysis and intervention control on a distributed object based on an information communication technology, wherein the core matters comprise terminal side data acquisition remote side state identification and cross-terminal interaction control, positioning physiological and behavior information acquired by a wearable or portable terminal is usually sent to a monitoring end through network communication, state judgment and operation instruction generation are completed on the monitoring end, so that remote nursing and operation management on the monitored object are realized, wherein the traditional parent-child safety monitoring refers to a mode of acquiring positioning information heart rate data and action characteristics by means of a wearable terminal worn by a child and carrying out state judgment by the monitoring end according to a preset threshold rule, the specific technical matters are safety state perception and remote guarding of the child in daily activities and high risk scenes, the traditional scheme generally completes monitoring by positioning out-of-limit judgment heart rate overrun judgment and alarm logic based on abnormality or not, and uses vibration frequency or vibration duration as a main information transmission means on the non-screen or low-power consumption terminal, and the method is used for prompting state change to the child or the monitoring process of the whole safety monitoring in a remote operation parent-child. The existing parent-child safety monitoring generally takes single thresholds such as positioning out-of-range, heart rate out-of-limit and the like as judgment basis, state judgment is highly dependent on instantaneous data, comprehensive consideration on time continuity and multi-state association is lacked, in actual operation, short-time severe motion or environmental change of children is easy to trigger frequent alarms, information redundancy of a monitoring end is caused, alarm reliability is weakened, positioning data is mostly based on whether the data enter or leave a safety area or not as a core, behavior risks implied by long-time stay in the same area are ignored, part of abnormal activities are difficult to pay attention to in time, meanwhile, heart rate and action information are mostly used as independent judgment conditions, joint analysis logic is not formed, the association value between physiological change and behavior change is not effectively utilized, monitoring records are mostly stored in an event triggering mode, structural arrangement on continuous time periods is lacked, follow-up retrospective analysis can only rely on scattered alarm records, the actual activity process is difficult to restore, problems such as monitoring fatigue, misjudgment frequently occurs, key risks are covered up in complex environments and the like easily occur under long-term use scenes, and the actual effect of parent-child safety monitoring in daily environments is influenced. Disclosure of Invention In order to solve the technical problems in the prior art, the embodiment of the invention provides a parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon, which comprises the following steps: In order to achieve the purpose, the invention adopts the following technical scheme that the parent-child safety monitoring method based on artificial intelligence emotion synchronization and positioning daemon comprises the following steps: S1, acquiring positioning coordinates, heart rate monitoring and acceleration change information output by a safety monitoring bracelet of a child wearing end, synchronously aligning based on a uniform time mark, integrating heart rate change state and motion state at the same time node, and generating a real-time state combination record of the child; S2, mapping the corresponding positions to the geofence partitions and acquiring risk level identifiers according to the positioning coordinate information in the child real-time state combination record to form a child emotion state continuous record; S3, acquiring the continuous records of the child emotion states, acquiring continuous positioning track records within the same time range, identifying continuous time sections with consistent emotion states, judging whether positioning residence sections are formed in the sections, and establishing emotion and activity consistency section records; S4, calculating the difference value between the emotion dura