CN113674127B - Emergent mobile monitoring command platform based on thing networking - Google Patents
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Abstract
The invention discloses an emergency mobile monitoring command platform based on the Internet of things, which relates to the technical field of emergency mobile monitoring command and solves the technical problem that in the prior art, the accuracy of monitoring is reduced because a monitoring area cannot be divided into areas, the areas are monitored through an area monitoring unit, the boundary of the monitoring area is set, the areas in the boundary of the monitoring area are marked as monitoring areas, then the monitoring area is divided into a plurality of subareas, the data information of each subarea is obtained, the data information corresponds to the subareas one by one, a monitoring time threshold is set, the data information monitoring coefficient Xi in the subareas is obtained through a formula, and the data information monitoring coefficient Xi in the subareas is compared with the monitoring coefficient threshold; the monitoring area is limited, and is divided into areas, so that the monitoring accuracy and the monitoring working efficiency are improved, and the monitoring error rate is reduced.
Description
Technical Field
The invention relates to the technical field of emergency mobile monitoring and commanding, in particular to an emergency mobile monitoring and commanding platform based on the Internet of things.
Background
Viruses are a class of parasites that are smaller, cell-free structures than bacteria, and which are found in living cells containing only one nucleic acid. As there is no intact cellular structure, it is clearly different from other organisms. The virus has the specificity and the parasitism, and in the public place, the pedestrian is too dense, the air flow speed is low, the virus infection is often caused, and great inconvenience is brought to the healthy trip of people, so that the public place needs to be monitored in an emergency.
However, in the prior art, the monitoring area cannot be divided into areas, so that the accuracy of monitoring is reduced, and the monitoring cost is increased.
Disclosure of Invention
The invention aims to provide an emergency mobile monitoring command platform based on the Internet of things, which is characterized in that an area is monitored through an area monitoring unit, a monitoring area boundary is set, the area in the monitoring area boundary is marked as a monitoring area, then the monitoring area is divided into a plurality of subareas, the data information of each subarea is obtained, the data information of the subareas is analyzed, the data information corresponds to the subareas one by one, a monitoring time threshold is set, the monitoring time threshold is divided into time periods with one hour as a unit interval time, the maximum pedestrian flow quantity, average walking speed and total number of pedestrians in the monitoring time threshold are obtained, the data information monitoring coefficient Xi in the subarea is obtained through a formula, and the data information monitoring coefficient Xi in the subarea is compared with the monitoring coefficient threshold; the monitoring area is limited, and is divided, so that the monitoring accuracy and the monitoring working efficiency are improved, and the monitoring error rate is reduced;
the aim of the invention can be achieved by the following technical scheme:
an emergency mobile monitoring command platform based on the Internet of things comprises an equipment monitoring unit, an area monitoring unit, an emergency analysis unit, a monitoring command platform, a registration login unit and a database;
the area monitoring unit is used for monitoring the area, and the specific monitoring process is as follows:
step S1: setting a monitoring area boundary, marking an area in the monitoring area boundary as a monitoring area, dividing the monitoring area into a plurality of sub-areas, marking the sub-areas as i, i=1, 2, … …, n, n being a positive integer;
step S2: acquiring data information of each sub-region, analyzing the data information of the sub-region, wherein the data information corresponds to the sub-region one by one, then setting a monitoring time threshold, dividing the monitoring time threshold into time periods with one hour as a unit interval time, and marking the divided time periods as o, o=1, 2, … … and 24; the data information of the subareas comprises people flow data, pace data and density data, wherein the people flow data is the maximum pedestrian flow quantity of the subareas in the monitoring time threshold, the pace data is the average walking speed of pedestrians in the monitoring time threshold of the subareas, and the density data is the total number of pedestrians in the monitoring time threshold of the subareas;
step S3: obtaining the maximum pedestrian flow number, the average walking speed and the total number of pedestrians staying in the sub-area within the monitoring time threshold, and marking the maximum pedestrian flow number, the average walking speed and the total number of pedestrians staying in the sub-area within the monitoring time threshold as LDi, SDi and RSi respectively;
step S4: by the formula xi=β (ldixa1+sdi×a2+rsi×a3) 2 Obtaining a data information monitoring coefficient Xi in the subarea, wherein a1, a2 and a3 are proportionality coefficients, a1 is more than a2 and more than a3 is more than 0, beta is an error correction factor, and the value is 2.365;
step S5: comparing the data information monitoring coefficient Xi in the subarea with a monitoring coefficient threshold value:
if the data information monitoring coefficient Xi in the subarea is more than or equal to the monitoring coefficient threshold value, judging that the subarea is abnormal in monitoring, marking the subarea as an abnormal subarea, marking a time period corresponding to the subarea as an abnormal time period, and then sending the abnormal subarea and the corresponding abnormal time period to a monitoring command platform;
if the data information monitoring coefficient Xi in the subarea is smaller than the monitoring coefficient threshold value, judging that the subarea is monitored normally, marking the subarea as a normal subarea, marking the time period corresponding to the subarea as a normal time period, and then sending the normal subarea and the corresponding normal time period to a monitoring command platform.
Further, after the monitoring command platform receives the abnormal subarea and the abnormal time period, generating a device monitoring signal and sending the device monitoring signal to the device monitoring unit, and after the device monitoring unit receives the device monitoring signal, monitoring the area device in the corresponding abnormal subarea, wherein the area device comprises a camera and an indicator lamp, the abnormal subarea is marked as p, p=1, 2, … …, y and y are positive integers, and the specific area device monitoring process is as follows:
step SS1: acquiring the monitoring frequency of the cameras in the abnormal subarea, and marking the monitoring frequency of the cameras in the abnormal subarea as PLp;
step SS2: acquiring the power of the indicator lamp in the abnormal subarea and the use times of the indicator lamp, and marking the power of the indicator lamp in the abnormal subarea and the use times of the indicator lamp as GLp and CSp respectively;
step SS3: by the formula
Acquiring a device monitoring coefficient SBp in an abnormal subarea, wherein v1, v2 and v3 are proportionality coefficients, v1 is more than v2 is more than v3 is more than 0, and e is a natural constant;
step SS4: comparing the device monitoring coefficient SBp within the abnormal sub-area with a device monitoring coefficient threshold:
if the equipment monitoring coefficient SBp in the abnormal subarea is more than or equal to the equipment monitoring coefficient threshold value, judging that the area equipment corresponding to the abnormal subarea is abnormal in use, generating an equipment maintenance signal and sending the equipment maintenance signal to a mobile phone terminal of a monitoring person;
if the equipment monitoring coefficient SBp in the abnormal subarea is smaller than the equipment monitoring coefficient threshold value, judging that the area equipment corresponding to the abnormal subarea is normal in use, generating an equipment normal signal and sending the equipment normal signal to the monitoring command platform.
Further, after receiving the equipment normal signal, the monitoring command platform generates an emergency analysis signal and sends the emergency analysis signal to the emergency analysis unit, and the emergency analysis unit receives the emergency analysis signal to perform early warning analysis on the abnormal subareas, wherein the specific early warning analysis process is as follows:
step T1: acquiring the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea, and marking the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea as WDSp, KLDp and YSSp respectively;
step T2: by the formula
Acquiring an early warning analysis coefficient FXp of the abnormal subarea, wherein s1, s2 and s3 are proportionality coefficients, s1 is more than s2 is more than s3 is more than 0, alpha is an error correction factor, and the value is 1.562; />
Step T3: comparing the early warning analysis coefficient FXp of the abnormal subarea with an early warning analysis coefficient threshold value:
if the early warning analysis coefficient FXp of the abnormal subarea is more than or equal to the early warning analysis coefficient threshold value, judging that the corresponding abnormal subarea has risks, generating an emergency adjustment signal and sending the emergency adjustment signal and the corresponding abnormal subarea to the monitoring command platform;
if the early warning analysis coefficient FXp of the abnormal subarea is smaller than the early warning analysis coefficient threshold value, judging that the corresponding abnormal subarea does not have risks, generating a risk-free signal and transmitting the risk-free signal and the corresponding abnormal subarea to a mobile phone terminal of a manager;
step T4: after receiving the emergency adjustment signals and the corresponding abnormal subareas, the monitoring command platform performs pedestrian evacuation on the abnormal subareas, divides the abnormal subareas into four evacuation lines according to the azimuth, reasonably matches the evacuation lines with pedestrians in the abnormal subareas, namely, the evacuation line with the shortest pedestrian matching stroke in the abnormal subareas, stops matching the corresponding evacuation lines with pedestrians if the number of pedestrians in the four evacuation lines exceeds a threshold value of the number of pedestrians, marks the evacuation line with the nearest peripheral distance of the corresponding evacuation line as a substitute evacuation line, and matches the substitute evacuation line with the pedestrians.
Furthermore, the registration login unit is used for submitting manager information and monitor information to register through the mobile phone terminal, and storing the successfully registered manager information and monitor information in data, wherein the manager information comprises the name, age, time of entering and mobile phone number of the real name authentication of the manager, and the monitor information comprises the name, age, time of entering and mobile phone number of the real name authentication of the monitor.
Compared with the prior art, the invention has the beneficial effects that:
1. according to the method, an area is monitored through an area monitoring unit, a monitoring area boundary is set, the area in the monitoring area boundary is marked as a monitoring area, then the monitoring area is divided into a plurality of subareas, data information of each subarea is obtained, the data information of the subareas is analyzed, the data information corresponds to the subareas one by one, a monitoring time threshold is set, the monitoring time threshold is divided into time periods with one hour as a unit interval time, the maximum pedestrian flow quantity, average walking speed and total number of pedestrians staying in the monitoring time threshold of the subarea are obtained, a data information monitoring coefficient Xi in the subarea is obtained through a formula, and the data information monitoring coefficient Xi in the subarea is compared with the monitoring coefficient threshold; the monitoring area is limited, and is divided, so that the monitoring accuracy and the monitoring working efficiency are improved, and the monitoring error rate is reduced;
2. in the invention, the emergency analysis unit receives the emergency analysis signal to perform early warning analysis on the abnormal subarea, the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea are obtained, the early warning analysis coefficient FXp of the abnormal subarea is obtained through a formula, and the early warning analysis coefficient FXp of the abnormal subarea is compared with the early warning analysis coefficient threshold value: after receiving the emergency adjustment signals and the corresponding abnormal subareas, the monitoring command platform performs pedestrian evacuation on the abnormal subareas, divides the abnormal subareas into four evacuation lines according to the azimuth, reasonably matches the evacuation lines with pedestrians in the abnormal subareas, namely, the evacuation line with the shortest pedestrian matching stroke in the abnormal subareas, stops matching the corresponding evacuation lines with pedestrians if the number of pedestrians in the four evacuation lines exceeds a threshold value of the number of pedestrians, marks the evacuation line with the nearest peripheral distance of the corresponding evacuation line as a substitute evacuation line, and matches the substitute evacuation line with the pedestrians; emergency monitoring is carried out on the abnormal region with risk, pedestrians in the corresponding region are evacuated, the safety problem of the pedestrians is reduced, the speed of mutual infection of the pedestrians is reduced, and the working efficiency of the emergency monitoring of the region is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a functional block diagram of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the emergency mobile monitoring command platform based on the internet of things comprises a device monitoring unit, an area monitoring unit, an emergency analysis unit, a monitoring command platform, a registration login unit and a database;
the registration login unit is used for submitting manager information and monitor information to register through the mobile phone terminal, and storing the successfully registered manager information and monitor information in data, wherein the manager information comprises the name, age, job time of the manager and the mobile phone number of the real name authentication of the person, and the monitor information comprises the name, age, job time of the monitor and the mobile phone number of the real name authentication of the person;
the area monitoring unit is used for monitoring the area, and the specific monitoring process is as follows:
step S1: setting a monitoring area boundary, marking an area in the monitoring area boundary as a monitoring area, dividing the monitoring area into a plurality of sub-areas, marking the sub-areas as i, i=1, 2, … …, n, n being a positive integer;
step S2: acquiring data information of each sub-region, analyzing the data information of the sub-region, wherein the data information corresponds to the sub-region one by one, then setting a monitoring time threshold, dividing the monitoring time threshold into time periods with one hour as a unit interval time, and marking the divided time periods as o, o=1, 2, … … and 24; the data information of the subareas comprises people flow data, pace data and density data, wherein the people flow data is the maximum pedestrian flow quantity of the subareas in the monitoring time threshold, the pace data is the average walking speed of pedestrians in the monitoring time threshold of the subareas, and the density data is the total number of pedestrians in the monitoring time threshold of the subareas;
step S3: obtaining the maximum pedestrian flow number, the average walking speed and the total number of pedestrians staying in the sub-area within the monitoring time threshold, and marking the maximum pedestrian flow number, the average walking speed and the total number of pedestrians staying in the sub-area within the monitoring time threshold as LDi, SDi and RSi respectively;
step S4: by the formula xi=β (ldixa1+sdi×a2+rsi×a3) 2 Obtaining a data information monitoring coefficient Xi in the subarea, wherein a1, a2 and a3 are proportionality coefficients, a1 is more than a2 and more than a3 is more than 0, beta is an error correction factor, and the value is 2.365;
step S5: comparing the data information monitoring coefficient Xi in the subarea with a monitoring coefficient threshold value:
if the data information monitoring coefficient Xi in the subarea is more than or equal to the monitoring coefficient threshold value, judging that the subarea is abnormal in monitoring, marking the subarea as an abnormal subarea, marking a time period corresponding to the subarea as an abnormal time period, and then sending the abnormal subarea and the corresponding abnormal time period to a monitoring command platform;
if the data information monitoring coefficient Xi in the subarea is smaller than the monitoring coefficient threshold value, judging that the subarea is monitored normally, marking the subarea as a normal subarea, marking the time period corresponding to the subarea as a normal time period, and then sending the normal subarea and the corresponding normal time period to a monitoring command platform;
after the monitoring command platform receives the abnormal subarea and the abnormal time period, generating a device monitoring signal and sending the device monitoring signal to a device monitoring unit, wherein the device monitoring unit monitors area devices in the corresponding abnormal subarea after receiving the device monitoring signal, the area devices comprise cameras and indicator lamps, the abnormal subarea is marked as p, p=1, 2, … …, y and y are positive integers, and the specific area device monitoring process is as follows:
step SS1: acquiring the monitoring frequency of the cameras in the abnormal subarea, and marking the monitoring frequency of the cameras in the abnormal subarea as PLp;
step SS2: acquiring the power of the indicator lamp in the abnormal subarea and the use times of the indicator lamp, and marking the power of the indicator lamp in the abnormal subarea and the use times of the indicator lamp as GLp and CSp respectively;
step SS3: by the formula
Acquiring a device monitoring coefficient SBp in an abnormal subarea, wherein v1, v2 and v3 are proportionality coefficients, v1 is more than v2 is more than v3 is more than 0, and e is a natural constant;
step SS4: comparing the device monitoring coefficient SBp within the abnormal sub-area with a device monitoring coefficient threshold:
if the equipment monitoring coefficient SBp in the abnormal subarea is more than or equal to the equipment monitoring coefficient threshold value, judging that the area equipment corresponding to the abnormal subarea is abnormal in use, generating an equipment maintenance signal and sending the equipment maintenance signal to a mobile phone terminal of a monitoring person;
if the equipment monitoring coefficient SBp in the abnormal subarea is smaller than the equipment monitoring coefficient threshold value, judging that the area equipment corresponding to the abnormal subarea is normal in use, generating an equipment normal signal and sending the equipment normal signal to a monitoring command platform;
after receiving the equipment normal signal, the monitoring command platform generates an emergency analysis signal and sends the emergency analysis signal to the emergency analysis unit, and the emergency analysis unit receives the emergency analysis signal to perform early warning analysis on the abnormal subareas, wherein the specific early warning analysis process is as follows:
step T1: acquiring the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea, and marking the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea as WDSp, KLDp and YSSp respectively;
step T2: by the formula
Acquiring an early warning analysis coefficient FXp of the abnormal subarea, wherein s1, s2 and s3 are proportionality coefficients, s1 is more than s2 is more than s3 is more than 0, alpha is an error correction factor, and the value is 1.562;
step T3: comparing the early warning analysis coefficient FXp of the abnormal subarea with an early warning analysis coefficient threshold value:
if the early warning analysis coefficient FXp of the abnormal subarea is more than or equal to the early warning analysis coefficient threshold value, judging that the corresponding abnormal subarea has risks, generating an emergency adjustment signal and sending the emergency adjustment signal and the corresponding abnormal subarea to the monitoring command platform;
if the early warning analysis coefficient FXp of the abnormal subarea is smaller than the early warning analysis coefficient threshold value, judging that the corresponding abnormal subarea does not have risks, generating a risk-free signal and transmitting the risk-free signal and the corresponding abnormal subarea to a mobile phone terminal of a manager;
step T4: after receiving the emergency adjustment signals and the corresponding abnormal subareas, the monitoring command platform performs pedestrian evacuation on the abnormal subareas, divides the abnormal subareas into four evacuation lines according to the azimuth, reasonably matches the evacuation lines with pedestrians in the abnormal subareas, namely, the evacuation line with the shortest pedestrian matching stroke in the abnormal subareas, stops matching the corresponding evacuation lines with pedestrians if the number of pedestrians in the four evacuation lines exceeds a threshold value of the number of pedestrians, marks the evacuation line with the nearest peripheral distance of the corresponding evacuation line as a substitute evacuation line, and matches the substitute evacuation line with the pedestrians.
The working principle of the invention is as follows:
the emergency mobile monitoring command platform based on the Internet of things monitors an area through an area monitoring unit, a monitoring area boundary is set, the area in the monitoring area boundary is marked as a monitoring area, then the monitoring area is divided into a plurality of sub-areas, data information of each sub-area is obtained, the data information of the sub-areas is analyzed, the data information corresponds to the sub-areas one by one, a monitoring time threshold is set, the monitoring time threshold is divided into time segments with one hour as a unit interval time, the maximum pedestrian flow quantity, average walking speed and total number of pedestrians in the monitoring time threshold are obtained, the data information monitoring coefficient Xi in the sub-areas is obtained through a formula, and the data information monitoring coefficient Xi in the sub-areas is compared with the monitoring coefficient threshold.
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.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (1)
1. The emergency mobile monitoring command platform based on the Internet of things is characterized by comprising an equipment monitoring unit, an area monitoring unit, an emergency analysis unit, a monitoring command platform, a registration login unit and a database;
the area monitoring unit is used for monitoring the area, and the specific monitoring process is as follows:
step S1: setting a monitoring area boundary, marking an area in the monitoring area boundary as a monitoring area, dividing the monitoring area into a plurality of sub-areas, marking the sub-areas as i, i=1, 2, … …, n, n being a positive integer;
step S2: acquiring data information of each sub-region, analyzing the data information of the sub-region, wherein the data information corresponds to the sub-region one by one, then setting a monitoring time threshold, dividing the monitoring time threshold into time periods with one hour as a unit interval time, and marking the divided time periods as o, o=1, 2, … … and 24;
step S3: obtaining the maximum pedestrian flow number, the average walking speed and the total number of pedestrians staying in the sub-area within the monitoring time threshold, and marking the maximum pedestrian flow number, the average walking speed and the total number of pedestrians staying in the sub-area within the monitoring time threshold as LDi, SDi and RSi respectively;
step S4: by the formula xi=β (ldixa1+sdi×a2+rsi×a3) 2 Obtaining a data information monitoring coefficient Xi in the subarea, wherein a1, a2 and a3 are proportionality coefficients, a1 is more than a2 and more than a3 is more than 0, beta is an error correction factor, and the value is 2.365;
step S5: comparing the data information monitoring coefficient Xi in the subarea with a monitoring coefficient threshold value;
after the monitoring command platform receives the abnormal subareas and the abnormal time periods, generating equipment monitoring signals and sending the equipment monitoring signals to the equipment monitoring units, and after the equipment monitoring units receive the equipment monitoring signals, monitoring area equipment in the corresponding abnormal subareas, wherein the area equipment comprises cameras and indicator lamps, the abnormal subareas are marked as p, p=1, 2, … …, y and y are positive integers, and the specific area equipment monitoring process is as follows:
step SS1: acquiring the monitoring frequency of the cameras in the abnormal subarea, and marking the monitoring frequency of the cameras in the abnormal subarea as PLp;
step SS2: acquiring the power of the indicator lamp in the abnormal subarea and the use times of the indicator lamp, and marking the power of the indicator lamp in the abnormal subarea and the use times of the indicator lamp as GLp and CSp respectively;
step SS3: by the formula
Acquiring a device monitoring coefficient SBp in an abnormal subarea, wherein v1, v2 and v3 are proportionality coefficients, v1 is more than v2 is more than v3 is more than 0, and e is a natural constant;
step SS4: comparing the device monitoring coefficient SBp in the abnormal sub-region with a device monitoring coefficient threshold;
after receiving the equipment normal signal, the monitoring command platform generates an emergency analysis signal and sends the emergency analysis signal to the emergency analysis unit, and the emergency analysis unit receives the emergency analysis signal to perform early warning analysis on the abnormal subareas, wherein the specific early warning analysis process is as follows:
step T1: acquiring the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea, and marking the temperature rising speed, the air flow speed and the carbon dioxide content rising speed of the abnormal subarea as WDSp, KLDp and YSSp respectively;
step T2: by the formula
Acquiring an early warning analysis coefficient FXp of the abnormal subarea, wherein s1, s2 and s3 are proportionality coefficients, s1 is more than s2 is more than s3 is more than 0, alpha is an error correction factor, and the value is 1.562;
step T3: comparing the early warning analysis coefficient FXp of the abnormal subarea with an early warning analysis coefficient threshold;
step T4: after receiving the emergency adjustment signals and the corresponding abnormal subareas, the monitoring command platform performs pedestrian evacuation on the abnormal subareas, divides the abnormal subareas into four evacuation lines according to the azimuth, reasonably matches the evacuation lines with pedestrians in the abnormal subareas, namely, the evacuation line with the shortest pedestrian matching stroke in the abnormal subareas, stops matching the corresponding evacuation lines with pedestrians if the number of pedestrians in the four evacuation lines exceeds a threshold value of the number of pedestrians, marks the evacuation line with the nearest peripheral distance of the corresponding evacuation line as a substitute evacuation line, and matches the substitute evacuation line with the pedestrians;
the registration login unit is used for submitting manager information and monitor information through the mobile phone terminal for registration, and storing the successfully registered manager information and monitor information in data, wherein the manager information comprises the name, age, time of entering and mobile phone number of the real name authentication of the manager, and the monitor information comprises the name, age, time of entering and mobile phone number of the real name authentication of the monitor.
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