CN113628472A - Community security control system and method based on Internet of things - Google Patents

Community security control system and method based on Internet of things Download PDF

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CN113628472A
CN113628472A CN202111168610.9A CN202111168610A CN113628472A CN 113628472 A CN113628472 A CN 113628472A CN 202111168610 A CN202111168610 A CN 202111168610A CN 113628472 A CN113628472 A CN 113628472A
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community
fire fighting
unit
information
lane
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徐忠建
计宏
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Jiangsu Dream Iot Co ltd
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Jiangsu Dream Iot Co ltd
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    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/09—Arrangements for giving variable traffic instructions
    • G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
    • G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
    • G08G1/096833—Systems involving transmission of navigation instructions to the vehicle where different aspects are considered when computing the route
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
    • G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
    • G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
    • G01S19/42—Determining position
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0125—Traffic data processing
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
    • G08G1/0137—Measuring and analyzing of parameters relative to traffic conditions for specific applications
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
    • G16Y40/00—IoT characterised by the purpose of the information processing
    • G16Y40/50—Safety; Security of things, users, data or systems

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Abstract

The invention discloses a community security control system and method based on the Internet of things, and relates to the technical field of instruction sending and alarming, wherein the system comprises a community property information acquisition module, a fire fighting lane information processing module and a community security monitoring module; the community property information acquisition module is used for receiving an alarm signal of a fire truck in a community and acquiring information of the fire truck in the community; the fire fighting lane information processing module is used for arranging an optimal path for the fire fighting truck to reach the destination position from the community position according to the acquired information, so that the fire fighting truck can reach the destination position at the highest speed; the community security monitoring module is used for acquiring position information of pedestrians in a community when the pedestrians walk and monitoring the relative positions of the pedestrians and the fire fighting lane, so that the pedestrians in the community can not prolong the time of the fire fighting truck parked in the fire fighting lane; the safety of the community can be guaranteed through the community security monitoring module; through alarm information, the fire fighting truck can reach the rescue position at the fastest speed.

Description

Community security control system and method based on Internet of things
Technical Field
The invention relates to the technical field of instruction transmitting and alarming, in particular to a community security control system and method based on the Internet of things.
Background
Security control work in communities is a popular research topic, which is widely researched; the community is a large group which is formed by gathering a plurality of groups and is mutually associated in a certain field, and the community is a miniature of a macroscopic society; a community is a population group in a particular area;
particularly, when a fire or other emergency occurs in the community, the community work at the moment is very important; the community needs to arrange the fire-fighting vehicles to reach the destination position in a short time in time to extinguish the fire, so that the life safety of residents and the public property safety of the community are guaranteed; in this regard, it is necessary to arrange an optimal path from the fire engine to the destination, thereby reducing the waiting time of the fire engine on the path; in Chinese patent: the invention patent with application number 202110087151.5 and publication number 2021.5.18 discloses a path planning method based on equivalent road resistance analysis and considering dynamic availability of a fire hydrant, wherein the passing speed of a fire truck in a road section is judged by vehicle density in the specification; in the analysis process, however, only the speed of each road section is predicted, but the road sections are divided into a main road section and a small road section, the specific consumed speed of each road section is not judged, and only the speed of the total road section is analyzed; make the fire engine speed analysis of traveling at concrete highway section not accurate, consequently, need improve this problem, guarantee the safety that the fire engine can in time ensure the community, at this in-process, need the thing networking to assist it, guarantee in the community optional position department, can both in time feed back information to the terminal.
Disclosure of Invention
The invention aims to provide a community security control system and method based on the Internet of things, and aims to solve the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a community security control system based on the Internet of things comprises a community property information acquisition module, a fire fighting lane information processing module and a community security monitoring module;
the community property information acquisition module is used for receiving an alarm signal of a fire truck in a community and acquiring information of the fire truck in the community;
the fire fighting lane information processing module is used for arranging an optimal path for the fire fighting truck to reach the destination position from the community position according to the acquired information, so that the fire fighting truck can reach the destination position at the highest speed;
the community security monitoring module acquires position information of pedestrians in a community when the pedestrians walk and monitors the relative positions of the pedestrians and the fire fighting lane, and the time that the fire fighting truck is parked in the community is guaranteed not to be delayed;
the fire fighting lane information processing module comprises a vehicle flow density prediction unit, an optimal path selection unit, a pre-estimated time determination unit and a fire fighting lane occupation probability analysis unit;
the traffic flow density prediction unit acquires traffic flow information in a historical time period and predicts the current traffic flow information; thereby judging the influence of the vehicle flow on the running speed of the fire truck on the path;
the optimal path selection unit selects an optimal path which reaches the destination position through the optimal speed according to the traffic flow information on the path;
the estimated time determining unit estimates the final arrival time of the fire fighting truck according to the position of the fire fighting truck and the selected optimal path;
the fire fighting lane occupation probability analysis unit is used for obtaining the probability of the fire fighting lane being occupied by social vehicles according to the traffic flow information in the current time period;
the output end of the vehicle flow density prediction unit is connected with the input ends of the fire fighting lane occupation probability analysis unit and the optimal path selection unit; the output end of the estimated time determining unit is connected with the input end of the traffic flow density predicting unit;
furthermore, the community property information acquisition module comprises a fire fighting truck signal receiving unit, a GPS positioning unit, a two-dimensional plane display unit and a historical data acquisition unit;
the fire fighting truck signal receiving unit is used for receiving a signal when the fire fighting truck arrives in a community; thereby being capable of distributing an optimal path for the fire truck in time;
the GPS positioning unit is used for positioning the positions of vehicles and pedestrians in the community and transmitting positioning information to the two-dimensional plane display unit;
the two-dimensional plane display unit is used for receiving the positioning information and displaying the positioning information in the set two-dimensional plane model, so that the information of vehicles and pedestrians in the community can be clearly known;
the historical data acquisition unit is used for acquiring traffic flow information running on a historical time period path;
the input end of the fire engine signal receiving unit is connected with the output end of the GPS positioning unit; and the output end of the GPS positioning unit is connected with the input end of the two-dimensional plane display unit.
Furthermore, the community security monitoring module comprises an angle direction calculation unit, an information comparison unit and a prompt warning unit;
the angle direction calculation unit is used for acquiring a first included angle formed by a connecting line of a first position coordinate and a second position coordinate and a connecting line of the second position coordinate and a third coordinate when the pedestrian walks to the community according to the walking position of the pedestrian in the community;
the information comparison unit is used for judging a connection line between the position coordinate of the pedestrian in the community and the intersection position of the extension line of the position and the fire fighting lane, and comparing a second included angle of the connection line and the horizontal direction with the first included angle to obtain a comparison result and transmitting the comparison result to the prompt warning unit;
the prompting and warning unit is used for early warning and reminding pedestrians not to walk towards the community direction if the first included angle is larger than the first included angle; if the first included angle is smaller than the first included angle, the fire fighting truck can be stopped in the appointed lane;
and the output end of the prompt warning unit is connected with the input ends of the angle direction calculation unit and the information comparison unit.
Further, a community security control method based on the Internet of things comprises the following steps:
s01: the community receives the fire-fighting alarm signal, acquires the position information of the fire truck, the social vehicle and the pedestrian and displays the positions on a two-dimensional plane;
s02: acquiring the position information of the nearest fire fighting lane in the position where the fire fighting truck reaches the end position, and predicting the traffic flow information in the path according to the traffic flow information in the historical time period from the position of the fire fighting truck and the path in the end position; acquiring an optimal path of the fire fighting truck through the optimal speed, predicting the time of the fire fighting truck reaching the end point position, and transmitting the time of reaching the end point to the step S03;
s03: analyzing the probability that the fire fighting vehicle is occupied by social vehicles within the estimated time of reaching the terminal position;
s04: if the probability that the fire fighting lane is occupied by the social vehicles is greater than the preset standard probability in the step S03, replacing the fire fighting lane; if the probability that the fire fighting lane is occupied by the social vehicles is smaller than the preset standard probability in the step S03, acquiring the position information of the pedestrian in the community;
s05: judging a connecting line between the position coordinate of the pedestrian in the community and the position of the fire fighting lane closest to the pedestrian, and comparing a second included angle between the connecting line and the horizontal direction with the first included angle, wherein the first included angle is an included angle formed by the connecting line of the first position coordinate and the second position coordinate and the connecting line of the second position coordinate and the third coordinate, which are obtained when the pedestrian walks to the community according to the walking position of the pedestrian in the community; if the first included angle is larger than the first included angle, early warning is carried out and the pedestrian is reminded not to continue walking in the direction; if the first included angle is smaller than the first included angle, the fire fighting truck can stop in the appointed lane.
Further, in step S02, the monitored points set in the Y = {1,2,3, · m } path are analyzed to obtain the results
The amount of traffic passing through T = {1,2,3,. i.., n } in the same historical time point is W = { W }11,w22,w33...wiq...wnmIn which w11={w1,w2,w3..wi..wnI and n are time item numbers, q and m are path item numbers, and wiThe number of traffic flows passing through the time point i;
setting a function
Figure 751608DEST_PATH_IMAGE001
；
Figure 629434DEST_PATH_IMAGE002
Refers to the coefficient, b refers to the intercept;
calculated by the following formula
Figure 573119DEST_PATH_IMAGE002
And b;
Figure 132277DEST_PATH_IMAGE003
(ii) a Predicting the traffic flow number at the time point by the formula;
further obtain
Figure 110597DEST_PATH_IMAGE004
；
Wherein v ismax1Refers to the fastest speed limited in the main road,
Figure 831428DEST_PATH_IMAGE005
means error velocity; v. ofmax2Is the fastest speed, v, limited in the pathzuThe speed is slowed down due to excessive vehicles or the speed is limited by the interpenetration of pedestrians among vehicles, and wh is the standard traffic flow number;
if v (w) is detectedi)>v(wk) When is, represents wkCompared with wiThe corresponding path is more optimal, and w is selectedkThe corresponding path is an optimal path, the selected path information is transmitted to the community terminal, and the information is transmitted to the fire fighting truck terminal;
if v (w) is detectedi)<v(wk) When is, represents wiCompared with wkThe corresponding path is more optimal, and w is selectediThe corresponding path is an optimal path, the selected path information is transmitted to the community terminal, and the information is transmitted to the fire fighting truck terminal;
obtaining the time of the fire engine reaching the end position, specifically s0= L/V (w)nm) Wherein L isThe distance between the fire fighting truck and the fire fighting lane is the distance of the selected optimal path; s0 refers to the estimated time.
In step S03, obtaining a time period when the fire fighting truck departs from the community at time point S1 and estimated time point S0, and detecting that the number of vehicles staying in a fire fighting lane within a preset radius range in the time period S0-S1 is h and the number of remaining empty parking spaces is x; if h-x is detected to be greater than 0, the probability D that the fire fighting lane is occupied is larger than the preset standard probability, and the social vehicles are monitored and reminded through an external device arranged in the community; and if h-x is detected to be less than 0, the probability D that the fire fighting lane is occupied by the social vehicles is smaller than the preset standard probability.
In step S05, it is acquired that the real-time walking position of the pedestrian in the community is { (a)1,b1),(a2,b2),(a3,b3)...(ao,bo) -o refers to the number of steps of the pedestrian; the position coordinates of each vertex of the fire fighting lane are
Figure 527989DEST_PATH_IMAGE006
；
Establishing a rectangular coordinate system, and detecting a first position coordinate (a) of the pedestrian walkingg,bg) And second position coordinates (a)f,bf) Is connected to the second position coordinate (a)f,bf) And third position coordinates (a)q,bq) The calculation step of the first included angle formed by the connecting line is as follows;
Figure 625258DEST_PATH_IMAGE007
setting the coordinates (a) of the position of the pedestrian in the communityd，bd) A line between the extension line of the position and the intersection position () of the fire fighting lane, and a second included angle between the line and the horizontal direction
Figure 458085DEST_PATH_IMAGE008
The calculation steps are as follows:
set up a rectangular coordinate system, then
Figure 618326DEST_PATH_IMAGE009
；
If it is detected
Figure 536604DEST_PATH_IMAGE010
And early warning and reminding the pedestrian not to continue to run towards the current direction if detecting
Figure 437564DEST_PATH_IMAGE011
In time, the fire engine can smoothly stop in the lane.
The external playing device is monitoring video and public address equipment.
Compared with the prior art, the invention has the following beneficial effects: through the community security monitoring module who sets up, trail the location to the pedestrian position in the community for pedestrian position can not block the fire engine and park in the fire engine lane in the community, can not delay the rescue time of fire engine, guarantees that the fire engine lane can not be occupied by social vehicle. Monitoring and analyzing the positions of pedestrians, fire trucks and social vehicles in the community through the external device; the pedestrians or social vehicles in the community can not occupy the fire fighting lane; the optimal path selection unit is used for monitoring the speed of the fire fighting truck in different paths reaching the end position, and the speed of the fire fighting truck when running on a main road and a small road is reasonably controlled, so that the fire fighting truck can reach the end position at the highest speed, and the optimal path is arranged for the fire fighting truck; the probability of the social vehicle occupying the fire fighting lane is analyzed by using the fire fighting lane occupation probability analysis unit, so that the fire fighting vehicle is not privately occupied.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic block diagram of the present invention;
FIG. 2 is a schematic representation of the steps of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-2, the present invention provides the following technical solutions: a community security control system based on the Internet of things comprises a community property information acquisition module, a fire fighting lane information processing module and a community security monitoring module;
the community property information acquisition module is used for receiving an alarm signal of a fire truck in a community and acquiring information of the fire truck in the community;
the fire fighting lane information processing module is used for arranging an optimal path for the fire fighting truck to reach the destination position from the community position according to the acquired information, so that the fire fighting truck can reach the destination position at the highest speed;
the community security monitoring module acquires position information of pedestrians in a community when the pedestrians walk and monitors the relative positions of the pedestrians and the fire fighting lane, and the time that the fire fighting truck is parked in the community is guaranteed not to be delayed;
the fire fighting lane information processing module comprises a vehicle flow density prediction unit, an optimal path selection unit, a pre-estimated time determination unit and a fire fighting lane occupation probability analysis unit;
the traffic flow density prediction unit acquires traffic flow information in a historical time period and predicts the current traffic flow information; thereby judging the influence of the vehicle flow on the running speed of the fire truck on the path;
the optimal path selection unit selects an optimal path which reaches the destination position through the optimal speed according to the traffic flow information on the path;
the estimated time determining unit estimates the final arrival time of the fire fighting truck according to the position of the fire fighting truck and the selected optimal path;
the fire fighting lane occupation probability analysis unit is used for obtaining the probability of the fire fighting lane being occupied by social vehicles according to the traffic flow information in the current time period;
the output end of the vehicle flow density prediction unit is connected with the input ends of the fire fighting lane occupation probability analysis unit and the optimal path selection unit; the output end of the estimated time determining unit is connected with the input end of the traffic flow density predicting unit;
furthermore, the community property information acquisition module comprises a fire fighting truck signal receiving unit, a GPS positioning unit, a two-dimensional plane display unit and a historical data acquisition unit;
the fire fighting truck signal receiving unit is used for receiving a signal when the fire fighting truck arrives in a community; thereby being capable of distributing an optimal path for the fire truck in time;
the GPS positioning unit is used for positioning the positions of vehicles and pedestrians in the community and transmitting positioning information to the two-dimensional plane display unit;
the two-dimensional plane display unit is used for receiving the positioning information and displaying the positioning information in the set two-dimensional plane model, so that the information of vehicles and pedestrians in the community can be clearly known;
the historical data acquisition unit is used for acquiring traffic flow information running on a historical time period path;
the input end of the fire engine signal receiving unit is connected with the output end of the GPS positioning unit; and the output end of the GPS positioning unit is connected with the input end of the two-dimensional plane display unit.
Furthermore, the community security monitoring module comprises an angle direction calculation unit, an information comparison unit and a prompt warning unit;
the angle direction calculation unit is used for acquiring a first included angle formed by a connecting line of a first position coordinate and a second position coordinate and a connecting line of the second position coordinate and a third coordinate when the pedestrian walks to the community according to the walking position of the pedestrian in the community;
the information comparison unit is used for judging a connection line between the position coordinate of the pedestrian in the community and the intersection position of the extension line of the position and the fire fighting lane, and comparing a second included angle of the connection line and the horizontal direction with the first included angle to obtain a comparison result and transmitting the comparison result to the prompt warning unit;
the prompting and warning unit is used for early warning and reminding pedestrians not to walk towards the community direction if the first included angle is larger than the first included angle; if the first included angle is smaller than the first included angle, the fire fighting truck can be stopped in the appointed lane;
and the output end of the prompt warning unit is connected with the input ends of the angle direction calculation unit and the information comparison unit.
Further, a community security control method based on the Internet of things comprises the following steps:
s01: the community receives the fire-fighting alarm signal, acquires the position information of the fire truck, the social vehicle and the pedestrian and displays the positions on a two-dimensional plane;
s02: acquiring the position information of the nearest fire fighting lane in the position where the fire fighting truck reaches the end position, and predicting the traffic flow information in the path according to the traffic flow information in the historical time period from the position of the fire fighting truck and the path in the end position; acquiring an optimal path of the fire fighting truck through the optimal speed, predicting the time of the fire fighting truck reaching the end point position, and transmitting the time of reaching the end point to the step S03;
s03: analyzing the probability that the fire fighting vehicle is occupied by social vehicles within the estimated time of reaching the terminal position;
s04: if the probability that the fire fighting lane is occupied by the social vehicles is greater than the preset standard probability in the step S03, replacing the fire fighting lane; if the probability that the fire fighting lane is occupied by the social vehicles is smaller than the preset standard probability in the step S03, acquiring the position information of the pedestrian in the community;
s05: judging a connecting line between the position coordinate of the pedestrian in the community and the position of the fire fighting lane closest to the pedestrian, and comparing a second included angle between the connecting line and the horizontal direction with the first included angle, wherein the first included angle is an included angle formed by the connecting line of the first position coordinate and the second position coordinate and the connecting line of the second position coordinate and the third coordinate, which are obtained when the pedestrian walks to the community according to the walking position of the pedestrian in the community; if the first included angle is larger than the first included angle, early warning is carried out and the pedestrian is reminded not to continue walking in the direction; if the first included angle is smaller than the first included angle, the fire fighting truck can stop in the appointed lane.
Further, in step S02, the monitored points set in the Y = {1,2,3, · m } path are analyzed to obtain the results
The amount of traffic passing through T = {1,2,3,. i.., n } in the same historical time point is W = { W }11,w22,w33...wiq...wnmIn which w11={w1,w2,w3..wi..wnI and n are time item numbers, q and m are path item numbers, and wiThe number of traffic flows passing through the time point i;
setting a function
Figure 124897DEST_PATH_IMAGE012
；
Figure 453110DEST_PATH_IMAGE002
Refers to the coefficient, b refers to the intercept;
b is calculated by the following formula;
Figure 593104DEST_PATH_IMAGE013
(ii) a Predicting the traffic flow number at the time point by the formula;
further obtain
Figure 297755DEST_PATH_IMAGE014
；
Wherein v ismax1Refers to the fastest speed limited in the main road,
Figure 105174DEST_PATH_IMAGE015
means error velocity; v. ofmax2Is the fastest speed, v, limited in the pathzuThe speed is slowed down due to excessive vehicles or the speed is limited by the interpenetration of pedestrians among vehicles, and wh is the standard traffic flow number;
if v (w) is detectedi)>v(wk) When is, represents wkCompared with wiThe corresponding path is more optimal, and w is selectedkThe corresponding path is an optimal path, the selected path information is transmitted to the community terminal, and the information is transmitted to the fire fighting truck terminal;
if v (w) is detectedi)<v(wk) When is, represents wiCompared with wkThe corresponding path is more optimal, and w is selectediThe corresponding path is an optimal path, the selected path information is transmitted to the community terminal, and the information is transmitted to the fire fighting truck terminal;
obtaining the time of the fire engine reaching the end position, specifically s0= L/V (w)nm) Wherein L is the distance between the fire fighting truck and the fire fighting lane, and the distance is the distance of the selected optimal path; s0 refers to the estimated time;
analyzing the traffic flow number in the historical time period in the path, and judging that the traffic flow number influences the speed in the path in different paths, so that the optimal path can be selected from the paths; since, in the path, there is usually a combination of trunk and minor roads to be able to reach the final position,
Figure 604289DEST_PATH_IMAGE016
therefore, the influence of the traffic flow in the minor roads and the main roads is analyzed, and the fire fighting vehicles can smoothly pass through the main roads and the minor roads respectively;
the vehicle flow rate and the time point are in forward distribution, and the vehicle flow rate is increased in number in a peak period, so that the current vehicle flow rate can be analyzed as soon as possible by adopting the method.
In step S03, obtaining a time period when the fire fighting truck departs from the community at time point S1 and estimated time point S0, and detecting that the number of vehicles staying in a fire fighting lane within a preset radius range in the time period S0-S1 is h and the number of remaining empty parking spaces is x; if h-x is detected to be greater than 0, the probability D that the fire fighting lane is occupied is larger than the preset standard probability, and the social vehicles are monitored and reminded through an external device arranged in the community; and if h-x is detected to be less than 0, the probability D that the fire fighting lane is occupied by the social vehicles is smaller than the preset standard probability.
In step S05, it is acquired that the real-time walking position of the pedestrian in the community is { (a)1,b1),(a2,b2),(a3,b3)...(ao,bo) -o refers to the number of steps of the pedestrian; the position coordinates of each vertex of the fire fighting lane are
Figure 231579DEST_PATH_IMAGE017
；
Establishing a rectangular coordinate system, and detecting a first position coordinate (a) of the pedestrian walkingg,bg) And second position coordinates (a)f,bf) Is connected to the second position coordinate (a)f,bf) And third position coordinates (a)q,bq) The calculation step of the first included angle formed by the connecting line is as follows;
Figure 739921DEST_PATH_IMAGE018
setting the coordinates (a) of the position of the pedestrian in the communityd，bd) The intersection point position of the extension line of the position and the fire fighting lane
Figure 136267DEST_PATH_IMAGE019
A second included angle between the connecting line and the horizontal direction and a second included angle between the connecting line and the horizontal direction
Figure 806283DEST_PATH_IMAGE020
The calculation steps are as follows:
set up a rectangular coordinate system, then
Figure 920869DEST_PATH_IMAGE021
；
If it is detected
Figure 701744DEST_PATH_IMAGE022
Timely, early warning and reminding pedestriansDo not continue to drive in the current direction, if it is detected
Figure 504263DEST_PATH_IMAGE023
When the fire engine is stopped, the fire engine can smoothly stop in the lane;
when the pedestrian walks in the community, the pedestrian cannot be predicted in advance to walk in the direction of the fire lane or walk away from the direction, so that the first included angle is calculated; through the contrast of first contained angle and second contained angle, whether the direction of assay out the pedestrian and traveling can disturb the fire engine and park in the fire control lane. The external playing device is monitoring video and public address equipment.
Example 1: obtaining the real-time walking position of the pedestrian in the community as { (a)g,bg),(af,bf),(aq,bq) } = { (150,450), (620,1000), (1200,1800) }, o means the number of steps of the pedestrian; the position coordinates of each vertex of the fire fighting lane are
Figure 345180DEST_PATH_IMAGE024
={(900,1200),(900,540),(1500,1200),(1500,540)}；
And (3) establishing a rectangular coordinate system, wherein a specific formula of the first included angle is as follows:
Figure 212642DEST_PATH_IMAGE025
setting the coordinates (a) of the position of the pedestrian in the communityf，bf) A second included angle between the connection line and the horizontal direction, and a connection line between the connection line and the intersection point position (950,1240) of the extension line of the position and the fire fighting lane, the calculation steps of the second included angle are as follows:
set up a rectangular coordinate system, then
Figure 797207DEST_PATH_IMAGE026
；
And detecting that the speed is more than 90 and 40, and early warning and reminding the pedestrian not to continue driving towards the current direction.
Example 2: obtaining the real-time walking position of the pedestrian in the community as { (a)g,bg),(af,bf),(aq,bq) } = { (1000,1600), (1250,1750), (1100,1300) }, o means the number of steps of a pedestrian; the position coordinates of each vertex of the fire fighting lane are
Figure 168145DEST_PATH_IMAGE024
={(900,1200),(900,540),(1500,1200),(1500,540)}；
And (3) establishing a rectangular coordinate system, wherein a specific formula of the first included angle is as follows:
Figure 179963DEST_PATH_IMAGE027
setting the coordinates (a) of the position of the pedestrian in the communityf，bf) A second included angle between the connection line and the horizontal direction, and a connection line between the connection line and the intersection point position (950,1240) of the extension line of the position and the fire fighting lane, the calculation steps of the second included angle are as follows:
establishing a rectangular coordinate system;
Figure 269142DEST_PATH_IMAGE028
and detecting that the speed is more than 90 and 60, and early warning and reminding the pedestrian not to continue driving towards the current direction.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (8)

1. The utility model provides a security protection control system of community based on thing networking which characterized in that: the system comprises a community property information acquisition module, a fire fighting lane information processing module and a community security monitoring module;
the community property information acquisition module is used for receiving an alarm signal of a fire truck in a community and acquiring information of the fire truck in the community;
the fire fighting lane information processing module is used for arranging an optimal path for a fire fighting truck to reach a destination position from a community position according to the acquired information;
the community security monitoring module is used for acquiring position information of pedestrians in a community during walking and monitoring the relative positions of the pedestrians and the fire fighting lane;
the fire fighting lane information processing module comprises a vehicle flow density prediction unit, an optimal path selection unit, a pre-estimated time determination unit and a fire fighting lane occupation probability analysis unit;
the traffic flow density prediction unit acquires traffic flow information in a historical time period and predicts the current traffic flow information;
the optimal path selection unit selects an optimal path reaching the end position according to traffic flow information on the path, wherein the optimal path is the path reaching the end position at the highest speed;
the estimated time determining unit estimates the final arrival time of the fire fighting truck according to the position of the fire fighting truck and the selected optimal path;
the fire fighting lane occupation probability analysis unit is used for obtaining the probability of the fire fighting lane being occupied by social vehicles according to the traffic flow information in the current time period;
the output end of the vehicle flow density prediction unit is connected with the input ends of the fire fighting lane occupation probability analysis unit and the optimal path selection unit; and the output end of the estimated time determining unit is connected with the input end of the traffic flow density predicting unit.
2. The internet of things-based community security control system according to claim 1, wherein: the community property information acquisition module comprises a fire fighting truck signal receiving unit, a GPS positioning unit, a two-dimensional plane display unit and a historical data acquisition unit;
the fire fighting truck signal receiving unit is used for receiving a signal when the fire fighting truck arrives in a community;
the GPS positioning unit is used for positioning the positions of vehicles and pedestrians in the community and transmitting positioning information to the two-dimensional plane display unit;
the two-dimensional plane display unit is used for receiving positioning information and displaying the positioning information in the set two-dimensional plane model;
the historical data acquisition unit is used for acquiring traffic flow information running on a historical time period path;
the input end of the fire engine signal receiving unit is connected with the output end of the GPS positioning unit; and the output end of the GPS positioning unit is connected with the input end of the two-dimensional plane display unit.
3. The internet of things-based community security control system according to claim 1, wherein: the community security monitoring module comprises an angle direction calculation unit, an information comparison unit and a prompt warning unit;
the angle direction calculation unit is used for acquiring a first included angle formed by a connecting line of a first position coordinate and a second position coordinate and a connecting line of the second position coordinate and a third coordinate when the pedestrian walks to the community according to the walking position of the pedestrian in the community;
the information comparison unit is used for judging a connection line between the position coordinate of the pedestrian in the community and the intersection position of the extension line of the position and the fire fighting lane, and comparing a second included angle of the connection line and the horizontal direction with the first included angle to obtain a comparison result and transmitting the comparison result to the prompt warning unit;
the prompting and warning unit is used for early warning and reminding pedestrians not to walk towards the community direction if the first included angle is larger than the second included angle; if the first included angle is smaller than the second included angle, the fire fighting truck can be stopped in the appointed lane;
and the output end of the prompt warning unit is connected with the input ends of the angle direction calculation unit and the information comparison unit.
4. A community security control method based on the Internet of things is characterized by comprising the following steps: the control method comprises the following steps:
s01: the community receives the fire-fighting alarm signal, acquires the position information of the fire truck, the social vehicle and the pedestrian and displays the positions on a two-dimensional plane;
s02: acquiring the position information of the nearest fire fighting lane in the position where the fire fighting truck reaches the end position, and predicting the traffic flow information in the path according to the traffic flow information in the historical time period from the position of the fire fighting truck and the path in the end position; acquiring an optimal path of the fire fighting truck through the optimal speed, predicting the time of the fire fighting truck reaching the end point position, and transmitting the time of reaching the end point to the step S03;
s03: analyzing the probability that the fire fighting vehicle is occupied by social vehicles within the estimated time of reaching the terminal position;
s04: if the probability that the fire fighting lane is occupied by the social vehicles is greater than the preset standard probability in the step S03, replacing the fire fighting lane; if the probability that the fire fighting lane is occupied by the social vehicles is smaller than the preset standard probability in the step S03, acquiring the position information of the pedestrian in the community;
s05: judging a connecting line between the position coordinate of the pedestrian in the community and the position of the fire fighting lane closest to the pedestrian, and comparing a second included angle between the connecting line and the horizontal direction with the first included angle, wherein the first included angle is an included angle formed by the connecting line of the first position coordinate and the second position coordinate and the connecting line of the second position coordinate and the third coordinate, which are obtained when the pedestrian walks to the community, according to the walking position of the pedestrian in the community; if the first included angle is larger than the second included angle, early warning is carried out and the pedestrian is reminded not to continue walking in the direction; and if the first included angle is smaller than the second included angle, the fire fighting truck can be stopped in the appointed lane.
5. The Internet of things-based community security control method according to claim 4, wherein the method comprises the following steps: in step S02, the number of traffic flows that T = {1,2,3,. i.. n } passes through in the same historical time point is W = { W } as analyzed by the monitoring point provided in the Y = {1,2,3,..., m } path11,w22,w33...wiq...wnmIn which w11={w1,w2,w3..wi..wnI and n are time item numbers, q and m are path item numbers, and wiThe number of traffic flows passing through the time point i;
setting a function
Figure DEST_PATH_IMAGE001
；
Figure DEST_PATH_IMAGE002
Refers to the coefficient, b refers to the intercept;
calculated by the following formula
Figure DEST_PATH_IMAGE003
And b;
Figure DEST_PATH_IMAGE004
(ii) a Predicting the traffic flow number at the time point by the formula;
further obtain
Figure DEST_PATH_IMAGE005
；
Wherein v ismax1Refers to the fastest speed limited in the main road,
Figure 363955DEST_PATH_IMAGE006
means error velocity; v. ofmax2Is the fastest speed, v, limited in the pathzuThe speed is slowed down due to excessive vehicles or the speed is limited by the interpenetration of pedestrians among vehicles, and wh is the standard traffic flow number;
if v (w) is detectedi)>v(wk) When is, represents wkCompared with wiThe corresponding path is more optimal, and w is selectedkThe corresponding path is an optimal path, the selected path information is transmitted to the community terminal, and the information is transmitted to the fire fighting truck terminal;
if v (w) is detectedi)<v(wk) When is, represents wiCompared with wkThe corresponding path is more optimal, and w is selectediThe corresponding path is an optimal path, the selected path information is transmitted to the community terminal, and the information is transmitted to the fire fighting truck terminal;
obtaining the time of the fire engine reaching the end position, specifically s0= L/V (w)nm) Wherein L is the distance between the fire fighting truck and the fire fighting lane, and the distance is the distance of the selected optimal path; s0 refers to the estimated time.
6. The Internet of things-based community security control method according to claim 4 or 5, wherein the method comprises the following steps: in step S03, obtaining a time period when the fire fighting truck departs from the community at time point S1 and estimated time point S0, and detecting that the number of vehicles staying in a fire fighting lane within a preset radius range in the time period S0-S1 is h and the number of remaining empty parking spaces is x; if h-x is detected to be greater than 0, the probability D that the fire fighting lane is occupied is larger than the preset standard probability, and the social vehicles are monitored and reminded through an external device arranged in the community; and if h-x is detected to be less than 0, the probability D that the fire fighting lane is occupied by the social vehicles is smaller than the preset standard probability.
7. The Internet of things-based community security control method according to claim 4, wherein the method comprises the following steps: in step S05, it is acquired that the real-time walking position of the pedestrian in the community is { (a)1,b1),(a2,b2),(a3,b3)...(ao,bo) -o refers to the number of steps of the pedestrian; the position coordinates of each vertex of the fire fighting lane are
Figure DEST_PATH_IMAGE007
；
Establishing a rectangular coordinate system, and detecting a first position coordinate (a) of the pedestrian walkingg,bg) And second position coordinates (a)f,bf) Is connected to the second position coordinate (a)f,bf) And third position coordinates (a)q,bq) The calculation step of the first included angle formed by the connecting line is as follows;
Figure DEST_PATH_IMAGE008
setting the coordinates (a) of the position of the pedestrian in the communityd，bd) The intersection point position of the extension line of the position and the fire fighting lane
Figure DEST_PATH_IMAGE009
A second included angle between the connecting line and the horizontal direction and a second included angle between the connecting line and the horizontal direction
Figure DEST_PATH_IMAGE010
The calculation steps are as follows: set up a rectangular coordinate system, then
Figure DEST_PATH_IMAGE011
；
If it is detected
Figure DEST_PATH_IMAGE012
And early warning and reminding the pedestrian not to continue to run towards the current direction if detecting
Figure DEST_PATH_IMAGE013
In time, the fire engine can smoothly stop in the lane.
8. The Internet of things-based community security control method according to claim 6, wherein the method comprises the following steps: the external playing device is monitoring video and public address equipment.
CN202111168610.9A 2021-10-08 2021-10-08 Community security control system and method based on Internet of things Pending CN113628472A (en)

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