WO2019085082A1 - 出险待命位置确定方法、装置、计算机设备和存储介质 - Google Patents

出险待命位置确定方法、装置、计算机设备和存储介质 Download PDF

Info

Publication number
WO2019085082A1
WO2019085082A1 PCT/CN2017/112656 CN2017112656W WO2019085082A1 WO 2019085082 A1 WO2019085082 A1 WO 2019085082A1 CN 2017112656 W CN2017112656 W CN 2017112656W WO 2019085082 A1 WO2019085082 A1 WO 2019085082A1
Authority
WO
WIPO (PCT)
Prior art keywords
risk
map
information
thermal
coordinate points
Prior art date
Application number
PCT/CN2017/112656
Other languages
English (en)
French (fr)
Inventor
褚秋实
张岳江
Original Assignee
平安科技（深圳）有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 平安科技（深圳）有限公司 filed Critical 平安科技（深圳）有限公司
Publication of WO2019085082A1 publication Critical patent/WO2019085082A1/zh

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/29—Geographical information databases
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/953—Querying, e.g. by the use of web search engines
    • G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries

Definitions

  • the present application relates to the field of electronic maps, and in particular, to a method, apparatus, computer device, and computer readable storage medium for determining a safe standby position.
  • a method, apparatus, computer device, and computer readable storage medium for determining a safe standby position are provided.
  • a method for determining a position of a standby comprising:
  • the time point of the risk of the historical case information is matched with the standby time period, and the risk area information of the historical case information is matched with the information to be inspected;
  • a safe standby position is determined based on the thermal image.
  • a safe standby position determining device comprising:
  • a standby determination module configured to determine a standby time period and information to be inspected
  • a case query module configured to query historical case information, where a time point of the historical case information matches the standby time period, and the risk area information of the historical case information matches the information to be inspected;
  • a coordinate point obtaining module configured to acquire a risk coordinate point included in the historical case information
  • a distance determining module configured to determine, in the acquired risk coordinate points, a linear distance between each of the risk coordinate points and other risk coordinate points;
  • a thermal value obtaining module configured to obtain a thermal power value of each of the risk coordinate points according to the linear distance
  • a thermal image generation module configured to import each of the risk coordinate points and corresponding thermal values into the map to generate a thermal image on the map
  • a position determining module configured to determine a safe standby position according to the thermal image.
  • One or more non-transitory readable storage mediums storing computer readable instructions, when executed by one or more processors, cause the one or more processors to perform the steps of: determining The standby time period and the information to be inspected; the historical case information is queried, the time point of the historical case information matches the standby time period, and the risk area information of the historical case information matches the information to be inspected; Obtaining a risk coordinate point included in the historical case information; determining, in the acquired risk point, a linear distance between each of the risk coordinate points and other risk coordinate points; obtaining each of the risk coordinate points according to the straight line distance Thermal value; will each The risk coordinate point and the corresponding thermal value are imported into the map to generate a thermal image on the map; and the risk standby position is determined according to the thermal image.
  • a computer device comprising a memory and one or more processors, the memory storing computer readable instructions, the computer readable instructions being executed by the processor, causing the one or more processors to execute The following steps: determining the standby time period and the information to be inspected; querying the historical case information, the time point of the historical case information matching the standby time period, and the risk area information of the historical case information and the to-be-investigated Matching the regional information; obtaining the risk coordinate points included in the historical case information; determining the linear distance between each of the risk coordinate points and the other risk coordinate points in the acquired risk coordinate points; obtaining each according to the straight line distance Determining the thermal value of the dangerous coordinate point; importing each of the risk coordinate points and the corresponding thermal power value into the map to generate a thermal image on the map; and determining the risk standby position according to the thermal image.
  • 1 is an application environment diagram of a method for determining a risk standby position in an embodiment
  • FIG. 2 is a schematic flow chart of a method for determining a standby position in an embodiment
  • FIG. 3 is a schematic diagram of generating a thermal image in a map according to a method for determining a standby position according to a risk
  • FIG. 4 is a schematic flow chart of a method for determining a risk standby position in another embodiment
  • FIG. 5 is a structural block diagram of an apparatus for determining a standby position in an embodiment
  • FIG. 6 is a structural block diagram of an apparatus for determining a standby position in another embodiment
  • FIG. 7 is a structural block diagram of an apparatus for determining a standby position in an embodiment
  • FIG. 8 is a structural block diagram of an apparatus for determining a standby position in another embodiment
  • Figure 9 is a block diagram showing the structure of a computer device in an embodiment.
  • first quotient value
  • second quotient value
  • first quotient value may be referred to as a second quotient value without departing from the scope of the present application
  • second quotient value may be referred to as a first quotient value.
  • Both the first quotient value and the second quotient value are quotient values, but they are not the same quotient value.
  • FIG. 1 is an application environment diagram of a method for determining a standby position in an embodiment.
  • the risk standby position determination method is applied to a risk standby position determination system.
  • the out-of-life standby location determining system includes a terminal 110 and a server 120.
  • the terminal 110 and the server 120 are connected through a network.
  • the terminal 110 may specifically be a desktop terminal or a mobile terminal, and the mobile terminal may specifically be at least one of a mobile phone, a tablet computer, a notebook computer, and the like.
  • the server 120 can be implemented by a stand-alone server or a server cluster composed of a plurality of servers.
  • a method for determining a risk standby position is provided. This embodiment is mainly illustrated by the method being applied to the server 120 in FIG. 1 described above. Referring to FIG. 2, the method for determining the location of the emergency standby includes the following steps:
  • the standby time period is the time period when the staff needs to take risks.
  • the standby time period may specifically be a time period between the whole points, for example, a time period from 10:00 am to 11:00 am.
  • the information to be inspected is the information corresponding to the area where the staff needs to go out.
  • the information to be inspected may specifically be a street name or a code name.
  • the time period and area information are selected on the terminal, and the selected time period and area information are sent to the server.
  • the server determines the standby time period according to the received time period, and determines the to-be-searched area information in the survey area information list according to the received area information.
  • the server sends an information determining instruction to the terminal, so that the terminal locates the terminal itself according to the information determining instruction, acquires the location information of the terminal, and obtains the time information recorded by the terminal according to the information determining instruction, and causes the terminal to obtain the feedback.
  • Location information and time information to the server. After receiving the location information and the time information, the server determines the to-be-searched area information according to the received location information, and determines the standby time period according to the received time information.
  • S204 Query historical case information, the time point of the historical case information matches the standby time period, and the risk area information of the historical case information matches the area information to be inspected.
  • the historical case information is the information included in the historical case.
  • the time of the accident is the time when the accident occurs.
  • the time point of the accident may specifically include the date and the time of day.
  • the date is the time information identifying a certain day, which can be expressed in years, months and days, such as September 20, 2017.
  • the intraday time point is the time information indicating a specific time in a natural day, which can be expressed in hours, minutes and seconds, such as 18:30:20.
  • the risk area information is the information corresponding to the area where the risk is located.
  • the risk area information may specifically be a street name or a code name.
  • the server filters the historical case information by using the determined standby time period and the information to be inspected, and the selected historical case information includes a time point included in the time point of the accident included in the standby time period, and the included risk area
  • the information matches the information to be surveyed.
  • the risk coordinate point is the coordinate point corresponding to the position of the risk.
  • the risk coordinate point may specifically be a earth coordinate point.
  • the server obtains the risk coordinate point from the queried historical case information.
  • S206 Determine a linear distance between each of the risk coordinate points and the other risk point in the detected risk point.
  • the straight line distance can be obtained by the distance of the earth coordinate between the accidental coordinate points.
  • a risk coordinate point is sequentially selected in the detected risk point, and a linear distance between the risk point and the other risk point is determined, until each of the inquired coordinate points is determined and the other risk coordinates are determined.
  • the straight line distance between points is determined.
  • round() is a rounding function
  • asin() is an inverse sine function
  • sqrt() is an square root function
  • pow() is a power function
  • sin() is a sine function
  • cos() is a cosine
  • pi() is the value that returns the pi
  • $p1_x and $p1_y are the coordinates of the selected risk point
  • $p2_x and $p2_y are the coordinates of the other risk points.
  • the thermal value is a numerical value.
  • the magnitude of the thermal value is positively correlated with the number of other risky coordinate points corresponding to the straight line distance, and the magnitude of the thermal force value is inversely related to the magnitude of the linear distance when the number of other risky coordinate points corresponding to the straight line distance is constant.
  • the distance corresponding to the risk coordinate point is divided by 100 to obtain the distance quotient, and the integer part of the distance quotient is selected, and the number N of the statistical integer part is less than 20, and the 20*N minus the integer part is added. And, the corresponding thermal value of the risk point is obtained.
  • the number of other risky coordinate points corresponding to the straight line distance in the preset distance interval is counted according to the distance between each of the insured coordinate points and the other insured coordinate points that are inquired, and the obtained quantity is defined as the number.
  • the corresponding thermal value of the accidental coordinate point is defined as the number.
  • the map can be an electronic map.
  • the electronic map may specifically be a flat electronic map or a three-dimensional electronic map.
  • Each of the risk coordinate points and the corresponding thermal value are imported into the map, and the coordinate values of the accidental coordinate points and the corresponding thermal values are imported into the map through the interface of the map.
  • Map connection The port specific may be a Map API (Application Programming Interface).
  • the thermal image is an image that feeds back at least one of density, distribution, and change trend of the risk point on the map.
  • the coordinate points on the thermal image correspond to corresponding thermal values.
  • the server may import the coordinate values of each of the risk coordinate points and the values of the corresponding thermal values into the map through the interface of the map, and generate a thermal image in the map.
  • the position of the standby is the position where the staff is on standby.
  • the out-of-life standby position may be determined by the distribution information of the thermal image in the map, or may be determined according to the recommended position displayed in the map.
  • the server determines the out-of-life location in the area covered by the thermal image near the center of the area to be inspected based on the image displayed on the map by the thermal image.
  • the server selects the corresponding risk coordinate point corresponding to the largest thermal image and the corresponding risk coordinate point of the second largest thermal image according to the size of the thermal image, and determines the risk according to the midpoint of the two dangerous coordinate points. position.
  • the server separates the area to be inspected into a plurality of small areas, selects a small area with the most thermal image, and determines a safe standby position in the selected small area.
  • the above-mentioned method for determining the standby position of the risk can determine the standby time point and the information of the area to be inspected, and can query the corresponding risk point according to the time point of the risk included in the historical case information and the appearance area information, so that the detected risk point is more accurate.
  • the detected risk point according to the linear distance between each risk coordinate point and other risk coordinates, the thermal value of each risk point is obtained, and the probability of the risk point being re-risk can be visually expressed through the heat value. .
  • the thermal image generated according to the accidental coordinate point and the corresponding thermal value can intuitively express the probability that the different positions on the map may be dangerous, so that the emergency position of the fast-rising position can be accurately selected according to the thermal image, and then This reduces the time from the out-of-warranty position to the location of the risk, improving efficiency.
  • the thermal value of each of the risk coordinate points is obtained according to the linear distance, including: obtaining a corresponding linear distance of each of the risk coordinate points; and if the corresponding linear distance of the risk coordinate point is preset Within the distance interval, the number of other risky coordinate points corresponding to the straight line distance in the preset distance interval is counted; respectively, the number in the preset distance interval is multiplied by the corresponding thermal weight value of the preset distance interval, and each risk coordinate is obtained.
  • the additional thermal value corresponding to the preset distance interval is added; the additional thermal value is added to the basic thermal value to obtain the thermal value of each of the accidental coordinate points.
  • the preset distance interval is a range of a straight line distance from the risk coordinate point.
  • the preset distance interval may be 0 to 1000 meters or 1000 meters to 2000 meters.
  • the thermodynamic weight is the value that calculates the thermal value.
  • the heat weight may specifically be 50 or 20.
  • the basic thermal values of each risk point are the same.
  • the basic thermal value may specifically be 10.
  • the server obtains a corresponding linear distance of each of the risk coordinate points.
  • the corresponding linear distance of the risk coordinate point is within the preset distance interval
  • the other risk coordinate points corresponding to the linear distance are marked, and the number of times of the mark is counted.
  • Each additional thermal value corresponding to each of the preset distance ranges for each of the risk coordinate points. Adding each additional thermal value and adding a preset basic thermal value to obtain the thermal value of each risk point
  • the calculation is performed according to the preset distance interval, which can simplify the calculation process, and quickly calculate the thermal value according to the number of other accidental coordinate points corresponding to the straight line distance. In turn, the efficiency of calculating the thermal value of each risk point is improved.
  • each of the risk coordinate points and the corresponding thermal value are imported into the map, and the thermal image is generated on the map, including: importing each of the risk coordinate points and the corresponding thermal value into the map; Determine the position of each risk coordinate point in the map; mark each risk coordinate point with the corresponding heat value; on the map, mark the heat value with other coordinate points on the map according to the straight line distance from the risk coordinate point; other coordinate points and The larger the linear distance of the accidental coordinate point, the smaller the corresponding thermal value; the thermal image is generated according to the thermal value marked on the map.
  • each coordinate point in the area covered by the thermal image in the map has a corresponding thermal value, and the greater the distance between the other coordinate points in the area covered by the thermal image and the insured coordinate point, the smaller the corresponding thermal value.
  • the thermal image can specifically use different colors to distinguish different thermal values.
  • the linear distance between the other coordinate points on the map and the risk coordinate point and the thermal value of the other coordinate points may be linear negative correlation, for example, the thermal value of the other coordinate points is Y, and the thermal value of the dangerous coordinate point is a, The distance between the other coordinate points and the risk point is X.
  • the negative correlation coefficient of X is -b
  • Y a-bX, where 0 ⁇ X ⁇ a/b.
  • the linear distance between other coordinate points on the map and the accidental coordinate points and the thermal values of other coordinate points may also be nonlinear negative correlations.
  • the thermal value of other coordinate points is Z
  • the thermal value of the dangerous coordinate point is c 2
  • FIG. 3 is a schematic diagram of generating a thermal image in a map according to a safe standby position determination method in one embodiment.
  • Each risk coordinate point and corresponding thermal value are imported into the map to determine the position of each risk coordinate point in the map. Mark each fired coordinate point with the corresponding thermal value, and mark the thermal value on the map according to the distance from the accidental coordinate point, and render the color according to the magnitude of the thermal value to the corresponding coordinate point, so that the color is rendered.
  • the post map generates a thermal image. Wherein, according to the size of the thermal image imaged on the map, the range of the area covered by the thermal image 306 is larger than the range covered by the thermal image 304, and the range covered by the thermal image 304 is larger than the range covered by the thermal image 302.
  • the corresponding thermal value of the coordinate point in the black area in the thermal image is greater than the corresponding thermal value of the coordinate point in the mesh area, and the corresponding thermal value of the coordinate point in the mesh area is greater than the corresponding thermal value of the coordinate point in the twill area.
  • a heat map is generated on the map, so that the map can be visually observed according to the generated heat map.
  • the thermal value of each coordinate point is importing the risk coordinate points and the corresponding thermal power values into the map, and marking the thermal power values on the coordinate points in the map.
  • the method further includes: determining a historical date and time period; querying historical case information, matching the time point of the historical case information with the standby time period, and historical case information
  • the information of the risk area is matched with the information of the area to be inspected, and further includes: querying the historical case information, and the time information of the historical case information includes the time zone of the standby and the historical date and time period, and the information of the risk area of the historical case information and the to-be-investigated The area information matches.
  • the historical date and time period is the time period in which the insurance is located.
  • the historical date period may specifically include a date.
  • the date is the time information identifying a certain day, which can be expressed by the year, month and day, such as August 20, 2017.
  • the standby time period is from 14 o'clock to 15 o'clock
  • the historical date and time period is determined to be from January 1 to February 28.
  • the risk location point included in the historical case information is queried, and the time point of the risk included in the historical case information is matched with the standby time period and the historical date time period, and the included risk area information matches the information to be inspected.
  • thermal images in different months or seasons can be generated, thereby analyzing the influence of different months or seasons on the risk coordinate points according to the generated thermal image, and further, according to the historical date and time period.
  • the generated thermal image determines the standby position to stand by, and can reach the risk location more quickly, improving efficiency.
  • determining the out-of-service location according to the thermal image includes: querying a road included in the area specified by the to-be-searched area information in the map; and obtaining a corresponding thermal image of each of the risky coordinate points along the road by the coordinate point on the statistical map.
  • the sum of the straight line distances of the covered areas; the coordinate point with the shortest sum of the straight lines is selected as the out-of-life standby position.
  • the road is the road displayed in the map.
  • the road can be adjusted according to the way the staff travels. For example, when the travel mode is a motor vehicle, the motor vehicle lane is selected. If the travel mode is non-motor vehicle or walking, the non-motor vehicle lane and the sidewalk are selected.
  • the selected travel mode is a motor vehicle
  • the motor vehicle lane included in the area specified by the information to be surveyed in the map is inquired, and the coordinate image on the statistical map arrives at the corresponding thermal image of each accident coordinate point along the motor vehicle lane.
  • the shortest coordinate point is used as a safe standby position.
  • the time taken to reach the area covered by the thermal image from the coordinate point can be more clearly determined, thereby selecting a cost.
  • the coordinate point with the least time is used as the standby position, which leads to an increase in efficiency.
  • a method for determining a standby position includes the following steps:
  • S402. Determine a standby time period and information to be inspected.
  • S406 Determine, in the acquired risk coordinate points, a linear distance between each of the risk coordinate points and the other risk coordinate points.
  • S408 Multiply the number in the preset distance interval by the corresponding thermal weight value of the preset distance interval, and obtain an additional thermal power value corresponding to each of the risk coordinate points in the preset distance interval.
  • S422 Query a road included in an area specified by the to-be-searched area information in the map.
  • S424 Calculate the sum of the linear distances of the coordinate points on the map along the road to reach the area covered by the corresponding thermal image of each risk coordinate point.
  • the coordinate point with the shortest distance of the straight line is selected as the emergency standby position.
  • the corresponding risk point can be queried according to the time point of the risk included in the historical case information and the appearance area information, so that the detected risk point is more accurate.
  • the thermal value of each risk point is obtained, and the probability of the risk point being re-risk can be visually expressed through the heat value.
  • the thermal image generated according to the accidental coordinate point and the corresponding thermal value can intuitively express the probability that the different positions on the map may be dangerous, so that the emergency position of the fast-rising position can be accurately selected according to the thermal image, and then This reduces the time from the out-of-warranty position to the location of the risk, improving efficiency.
  • an out-of-service location determining device 500 is further provided.
  • the risk standby location determining device 500 includes: a standby determining module 502, a case inquiring module 504, a distance determining module 506, and a thermal value.
  • the standby determination module 502 is configured to determine the standby time period and the information to be inspected.
  • the case querying module 504 is configured to query the historical case information, the time point of the risk of the historical case information is matched with the standby time period, and the information of the risk area of the historical case information matches the information of the area to be inspected.
  • the coordinate point obtaining module 505 is configured to acquire the risk coordinate point included in the historical case information.
  • the distance determining module 506 is configured to determine each of the risk coordinates in the acquired risk coordinate point The linear distance between the point and other risk points.
  • the thermal value acquisition module 508 is configured to obtain a thermal power value of each of the risk coordinate points according to the linear distance.
  • the thermal image generation module 510 is configured to import each of the risk coordinate points and the corresponding thermal value into the map to generate a thermal image on the map.
  • the location determining module 512 is configured to determine a risk standby location according to the thermal image.
  • the above-mentioned risk standby position determining device can query the corresponding risk coordinate point according to the time point of the risk included in the historical case information and the appearance area information, thereby making the detected risk point more accurate.
  • the thermal value of each risk point is obtained, and the probability of the risk point being re-risk can be visually expressed through the heat value.
  • the thermal image generated according to the accidental coordinate point and the corresponding thermal value can intuitively express the probability that the different positions on the map may be dangerous, so that the emergency position of the fast-rising position can be accurately selected according to the thermal image, and then This reduces the time from the out-of-warranty position to the location of the risk, improving efficiency.
  • the thermal value acquisition module 508 includes: a distance acquisition module 508d for acquiring a corresponding linear distance of each of the risk coordinate points; and a quantity statistics module 508a for corresponding to the risk coordinate point
  • the linear distance is within the preset distance interval, and the number of other risk coordinate points corresponding to the linear distance in the preset distance interval is counted
  • the additional thermal value calculation module 508b is configured to multiply the number in the preset distance interval by the pre-preparation
  • the corresponding thermal power value of the distance interval is obtained, and an additional thermal power value corresponding to each of the risk coordinate points in the preset distance interval is obtained
  • the thermal power value sum calculation module 508c is configured to add the additional thermal power value to the basic thermal power value to obtain each risk.
  • the thermal value of the coordinate point includes: a distance acquisition module 508d for acquiring a corresponding linear distance of each of the risk coordinate points; and a quantity statistics module 508a for corresponding to the risk coordinate point The linear distance is within the preset distance interval, and the
  • the thermal image generation module 510 includes: an import module 510a for importing each of the risky coordinate points and the corresponding thermal value into the map; the risk location determining module 510b is configured to determine each The position of the risk coordinate point in the map; the thermal value marking module 510c is configured to mark each of the risk coordinate points with a corresponding thermal value; on the map, mark the other coordinate points on the map according to the linear distance from the risk coordinate point. Value, the greater the linear distance between the other coordinate points on the map and the risk coordinate point, the smaller the corresponding thermal value; the thermal image imaging module 510d is used according to The thermal values marked on the map generate a thermal image.
  • the standby determination module 502 is further configured to determine a historical date period.
  • the case query module 504 is further configured to query historical case information, and the time information point included in the historical case information is simultaneously matched with the standby time period and the historical date time period, and the risk area information of the historical case information matches the area information to be inspected.
  • the location determining module 512 includes: a road query module 512a for querying a road included in an area specified by the to-be-searched area information in the map; a road distance statistics module 512b for counting The coordinate points on the map arrive at the sum of the linear distances of the areas covered by the corresponding thermal images of each of the accidental coordinate points along the road; the position selection module 512c is used to select the coordinate point with the shortest distance of the straight line as the standby standby position.
  • a computer device which may be a server or a mobile terminal.
  • the computer device includes a processor, memory, and network interface coupled by a system bus.
  • the processor of the computer device is used to provide computing and control capabilities.
  • the memory of the computer device includes a non-volatile storage medium, an internal memory.
  • the non-volatile storage medium stores operating systems and computer readable instructions.
  • the internal memory provides an environment for operation of an operating system and computer readable instructions in a non-volatile storage medium.
  • the network interface of the computer device is used to communicate with an external terminal via a network connection.
  • the computer readable instructions are executed by the processor to implement an outdated standby location determination method.
  • the display of the computer device can be a liquid crystal display or an electronic ink display that can be used to display thermal images in maps and maps.
  • the input device of the computer device may be a touch layer covered on the display screen, or may be a button, a trackball or a touchpad provided on the computer device casing, or may be an external keyboard, a touchpad or a mouse, etc., the input The device can be used to enter historical case information.
  • FIG. 9 is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation of the computer device to which the solution of the present application is applied.
  • the specific computer device may It includes more or fewer components than those shown in the figures, or some components are combined, or have different component arrangements.
  • the out-of-service location determination device can be implemented in the form of a computer readable instruction that can be executed on a computer device as shown in FIG.
  • the computer readable instructions formed by the various program modules cause the processor to perform the steps in the method of determining the risk standing position of the various embodiments of the present application described in this specification.
  • the computer device shown in FIG. 9 can perform step S202 through the standby determination module 502 in the out-of-service location determining device shown in FIG. 5.
  • the computer device can perform step S204 through the case inquiry module 504.
  • the computer device can perform step S205 through the coordinate point acquisition module 505.
  • the computer device can perform step S206 through the distance determination module 506.
  • the computer device can perform step S208 through the thermal value acquisition module 508.
  • the computer device may perform step S210 through the thermal image generation module 510.
  • the computer device can perform step S212 through the location determining module 512.
  • a computer apparatus comprising a memory and a processor, the memory storing computer readable instructions that, when executed by the processor, cause the processor to perform the steps of: determining the standby time Segment and area information to be inspected; query historical case information, the time point of the historical case information matches the standby time period, and the risk area information of the historical case information matches the area information to be inspected; and obtains the risk coordinate points included in the historical case information; In the obtained risk point, determine the linear distance between each risk coordinate point and other risk coordinate points; obtain the heat value of each risk coordinate point according to the straight line distance; import each risk point and corresponding heat value In the map, a thermal image is generated on the map; the standby position is determined based on the thermal image.
  • the computer device can query the corresponding risk coordinate point according to the time point of the risk included in the historical case information and the appearance area information, so that the detected risk point is more accurate.
  • the thermal value of each risk point is obtained, and the probability of the risk point being re-risk can be visually expressed through the heat value.
  • the thermal image generated according to the accidental coordinate point and the corresponding thermal value can visually represent different positions on the map. The probability of a risk may occur, so that the emergency position of the fast-rising position can be accurately selected according to the thermal image, thereby reducing the time from the out-of-risk position to the safe position and improving the efficiency.
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform the step of obtaining a thermal value for each of the risky coordinate points based on the linear distance, the processor is further caused to perform the steps of: acquiring each risk The corresponding linear distance of the coordinate point; if the corresponding linear distance of the accidental coordinate point is within the preset distance interval, the number of other risky coordinate points corresponding to the linear distance within the preset distance interval is counted; respectively, within the preset distance interval The number is multiplied by the corresponding thermal weight of the preset distance interval, and the additional thermal power value corresponding to each of the risk coordinate points in the preset distance interval is obtained; the additional thermal power value is added to the basic thermal value to obtain the thermal value of each of the risk coordinate points. .
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform the step of importing each of the risky coordinate points and the corresponding thermal value into the map to generate a thermal image on the map, further causing the processor to execute The steps of the following method: importing each of the risk coordinate points and the corresponding thermal value into the map; determining the position of each of the risk coordinate points in the map; marking each of the risk coordinate points with a corresponding thermal value; on the map, according to The linear distance of the accidental coordinate point marks the thermal value of other coordinate points on the map; the larger the linear distance between the other coordinate points and the accidental coordinate point, the smaller the corresponding thermal value; the thermal image is generated according to the thermal value marked on the map.
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform determining the standby time period and the to-be-searched area information, further causing the processor to perform the steps of: determining a historical date time period; processor execution Querying the historical case information, the step of matching the time of the historical case information with the standby time period, and the step of matching the risk area information of the historical case information with the information to be inspected, further causes the processor to perform the following steps: querying the historical case information
  • the historical case information includes a time point of coincidence that matches the standby time period and the historical date time period, and the risk area information of the historical case information matches the area information to be inspected.
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform the step of determining a safe standby position based on the thermal image, the processor is further caused to perform the step of: querying the specified area of the map to be inspected Roads included in the area; coordinates on the statistical map The point along the road arrives at the sum of the linear distances of the areas covered by the corresponding thermal images of each risk coordinate point; the coordinate point with the shortest sum of the straight lines is selected as the out-of-life standby position.
  • a computer readable storage medium storing computer readable instructions, the computer readable instructions being executed by a processor, causing the processor to perform the steps of: determining a standby time period and to be investigated Regional information; query historical case information, the time point of the historical case information matches the standby time period, and the risk area information of the historical case information matches the area information to be inspected; the acquisition of the historical case information includes the risk coordinate points; In the risk coordinate point, determine the linear distance between each risk coordinate point and other risk coordinate points; obtain the thermal value of each risk coordinate point according to the straight line distance; import each risk coordinate point and the corresponding heat value into the map, A thermal image is generated on the map; the standby position is determined based on the thermal image.
  • the computer readable storage medium can query the corresponding risk coordinate point according to the time point of the risk included in the historical case information and the appearance area information, so that the detected risk point is more accurate.
  • the thermal value of each risk point is obtained, and the probability of the risk point being re-risk can be visually expressed through the heat value. .
  • the thermal image generated according to the accidental coordinate point and the corresponding thermal value can intuitively express the probability that the different positions on the map may be dangerous, so that the emergency position of the fast-rising position can be accurately selected according to the thermal image, and then This reduces the time from the out-of-warranty position to the location of the risk, improving efficiency.
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform the step of obtaining a thermal value for each of the risky coordinate points based on the linear distance, the processor is further caused to perform the steps of: acquiring each risk The corresponding linear distance of the coordinate point; if the corresponding linear distance of the accidental coordinate point is within the preset distance interval, the number of other risky coordinate points corresponding to the linear distance within the preset distance interval is counted; respectively, within the preset distance interval The number is multiplied by the corresponding thermal weight of the preset distance interval, and the additional thermal power value corresponding to each of the risk coordinate points in the preset distance interval is obtained; the additional thermal power value is added to the basic thermal value to obtain the thermal value of each of the risk coordinate points. .
  • the step of generating the thermal image on the map further causes the processor to perform the following steps: importing each of the risk coordinate points and the corresponding thermal value into the map; The position of each risk coordinate point in the map; mark each fire risk point with the corresponding heat value; on the map, mark the heat value with other coordinate points on the map according to the straight line distance from the risk coordinate point; other coordinate points and risk The larger the linear distance of the coordinate point, the smaller the corresponding thermal value; the thermal image is generated according to the thermal value marked on the map.
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform determining the standby time period and the information to be inspected, the processor further causes the processor to perform the steps of: querying historical case information, historical case information The step of matching the time-out point with the standby time period and matching the risk area information of the historical case information with the information to be searched for the area, further causing the processor to perform the following steps: querying the historical case information, and the risk information point included in the historical case information At the same time, it matches the standby time period and the historical date time period, and the risk area information of the historical case information matches the area information to be inspected.
  • the processor when the computer readable instructions are executed by the processor, causing the processor to perform the step of determining a safe standby position based on the thermal image, the processor is further caused to perform the step of: querying the specified area of the map to be inspected The road included in the area; the coordinate distance of the statistical map on the road reaches the sum of the linear distances of the area covered by the corresponding thermal image of each accidental coordinate point; the coordinate point with the shortest sum of the straight line is selected as the emergency standby position.
  • Non-volatile memory can include read only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory.
  • ROM read only memory
  • PROM programmable ROM
  • EPROM electrically programmable ROM
  • EEPROM electrically erasable programmable ROM

Landscapes

  • Engineering & Computer Science (AREA)
  • Databases & Information Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Remote Sensing (AREA)
  • Alarm Systems (AREA)

Abstract

本申请涉及一种出险待命位置确定方法、装置、计算机设备和计算机可读存储介质。该出险待命位置确定方法包括：确定待命时间段和待查勘区域信息；查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配；获取历史案件信息包括的出险坐标点；在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；根据直线距离获得每个出险坐标点的热力值；将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像；根据热力图像确定出险待命位置。

Description

出险待命位置确定方法、装置、计算机设备和存储介质
本申请要求于2017年11月01日提交中国专利局、申请号为2017110573997、发明名称为“出险待命位置确定方法、装置、计算机设备和存储介质”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及电子地图领域，特别是涉及一种出险待命位置确定方法、装置、计算机设备和计算机可读存储介质。
背景技术
目前，工作人员需要呆在待查勘区域内，以处理在待查勘区域内发生的案件。然而案件发生的地点和时间并非固定的，因此选择出险待命位置，以使得工作人员在出险待命位置能够快速到达险位置。
但是，如何选择出险待命位置，往往是根据工作人员的经验来判断的，由于工作人员需要记忆大量的案件，才能判断得到出险待命位置，带有工作人员的主观意愿，不够客观。而且工作人员也并非固定不变，在更替工作人员后就更难以得到准确的出险待命位置。所以通过传统技术选出能够快速到达出险位置的出险待命位置的准确率很低，使得花费在路上的时间较长，效率很低。
发明内容
根据本申请的各种实施例，提供一种出险待命位置确定方法、装置、计算机设备和计算机可读存储介质。
一种出险待命位置确定方法，所述方法包括：
确定待命时间段和待查勘区域信息；
查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；
获取所述历史案件信息包括的出险坐标点；
在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；
根据所述直线距离获得每个所述出险坐标点的热力值；
将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及
根据所述热力图像确定出险待命位置。
一种出险待命位置确定装置，所述装置包括：
待命确定模块，用于确定待命时间段和待查勘区域信息；
案件查询模块，用于查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；
坐标点获取模块，用于获取所述历史案件信息包括的出险坐标点；
距离确定模块，用于在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；
热力值获取模块，用于根据所述直线距离获得每个所述出险坐标点的热力值；
热力图像生成模块，用于将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及
位置确定模块，用于根据所述热力图像确定出险待命位置。
一个或多个存储有计算机可读指令的非易失性可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：确定待命时间段和待查勘区域信息；查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；获取所述历史案件信息包括的出险坐标点；在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；根据所述直线距离获得每个所述出险坐标点的热力值；将每个 所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及根据所述热力图像确定出险待命位置。
一种计算机设备，包括存储器和一个或多个处理器，所述存储器中存储有计算机可读指令，所述计算机可读指令被所述处理器执行时，使得所述一个或多个处理器执行以下步骤：确定待命时间段和待查勘区域信息；查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；获取所述历史案件信息包括的出险坐标点；在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；根据所述直线距离获得每个所述出险坐标点的热力值；将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及根据所述热力图像确定出险待命位置。
本申请的一个或多个实施例的细节在下面的附图和描述中提出。本申请的其它特征、目的和优点将从说明书、附图以及权利要求书变得明显。
附图说明
为了更清楚地说明本申请实施例中的技术方案，下面将对实施例中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本申请的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其它的附图。
图1为一个实施例中出险待命位置确定方法的应用环境图；
图2为一个实施例中出险待命位置确定方法的流程示意图；
图3为一个实施例中根据出险待命位置确定方法在地图中生成热力图像的示意图；
图4为另一个实施例中出险待命位置确定方法的流程示意图；
图5为一个实施例中出险待命位置确定装置的结构框图；
图6为另一个实施例中出险待命位置确定装置的结构框图；
图7为一个实施例中出险待命位置确定装置的结构框图；
图8为另一个实施例中出险待命位置确定装置的结构框图；
图9为一个实施例中计算机设备的结构框图。
具体实施方式
为了使本申请的目的、技术方案及优点更加清楚明白，以下结合附图及实施例，对本申请进行进一步详细说明。应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
可以理解，本申请所使用的术语“第一”、“第二”等可在本文中用于描述各种元件，但这些元件不受这些术语的限制。这些术语仅用于将第一个元件与另一个元件区分。举例来说，在不脱离本申请的范围的情况下，可以将第一商值称为第二商值，且类似地，可将第二商值称为第一商值。第一商值和第二商值两者都是商值，但其不是同一商值。
图1为一个实施例中出险待命位置确定方法的应用环境图。参照图1，该出险待命位置确定方法应用于出险待命位置确定系统。该出险待命位置确定系统包括终端110和服务器120。终端110和服务器120通过网络连接。终端110具体可以是台式终端或移动终端，移动终端具体可以手机、平板电脑、笔记本电脑等中的至少一种。服务器120可以用独立的服务器或者是多个服务器组成的服务器集群来实现。
如图2所示，在一个实施例中，提供了一种出险待命位置确定方法。本实施例主要以该方法应用于上述图1中的服务器120来举例说明。参照图2，该出险待命位置确定方法具体包括如下步骤：
S202，确定待命时间段和待查勘区域信息。
其中，待命时间段是工作人员需要出险的时间段。待命时间段具体可以是整点之间的时间段，例如上午十点整至上午十一点整之间的时间段。待查勘区域信息是工作人员需要出险的区域相对应的信息。待查勘区域信息具体可以是街道名称，也可以是字符形式的代号。
在一个实施例中，在终端上选取时间段和区域信息，并将选取的时间段和区域信息发送至服务器。服务器根据接收到的时间段确定待命时间段，以及根据接收到的区域信息在查勘区域信息列表中确定待查勘区域信息。
在一个实施例中，服务器向终端发送信息确定指令，使得终端根据信息确定指令对终端自身进行定位，以获取终端的位置信息，以及根据信息确定指令获取终端记载的时间信息，并使得终端反馈获取的位置信息和时间信息至服务器。服务器在接收到位置信息和时间信息后，根据接收到的位置信息确定待查勘区域信息，以及根据接收到的时间信息确定待命时间段。
S204，查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
其中，历史案件信息是历史出险的案件所包括的信息。出险时间点是出险时的时间。出险时间点具体可以包括日期和日内时间点。其中，日期是标识某一日的时间信息，可用年、月和日来表示，比如2017年9月20日。日内时间点是表示一个自然日内具体时刻的时间信息，可用时、分和秒来表示，比如18点30分20秒。出险区域信息是出险的位置所在区域相对应的信息。出险区域信息具体可以是街道名称，也可以是字符形式的代号。
具体地，服务器通过确定的待命时间段和待查勘区域信息，对历史案件信息进行筛选，选取出的历史案件信息包括的出险时间点包括的日内时间点在待命时间段内，且包括的出险区域信息与待查勘区域信息匹配。
S205，获取历史案件信息包括的出险坐标点。
其中，出险坐标点是出险的位置相对应的坐标点。出险坐标点具体可以是地球坐标点。
具体地，服务器在根据确定的待命时间段和待查勘区域信息查询到历史案件信息后，从查询到的历史案件信息中获取出险坐标点。
S206，在查询到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离。
其中，直线距离具体可以通过出险坐标点之间的地球坐标距离来获取。
具体地，在查询到的出险坐标点中依次选定一个出险坐标点，确定该出险坐标点与其它出险坐标点之间的直线距离，直至每个查询到的出险坐标点都确定与其它出险坐标点间的直线距离。
在一个实施例中，查询到的出险坐标点为地球坐标点，根据distance＝round(6378.138*2*asin(sqrt(pow(sin(($p1_x*pi()/180-$p2_x*pi()/180)/2),2)+cos($p1_x*pi()/180)*cos($p2_x*pi()/180)*pow(sin(($p1_y*pi()/180-$p2_y*pi()/180)/2),2)))*1000)，在查询到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离。其中，distance是直线距离，round()是四舍五入函数，asin()是反正弦函数，sqrt()是开平方根函数，pow()是次方函数，sin()是正弦函数，cos()是余弦函数，pi()是返回圆周率的值，$p1_x和$p1_y是选定的出险坐标点的坐标值，$p2_x和$p2_y是其它出险坐标点的坐标值。
S208，根据直线距离获得每个出险坐标点的热力值。
其中，热力值是数值。热力值的大小与直线距离相应的其它出险坐标点的数量正相关，而在直线距离相应的其它出险坐标点的数量恒定时，热力值的大小与直线距离的大小负相关。
在一个实施例中，将出险坐标点相对应的距离除以100得到距离商，并选取距离商的整数部分，统计整数部分小于20的数量N，将20*N减去整数部分相加得到的和，得到该出险坐标点相应的热力值。
在一个实施例中，根据每个出险坐标点与查询到的其它出险坐标点间的距离，统计在预设距离区间内的直线距离相应的其它出险坐标点的数量，将得到的数量定义为该出险坐标点相应的热力值。
S210，将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像。
其中，地图可以是电子地图。电子地图具体可以是平面电子地图，也可以是三维电子地图。将每个出险坐标点及相应的热力值导入地图，可以是通过地图的接口将出险坐标点的坐标值及相应的热力值导入地图中。地图的接 口具体可以是地图API(Application Programming Interface，应用程序编程接口)。热力图像是反馈地图上出险坐标点的密度、分布和变化趋势中至少一种的图像。热力图像上的坐标点对应有相应的热力值。
具体地，服务器可将每个出险坐标点的坐标值及相应的热力值的数值通过地图的接口导入地图中，在地图中生成热力图像。
S212，根据热力图像确定出险待命位置。
其中，出险待命位置是工作人员待命的位置。出险待命位置可以是热力图像在地图中的分布信息进行确定，也可以是根据地图中显示的推荐位置进行确定。
在一个实施例中，服务器根据热力图像在地图上显示的图像，在靠近待查勘区域中心位置的热力图像所覆盖区域内确定出险待命位置。
在一个实施例中，服务器根据热力图像的大小，选取最大的热力图像相应的出险坐标点和第二大的热力图像相应的出险坐标点，根据两个出险坐标点连线的中点确定出险待命位置。
在一个实施例中，服务器将待查勘区域分离为多个小区域，选取热力图像最多的小区域，在选取的小区域内确定出险待命位置。
上述出险待命位置确定方法，通过确定待命时间段和待查勘区域信息，可以根据历史案件信息包括的出险时间点和出现区域信息查询出相应的出险坐标点，从而使得查询出来的出险坐标点更精准。而在查询到的出险坐标点中，根据每个出险坐标点与其它出险坐标点间的直线距离来获取每个出险坐标点的热力值，可以通过热力值直观地表达出险坐标点再次出险的概率。而根据出险坐标点和相应的热力值生成的热力图像，则能够直观的表现出地图上不同位置可能出险的概率，从而在根据热力图像能够精准地选出快速到达出险位置的出险待命位置，进而使得从出险待命位置抵达出险位置的时间减少，提高了效率。
在一个实施例中，根据直线距离获得每个出险坐标点的热力值，包括：获取每个出险坐标点相应的直线距离；若出险坐标点相应的直线距离在预设 距离区间内，则统计在预设距离区间内直线距离相应的其它出险坐标点的数量；分别将在预设距离区间内的数量乘以预设距离区间相应的热力权值，得到每个出险坐标点在预设距离区间相对应的附加热力值；将附加热力值加上基础热力值，得到每个出险坐标点的热力值。
其中，预设距离区间是与出险坐标点的直线距离的区间。预设距离区间具体可以是0至1000米，也可以是1000米至2000米。热力权值是计算热力值的数值。热力权值具体可以是50，也可以是20。每个出险坐标点的基础热力值一致。基础热力值具体可以是10。
具体地，服务器获取每个出险坐标点相应的直线距离，每当出险坐标点相应的直线距离在预设距离区间内时，则标记一次直线距离相应的其它出险坐标点，以标记的次数来统计在预设距离区间内直线距离相应的其它出险坐标点的数量。在服务器统计出每个出险坐标点相应的其它出险坐标点在各个预设距离区间内的数量后，分别将在各个预设距离区间内的数量乘以预设距离区间相应的热力权值，得到每个出险坐标点在各个预设距离区间相对应的各个附加热力值。将各个附加热力值相加，并加上预设的基础热力值，得到每个出险坐标点的热力值
在一个实施例中，当出险坐标点相应的直线距离在0至1000米时，统计出相应的其它出险坐标点的数量为N，以及当出险坐标点相应的距离在1000米至2000米时，统计出相应的其它出险坐标点的数量为M，将出险坐标点相应的数量N和数量M分别与热力权值50和20相乘，得到附加热力值，并将附加热力值加上基础热力值，得到每个出险坐标点的热力值P。即根据P＝10+N*50+M*20，计算出出险坐标点的热力值。
本实施例中，根据每个出险坐标点的直线距离按照预设距离区间进行统计，可以简化计算过程，快捷地根据直线距离相应的其它出险坐标点的数量计算出热力值。进而提高了计算出每个出险坐标点的热力值的效率。
在一个实施例中，将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像，包括：将每个出险坐标点及相应的热力值导入地图中； 确定每个出险坐标点在地图中的位置；将每个出险坐标点标记相应的热力值；在地图上，按照与出险坐标点的直线距离给地图上其它坐标点标记热力值；其它坐标点与出险坐标点的直线距离越大，相应的热力值越小；根据地图上标记的热力值生成热力图像。
其中，在地图中热力图像所覆盖区域内的每个坐标点都有相对应的热力值，热力图像所覆盖区域内的其它坐标点与出险坐标点的距离越大，相应的热力值越小。热力图像具体可以使用不同的颜色区分不同的热力值。
在一个实施例中，地图上其它坐标点与出险坐标点的直线距离和其它坐标点的热力值可以是线性负相关，例如其它坐标点的热力值为Y，出险坐标点的热力值为a，其它坐标点与出险坐标点的直线距离为X，在X的负相关系数为-b时，则Y＝a-bX，其中，0<X<a/b。地图上其它坐标点与出险坐标点的直线距离和其它坐标点的热力值也可以是非线性负相关，例如其它坐标点的热力值为Z，出险坐标点的热力值为c2，其它坐标点与出险坐标点的直线距离为W，在W的负相关系数为-d2时，则Z＝c2-d2W2，其中，0<W<c/d。
图3为一个实施例中，根据出险待命位置确定方法在地图中生成热力图像的示意图。将每个出险坐标点及相应的热力值导入地图中，确定每个出险坐标点在地图中的位置。将每个出险坐标点标记相应的热力值，并在地图上，按照与出险坐标点的距离给地图上其它坐标点标记热力值，根据热力值的大小对相应的坐标点渲染颜色，使得渲染颜色后的地图生成热力图像。其中，根据热力图像在地图上成像的大小，热力图像306所覆盖区域的范围大于热力图像304所覆盖区域的范围，且热力图像304所覆盖区域的范围大于热力图像302所覆盖区域的范围。热力图像中黑色区域内的坐标点相应的热力值大于网格区域内的坐标点相应的热力值，且网格区域内的坐标点相应的热力值大于斜纹区域内的坐标点相应的热力值。
本实施例中，通过将出险坐标点和相应的热力值导入地图中，并对地图中的坐标点标记热力值，使得地图上生成热力图，从而可以根据生成的热力图直观地观察到地图上各个坐标点的热力值。
在一个实施例中，确定待命时间段和待查勘区域信息之后，上述方法还包括：确定历史日期时间段；查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配，还包括：查询历史案件信息，历史案件信息包括的出险时间点同时与待命时间段和历史日期时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
其中，历史日期时间段是出险时所在的时间段。历史日期时间段具体可以包括日期。其中，日期是标识某一日的时间信息，可用年、月和日来表示，比如2017年8月20日。
在一个实施例中，确定待命时间段为14点至15点，待查勘区域信息为A4区后，再确定历史日期时间段为1月1日至2月28日。查询历史案件信息包括的出险坐标点，历史案件信息包括的出险时间点同时与待命时间段和历史日期时间段匹配、且包括的出险区域信息与待查勘区域信息匹配。
本实施例中，通过额外确定历史日期时间段，可以生成出不同月份或季节下的热力图像，从而根据生成热力图像分析出不同月份或季节对出险坐标点的影响，进而在根据历史日期时间段生成的热力图像确定的待命出险位置上待命，能够更快地抵达出险位置，提高了效率。
在一个实施例中，根据热力图像确定出险待命位置，包括：查询地图中待查勘区域信息指定的区域内所包括的道路；统计地图上的坐标点沿道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；选取直线距离总和最短的坐标点作为出险待命位置。
其中，道路是地图中显示的道路。道路可以根据工作人员的出行方式进行调整，例如出行方式为机动车时，则选择显示机动车道，若出行方式为非机动车或步行时，则选择显示非机动车道和人行道。
在一个实施例中，选定出行方式为机动车，查询地图中待查勘区域信息指定的区域内所包括的机动车道，统计地图上的坐标点沿机动车道抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和，选取直线距离总和 最短的坐标点作为出险待命位置。
本实施例中，通过计算并比较坐标点沿道路抵达热力图像所覆盖区域的直线距离的总和，可以更明确地得出从坐标点出发抵达热力图像所覆盖区域所花费的时间，从而选取一个花费时间最少的坐标点作为出险待命位置，进而使得效率得到了提高。
如图4所示，在一个实施例中，还提供了一种出险待命位置确定方法，参照图4，该出险待命位置确定方法具体包括以下步骤：
S402，确定待命时间段和待查勘区域信息。
S404，查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
S405，获取历史案件信息包括的出险坐标点。
S406，在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离。
S407，若出险坐标点相应的直线距离在预设距离区间内，则统计在预设距离区间内直线距离相应的其它出险坐标点的数量。
S408，分别将在预设距离区间内的数量乘以预设距离区间相应的热力权值，得到每个出险坐标点在预设距离区间相对应的附加热力值。
S410，将附加热力值加上基础热力值，得到每个出险坐标点的热力值。
S412，将每个出险坐标点及相应的热力值导入地图中。
S414，确定每个出险坐标点在地图中的位置。
S416，将每个出险坐标点标记相应的热力值。
S418，在地图上，按照与出险坐标点的直线距离给地图上其它坐标点标记热力值。
S420，根据地图上标记的热力值生成热力图像。
S422，查询地图中待查勘区域信息指定的区域内所包括的道路。
S424，统计地图上的坐标点沿道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和。
S426，选取直线距离总和最短的坐标点作为出险待命位置。
本实施例中，通过确定待命时间段和待查勘区域信息，可以根据历史案件信息包括的出险时间点和出现区域信息查询出相应的出险坐标点，从而使得查询出来的出险坐标点更精准。而在查询到的出险坐标点中，根据每个出险坐标点与其它出险坐标点间的直线距离来获取每个出险坐标点的热力值，可以通过热力值直观地表达出险坐标点再次出险的概率。而根据出险坐标点和相应的热力值生成的热力图像，则能够直观的表现出地图上不同位置可能出险的概率，从而在根据热力图像能够精准地选出快速到达出险位置的出险待命位置，进而使得从出险待命位置抵达出险位置的时间减少，提高了效率。
应该理解的是，虽然本申请各实施例的流程图中的各个步骤按照箭头的指示依次显示，但是这些步骤并不是必然按照箭头指示的顺序依次执行。除非本文中有明确的说明，这些步骤的执行并没有严格的顺序限制，这些步骤可以以其它的顺序执行。而且，本申请各实施例的流程图中的至少一部分步骤可以包括多个子步骤或者多个阶段，这些子步骤或者阶段并不必然是在同一时刻执行完成，而是可以在不同的时刻执行，这些子步骤或者阶段的执行顺序也不必然是依次进行，而是可以与其它步骤或者其它步骤的子步骤或者阶段的至少一部分轮流或者交替地执行。
如图5所示，在一个实施例中，还提供了一种出险待命位置确定装置500，该出险待命位置确定装置500包括：待命确定模块502、案件查询模块504、距离确定模块506、热力值获取模块508、热力图像生成模块510和位置确定模块512。
待命确定模块502，用于确定待命时间段和待查勘区域信息。
案件查询模块504，用于查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
坐标点获取模块505，用于获取历史案件信息包括的出险坐标点。
距离确定模块506，用于在获取到的出险坐标点中，确定每个出险坐标 点与其它出险坐标点间的直线距离。
热力值获取模块508，用于根据直线距离获得每个出险坐标点的热力值。
热力图像生成模块510，用于将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像。
位置确定模块512，用于根据热力图像确定出险待命位置。
上述出险待命位置确定装置，通过确定待命时间段和待查勘区域信息，可以根据历史案件信息包括的出险时间点和出现区域信息查询出相应的出险坐标点，从而使得查询出来的出险坐标点更精准。而在查询到的出险坐标点中，根据每个出险坐标点与其它出险坐标点间的直线距离来获取每个出险坐标点的热力值，可以通过热力值直观地表达出险坐标点再次出险的概率。而根据出险坐标点和相应的热力值生成的热力图像，则能够直观的表现出地图上不同位置可能出险的概率，从而在根据热力图像能够精准地选出快速到达出险位置的出险待命位置，进而使得从出险待命位置抵达出险位置的时间减少，提高了效率。
如图6所示，在一个实施例中，热力值获取模块508包括：距离获取模块508d，用于获取每个出险坐标点相应的直线距离；数量统计模块508a，用于若出险坐标点相应的直线距离在预设距离区间内，则统计在预设距离区间内直线距离相应的其它出险坐标点的数量；附加热力值计算模块508b，用于分别将在预设距离区间内的数量乘以预设距离区间相应的热力权值，得到每个出险坐标点在预设距离区间相对应的附加热力值；热力值总和计算模块508c，用于将附加热力值加上基础热力值，得到每个出险坐标点的热力值。
如图7所示，在一个实施例中，热力图像生成模块510包括：导入模块510a，用于将每个出险坐标点及相应的热力值导入地图中；出险位置确定模块510b，用于确定每个出险坐标点在地图中的位置；热力值标记模块510c，用于将每个出险坐标点标记相应的热力值；在地图上，按照与出险坐标点的直线距离给地图上其它坐标点标记热力值，地图上其它坐标点与出险坐标点的直线距离越大，则相应的热力值越小；热力图像成像模块510d，用于根据 地图上标记的热力值生成热力图像。
在一个实施例中，待命确定模块502，还用于确定历史日期时间段。案件查询模块504，还用于查询历史案件信息，历史案件信息包括的出险时间点同时与待命时间段和历史日期时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
如图8所示，在一个实施例中，位置确定模块512包括：道路查询模块512a，用于查询地图中待查勘区域信息指定的区域内所包括的道路；道路距离统计模块512b，用于统计地图上的坐标点沿道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；位置选取模块512c，用于选取直线距离总和最短的坐标点作为出险待命位置。
在一个实施例中，提供了一种计算机设备，该计算机设备可以是服务器，也可以是移动终端。当该计算机设备为服务器时，其内部结构图可以如图9所示。该计算机设备包括通过系统总线连接的处理器、存储器和网络接口。其中，该计算机设备的处理器用于提供计算和控制能力。该计算机设备的存储器包括非易失性存储介质、内存储器。该非易失性存储介质存储有操作系统和计算机可读指令。该内存储器为非易失性存储介质中的操作系统和计算机可读指令的运行提供环境。该计算机设备的网络接口用于与外部的终端通过网络连接通信。该计算机可读指令被处理器执行时以实现一种出险待命位置确定方法。该计算机设备的显示屏可以是液晶显示屏或者电子墨水显示屏，该显示屏可以用于显示地图和地图中的热力图像。该计算机设备的输入装置可以是显示屏上覆盖的触摸层，也可以是计算机设备外壳上设置的按键、轨迹球或触控板，还可以是外接的键盘、触控板或鼠标等，该输入装置可以用于输入历史案件信息。
本领域技术人员可以理解，图9中示出的结构，仅仅是与本申请方案相关的部分结构的框图，并不构成对本申请方案所应用于其上的计算机设备的限定，具体的计算机设备可以包括比图中所示更多或更少的部件，或者组合某些部件，或者具有不同的部件布置。
在一个实施例中，本申请提供的出险待命位置确定装置可以实现为一种计算机可读指令的形式，计算机可读指令可在如图9所示的计算机设备上运行。比如，图5所示的待命确定模块502、案件查询模块504、坐标点获取模块505、距离确定模块506、热力值获取模块508、热力图像生成模块510和位置确定模块512。各个程序模块构成的计算机可读指令使得处理器执行本说明书中描述的本申请各个实施例的出险待命位置确定方法中的步骤。
例如，图9所示的计算机设备可以通过如图5所示的出险待命位置确定装置中的待命确定模块502执行步骤S202。计算机设备可通过案件查询模块504执行步骤S204。计算机设备可通过坐标点获取模块505执行步骤S205。计算机设备可通过距离确定模块506执行步骤S206。计算机设备可通过热力值获取模块508执行步骤S208。计算机设备可通过热力图像生成模块510执行步骤S210。计算机设备可通过位置确定模块512执行步骤S212。
在一个实施例中，还提供了一种计算机设备，包括存储器和处理器，存储器存储有计算机可读指令，计算机可读指令被处理器执行时，使得处理器执行以下方法的步骤：确定待命时间段和待查勘区域信息；查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配；获取历史案件信息包括的出险坐标点；在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；根据直线距离获得每个出险坐标点的热力值；将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像；根据热力图像确定出险待命位置。
上述计算机设备，通过确定待命时间段和待查勘区域信息，可以根据历史案件信息包括的出险时间点和出现区域信息查询出相应的出险坐标点，从而使得查询出来的出险坐标点更精准。而在查询到的出险坐标点中，根据每个出险坐标点与其它出险坐标点间的直线距离来获取每个出险坐标点的热力值，可以通过热力值直观地表达出险坐标点再次出险的概率。而根据出险坐标点和相应的热力值生成的热力图像，则能够直观的表现出地图上不同位置 可能出险的概率，从而在根据热力图像能够精准地选出快速到达出险位置的出险待命位置，进而使得从出险待命位置抵达出险位置的时间减少，提高了效率。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行根据直线距离获得每个出险坐标点的热力值的步骤时，还使得处理器执行以下方法的步骤：获取每个出险坐标点相应的直线距离；若出险坐标点相应的直线距离在预设距离区间内，则统计在预设距离区间内直线距离相应的其它出险坐标点的数量；分别将在预设距离区间内的数量乘以预设距离区间相应的热力权值，得到每个出险坐标点在预设距离区间相对应的附加热力值；将附加热力值加上基础热力值，得到每个出险坐标点的热力值。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像的步骤时，还使得处理器执行以下方法的步骤：将每个出险坐标点及相应的热力值导入地图中；确定每个出险坐标点在地图中的位置；将每个出险坐标点标记相应的热力值；在地图上，按照与出险坐标点的直线距离给地图上其它坐标点标记热力值；其它坐标点与出险坐标点的直线距离越大，相应的热力值越小；根据地图上标记的热力值生成热力图像。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行确定待命时间段和待查勘区域信息之后，还使得处理器执行以下方法的步骤：确定历史日期时间段；处理器执行查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配的步骤时，还使得处理器执行以下方法的步骤：查询历史案件信息，历史案件信息包括的出险时间点同时与待命时间段和历史日期时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行根据热力图像确定出险待命位置的步骤时，还使得处理器执行以下方法的步骤：查询地图中待查勘区域信息指定的区域内所包括的道路；统计地图上的坐标 点沿道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；选取直线距离总和最短的坐标点作为出险待命位置。
在一个实施例中，还提供了一种计算机可读存储介质，存储有计算机可读指令，计算机可读指令被处理器执行时，使得处理器执行以下方法的步骤：确定待命时间段和待查勘区域信息；查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配；获取历史案件信息包括的出险坐标点；在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；根据直线距离获得每个出险坐标点的热力值；将每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像；根据热力图像确定出险待命位置。
上述计算机可读存储介质，通过确定待命时间段和待查勘区域信息，可以根据历史案件信息包括的出险时间点和出现区域信息查询出相应的出险坐标点，从而使得查询出来的出险坐标点更精准。而在查询到的出险坐标点中，根据每个出险坐标点与其它出险坐标点间的直线距离来获取每个出险坐标点的热力值，可以通过热力值直观地表达出险坐标点再次出险的概率。而根据出险坐标点和相应的热力值生成的热力图像，则能够直观的表现出地图上不同位置可能出险的概率，从而在根据热力图像能够精准地选出快速到达出险位置的出险待命位置，进而使得从出险待命位置抵达出险位置的时间减少，提高了效率。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行根据直线距离获得每个出险坐标点的热力值的步骤时，还使得处理器执行以下方法的步骤：获取每个出险坐标点相应的直线距离；若出险坐标点相应的直线距离在预设距离区间内，则统计在预设距离区间内直线距离相应的其它出险坐标点的数量；分别将在预设距离区间内的数量乘以预设距离区间相应的热力权值，得到每个出险坐标点在预设距离区间相对应的附加热力值；将附加热力值加上基础热力值，得到每个出险坐标点的热力值。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行将 每个出险坐标点及相应的热力值导入地图中，在地图上生成热力图像的步骤时，还使得处理器执行以下方法的步骤：将每个出险坐标点及相应的热力值导入地图中；确定每个出险坐标点在地图中的位置；将每个出险坐标点标记相应的热力值；在地图上，按照与出险坐标点的直线距离给地图上其它坐标点标记热力值；其它坐标点与出险坐标点的直线距离越大，相应的热力值越小；根据地图上标记的热力值生成热力图像。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行确定待命时间段和待查勘区域信息之后，还使得处理器执行以下方法的步骤：查询历史案件信息，历史案件信息的出险时间点与待命时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配的步骤时，还使得处理器执行以下方法的步骤：查询历史案件信息，历史案件信息包括的出险时间点同时与待命时间段和历史日期时间段匹配、且历史案件信息的出险区域信息与待查勘区域信息匹配。
在一个实施例中，计算机可读指令被处理器执行时，使得处理器执行根据热力图像确定出险待命位置的步骤时，还使得处理器执行以下方法的步骤：查询地图中待查勘区域信息指定的区域内所包括的道路；统计地图上的坐标点沿道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；选取直线距离总和最短的坐标点作为出险待命位置。
本领域普通技术人员可以理解实现上述实施例方法中的全部或部分流程，是可以通过计算机可读指令来指令相关的硬件来完成，所述的计算机可读指令可存储于一非易失性计算机可读取存储介质中，该计算机可读指令在执行时，可包括如上述各方法的实施例的流程。其中，本申请所提供的各实施例中所使用的对存储器、数据库或其它介质的任何引用，均可包括非易失性存储器。非易失性存储器可包括只读存储器(ROM)、可编程ROM(PROM)、电可编程ROM(EPROM)、电可擦除可编程ROM(EEPROM)或闪存。
以上所述实施例的各技术特征可以进行任意的组合，为使描述简洁，未 对上述实施例中的各个技术特征所有可能的组合都进行描述，然而，只要这些技术特征的组合不存在矛盾，都应当认为是本说明书记载的范围。
以上所述实施例仅表达了本申请的几种实施方式，其描述较为具体和详细，但并不能因此而理解为对发明专利范围的限制。应当指出的是，对于本领域的普通技术人员来说，在不脱离本申请构思的前提下，还可以做出若干变形和改进，这些都属于本申请的保护范围。因此，本申请专利的保护范围应以所附权利要求为准。

Claims (20)

  1. 一种出险待命位置确定方法，所述方法包括：
    确定待命时间段和待查勘区域信息；
    查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；
    获取所述历史案件信息包括的出险坐标点；
    在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；
    根据所述直线距离获得每个所述出险坐标点的热力值；
    将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及
    根据所述热力图像确定出险待命位置。
  2. 根据权利要求1所述的方法，其特征在于，所述根据所述直线距离获得每个所述出险坐标点的热力值，包括：
    获取每个所述出险坐标点相应的所述直线距离；
    若所述出险坐标点相应的所述直线距离在预设距离区间内，则统计在所述预设距离区间内所述直线距离相应的其它出险坐标点的数量；
    分别将在所述预设距离区间内的数量乘以所述预设距离区间相应的热力权值，得到每个所述出险坐标点在所述预设距离区间相对应的附加热力值；及
    将所述附加热力值加上基础热力值，得到每个所述出险坐标点的热力值。
  3. 根据权利要求1所述的方法，其特征在于，所述将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像，包括：
    将每个所述出险坐标点及相应的热力值导入地图中；
    确定每个所述出险坐标点在所述地图中的位置；
    将每个所述出险坐标点标记相应的热力值；
    在所述地图上，按照与所述出险坐标点的直线距离给所述地图上其它坐 标点标记热力值；所述其它坐标点与所述出险坐标点的直线距离越大，相应的热力值越小；及
    根据所述地图上标记的热力值生成热力图像。
  4. 根据权利要求1所述的方法，其特征在于，所述确定待命时间段和待查勘区域信息之后，还包括：
    确定历史日期时间段；
    所述查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配，还包括：
    查询历史案件信息，所述历史案件信息包括的所述出险时间点同时与所述待命时间段和所述历史日期时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配。
  5. 根据权利要求1所述的方法，其特征在于，所述根据所述热力图像确定出险待命位置，包括：
    查询所述地图中所述待查勘区域信息指定的区域内所包括的道路；
    统计所述地图上的坐标点沿所述道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；及
    选取所述直线距离总和最短的坐标点作为出险待命位置。
  6. 一种出险待命位置确定装置，其特征在于，所述装置包括：
    待命确定模块，用于确定待命时间段和待查勘区域信息；
    案件查询模块，用于查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；
    坐标点获取模块，用于获取所述历史案件信息包括的出险坐标点；
    距离确定模块，用于在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；
    热力值获取模块，用于根据所述直线距离获得每个所述出险坐标点的热 力值；
    热力图像生成模块，用于将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及
    位置确定模块，用于根据所述热力图像确定出险待命位置。
  7. 根据权利要求6所述的装置，其特征在于，所述热力值获取模块包括：
    距离获取模块，用于获取每个所述出险坐标点相应的所述直线距离；
    数量统计模块，用于若所述出险坐标点相应的所述直线距离在预设距离区间内，则统计在所述预设距离区间内所述直线距离相应的其它出险坐标点的数量；
    附加热力值计算模块，用于分别将在所述预设距离区间内的数量乘以所述预设距离区间相应的热力权值，得到每个所述出险坐标点在所述预设距离区间相对应的附加热力值；及
    热力值总和计算模块，用于将所述附加热力值加上基础热力值，得到每个所述出险坐标点的热力值。
  8. 根据权利要求7所述的装置，其特征在于，所述热力图像生成模块包括：
    导入模块，用于将每个所述出险坐标点及相应的热力值导入地图中；
    出险位置确定模块，用于确定每个所述出险坐标点在所述地图中的位置；
    热力值标记模块，用于将每个所述出险坐标点标记相应的热力值；在所述地图上，按照与所述出险坐标点的直线距离给所述地图上其它坐标点标记热力值，所述地图上其它坐标点与所述出险坐标点的直线距离越大，则相应的热力值越小；及
    热力图像成像模块，用于根据所述地图上标记的热力值生成热力图像。
  9. 根据权利要求6所述的装置，其特征在于，所述待命确定模块，还用于确定历史日期时间段；
    所述案件查询模块，还用于查询历史案件信息，所述历史案件信息包括的所述出险时间点同时与所述待命时间段和所述历史日期时间段匹配、且所 述历史案件信息的出险区域信息与所述待查勘区域信息匹配。
  10. 根据权利要求6所述的装置，其特征在于，所述位置确定模块包括：
    道路查询模块，用于查询所述地图中所述待查勘区域信息指定的区域内所包括的道路；
    道路距离统计模块，用于统计所述地图上的坐标点沿所述道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；及
    位置选取模块，用于选取所述直线距离总和最短的坐标点作为出险待命位置。
  11. 一个或多个存储有计算机可读指令的非易失性可读存储介质，所述计算机可读指令被一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    确定待命时间段和待查勘区域信息；
    查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；
    获取所述历史案件信息包括的出险坐标点；
    在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；
    根据所述直线距离获得每个所述出险坐标点的热力值；
    将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及
    根据所述热力图像确定出险待命位置。
  12. 根据权利要求11所述的存储介质，其特征在于，所述一个或多个处理器执行所述根据所述直线距离获得每个所述出险坐标点的热力值的步骤，包括：
    获取每个所述出险坐标点相应的所述直线距离；
    若所述出险坐标点相应的所述直线距离在预设距离区间内，则统计在所述预设距离区间内所述直线距离相应的其它出险坐标点的数量；
    分别将在所述预设距离区间内的数量乘以所述预设距离区间相应的热力权值，得到每个所述出险坐标点在所述预设距离区间相对应的附加热力值；及
    将所述附加热力值加上基础热力值，得到每个所述出险坐标点的热力值。
  13. 根据权利要求11所述的存储介质，其特征在于，所述一个或多个处理器执行所述将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像的步骤，包括：
    将每个所述出险坐标点及相应的热力值导入地图中；
    确定每个所述出险坐标点在所述地图中的位置；
    将每个所述出险坐标点标记相应的热力值；
    在所述地图上，按照与所述出险坐标点的直线距离给所述地图上其它坐标点标记热力值；所述其它坐标点与所述出险坐标点的直线距离越大，相应的热力值越小；及
    根据所述地图上标记的热力值生成热力图像。
  14. 根据权利要求11所述的存储介质，其特征在于，所述一个或多个处理器在执行所述确定待命时间段和待查勘区域信息的步骤之后，所述一个或多个处理器还执行以下步骤：
    确定历史日期时间段；
    所述一个或多个处理器在执行所述查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配的步骤时，所述一个或多个处理器还执行以下的步骤：
    查询历史案件信息，所述历史案件信息包括的所述出险时间点同时与所述待命时间段和所述历史日期时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配。
  15. 根据权利要求11所述的存储介质，其特征在于，所述一个或多个处理器执行所述根据所述热力图像确定出险待命位置的步骤，包括：
    查询所述地图中所述待查勘区域信息指定的区域内所包括的道路；
    统计所述地图上的坐标点沿所述道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；及
    选取所述直线距离总和最短的坐标点作为出险待命位置。
  16. 一种计算机设备，包括存储器和一个或多个处理器，所述存储器中存储有计算机可读指令，所述计算机可读指令被所述一个或多个处理器执行时，使得所述一个或多个处理器执行以下步骤：
    确定待命时间段和待查勘区域信息；
    查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配；
    获取所述历史案件信息包括的出险坐标点；
    在获取到的出险坐标点中，确定每个出险坐标点与其它出险坐标点间的直线距离；
    根据所述直线距离获得每个所述出险坐标点的热力值；
    将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像；及
    根据所述热力图像确定出险待命位置。
  17. 根据权利要求16所述的计算机设备，其特征在于，所述一个或多个处理器执行所述根据所述直线距离获得每个所述出险坐标点的热力值的步骤，包括：
    获取每个所述出险坐标点相应的所述直线距离；
    若所述出险坐标点相应的所述直线距离在预设距离区间内，则统计在所述预设距离区间内所述直线距离相应的其它出险坐标点的数量；
    分别将在所述预设距离区间内的数量乘以所述预设距离区间相应的热力权值，得到每个所述出险坐标点在所述预设距离区间相对应的附加热力值；及
    将所述附加热力值加上基础热力值，得到每个所述出险坐标点的热力值。
  18. 根据权利要求16所述的计算机设备，其特征在于，所述一个或多个处理器执行所述将每个所述出险坐标点及相应的热力值导入地图中，在所述地图上生成热力图像的步骤，包括：
    将每个所述出险坐标点及相应的热力值导入地图中；
    确定每个所述出险坐标点在所述地图中的位置；
    将每个所述出险坐标点标记相应的热力值；
    在所述地图上，按照与所述出险坐标点的直线距离给所述地图上其它坐标点标记热力值；所述其它坐标点与所述出险坐标点的直线距离越大，相应的热力值越小；及
    根据所述地图上标记的热力值生成热力图像。
  19. 根据权利要求16所述的计算机设备，其特征在于，所述一个或多个处理器在执行所述确定待命时间段和待查勘区域信息的步骤之后，所述一个或多个处理器还执行以下步骤：
    确定历史日期时间段；
    所述一个或多个处理器在执行所述查询历史案件信息，所述历史案件信息的出险时间点与所述待命时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配的步骤时，所述一个或多个处理器还执行以下的步骤：
    查询历史案件信息，所述历史案件信息包括的所述出险时间点同时与所述待命时间段和所述历史日期时间段匹配、且所述历史案件信息的出险区域信息与所述待查勘区域信息匹配。
  20. 根据权利要求16所述的计算机设备，其特征在于，所述一个或多个处理器执行所述根据所述热力图像确定出险待命位置的步骤，包括：
    查询所述地图中所述待查勘区域信息指定的区域内所包括的道路；
    统计所述地图上的坐标点沿所述道路抵达每个出险坐标点相应的热力图像所覆盖区域的直线距离总和；及
    选取所述直线距离总和最短的坐标点作为出险待命位置。
PCT/CN2017/112656 2017-11-01 2017-11-23 出险待命位置确定方法、装置、计算机设备和存储介质 WO2019085082A1 (zh)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201711057399.7 2017-11-01
CN201711057399.7A CN107862030B (zh) 2017-11-01 2017-11-01 出险待命位置确定方法、装置、计算机设备和存储介质

Publications (1)

Publication Number Publication Date
WO2019085082A1 true WO2019085082A1 (zh) 2019-05-09

Family

ID=61696541

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/112656 WO2019085082A1 (zh) 2017-11-01 2017-11-23 出险待命位置确定方法、装置、计算机设备和存储介质

Country Status (2)

Country Link
CN (1) CN107862030B (zh)
WO (1) WO2019085082A1 (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114359842A (zh) * 2022-03-17 2022-04-15 季华实验室 协作机器人事故检测系统、方法、存储介质和电子设备

Families Citing this family (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108959389B (zh) * 2018-06-01 2023-03-14 平安科技（深圳）有限公司 服务器、查勘网格的优化方法及存储介质
CN109492062A (zh) * 2018-10-16 2019-03-19 平安国际融资租赁有限公司 客户地图显示方法、装置、计算机设备和存储介质
CN110188818B (zh) * 2019-05-28 2021-05-04 南京中孚信息技术有限公司 热点区域聚类方法、装置及电子设备
CN113380422B (zh) * 2021-05-24 2024-06-18 首都医科大学 一种疫情规模预测方法、装置、电子设备及存储介质

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8219535B1 (en) * 2006-02-15 2012-07-10 Allstate Insurance Company Retail deployment model
CN106570917A (zh) * 2016-10-25 2017-04-19 先锋智道（北京）科技有限公司 车辆需求热力图生成方法和装置
CN106682876A (zh) * 2016-12-29 2017-05-17 广东精规划信息科技股份有限公司 一种用于公安指挥的可视化指挥平台
CN106708955A (zh) * 2016-11-29 2017-05-24 浙江宇视科技有限公司 一种热力图生成方法及设备

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103020284A (zh) * 2012-12-28 2013-04-03 刘建勋 一种基于时空聚类的出租车载客点推荐方法
US8799799B1 (en) * 2013-05-07 2014-08-05 Palantir Technologies Inc. Interactive geospatial map
CN105045858B (zh) * 2015-07-10 2018-04-13 湖南科技大学 基于投票的出租车载客点推荐方法
CN105206057B (zh) * 2015-09-30 2018-09-07 哈尔滨工业大学深圳研究生院 基于浮动车居民出行热点区域的检测方法及系统
EP3166063A1 (en) * 2015-11-06 2017-05-10 Mastercard International Incorporated Heatmap visualisation of event data
CN105893998A (zh) * 2016-03-30 2016-08-24 北京奇虎科技有限公司 一种指定区域内的实点的密度估计方法和装置
CN106940718B (zh) * 2017-03-14 2020-11-20 山东师范大学 一种获取候鸟迁徙路径描述的方法、装置及服务器

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8219535B1 (en) * 2006-02-15 2012-07-10 Allstate Insurance Company Retail deployment model
CN106570917A (zh) * 2016-10-25 2017-04-19 先锋智道（北京）科技有限公司 车辆需求热力图生成方法和装置
CN106708955A (zh) * 2016-11-29 2017-05-24 浙江宇视科技有限公司 一种热力图生成方法及设备
CN106682876A (zh) * 2016-12-29 2017-05-17 广东精规划信息科技股份有限公司 一种用于公安指挥的可视化指挥平台

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114359842A (zh) * 2022-03-17 2022-04-15 季华实验室 协作机器人事故检测系统、方法、存储介质和电子设备

Also Published As

Publication number Publication date
CN107862030A (zh) 2018-03-30
CN107862030B (zh) 2020-07-31

Similar Documents

Publication Publication Date Title
WO2019085082A1 (zh) 出险待命位置确定方法、装置、计算机设备和存储介质
US11294552B2 (en) Systems and methods for geospatial value subject analysis and management
US10769611B2 (en) Location based system and method for calculating sales and use tax
US8799074B2 (en) Methods and apparatus for performing enhanced queries for items such as maps and geospatial data
US20130262152A1 (en) Systems and methods for certified location data collection, management, and utilization
US9589259B2 (en) Location based system and method for calculating sales and use tax
WO2020107712A1 (zh) 基于用户数据实现天线方位角纠偏的方法
CN101350012A (zh) 一种地址匹配的方法和系统
US20130069948A1 (en) System and method for processing and displaying data relating to consumption data
WO2018188509A1 (zh) 楼盘信息处理方法、装置、计算机设备及存储介质
CN104102637A (zh) 一种生成热点区域的方法及装置
Gil de la Vega et al. Models for positional accuracy assessment of linear features: 2D and 3D cases
KR102184048B1 (ko) Gis 기반 토지 이용 계획 검토 시스템 및 방법
CN113656477A (zh) 一种国土空间多源异构数据的校验与融合方法
Balogun et al. Assessing the suitability of GlobeLand30 for land cover mapping and sustainable development in Malaysia using error matrix and unbiased area Estimation
Mozas-Calvache et al. Accuracy of contour lines using 3D bands
Demetriou Uncertainty of OpenStreetMap data for the road network in Cyprus
JP2016206825A (ja) 画像登録装置およびその方法
Favretto Georeferencing historical cartography: a quality-control method
Guillet et al. Camera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs
TWM554206U (zh) 房價地理資訊評估系統
Chandrasekar et al. Computer application on evaluating beach sediment erosion and accretion from profile survey data
Zhou et al. Validation analysis of OpenStreetMap data in some areas of China
CN112035590A (zh) 电子噪音地图显示方法、装置、计算机设备和存储介质
TWI579528B (zh) 導航方法、導航系統以及記錄媒體

Legal Events

Date Code Title Description
NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC, EPO FORM 1205A DATED 13/10/20

122 Ep: pct application non-entry in european phase

Ref document number: 17930984

Country of ref document: EP

Kind code of ref document: A1