JP7218827B2 - Information processing device, hazard map generation method and program - Google Patents

Description

The present invention relates to an information processing device, a hazard map generation method, and a program.

There is a hazard map that displays the expected damage situation on a map when disasters such as earthquakes, tsunamis caused by earthquakes, heavy rains, and volcanic eruptions occur. Hazard maps publish various information about disasters in an easy-to-understand format so that residents can reduce the damage caused by disasters. It is used for the purpose of minimizing the damage.

Hazard maps are generally created based on damage information from past disasters. Therefore, when a disaster actually occurs, the damage situation may not always be the same as the degree of disaster risk displayed on the hazard map, so the hazard map is not always fully utilized. Therefore, when a disaster occurs, a related technique for creating a hazard map that displays the damage situation in real time is being studied (for example, Patent Literature 1).

In Patent Document 1, when flood damage such as flooding occurs, real-time flood analysis and calculation of river water level prediction are performed in real time using current river information, and the calculated information is dynamically displayed. A dynamic flood simulation system is disclosed.

Incidentally, in recent years, SNSs (Social Networking Services) such as Twitter (registered trademark) and Facebook (registered trademark) have been widely used all over the world. SNS is a service that allows users to easily post events that occur in their immediate surroundings, and a huge amount of information can be collected by collecting SNS information. Therefore, it is expected that various services will be provided using SNS information. For example, as in Patent Literature 2, real-time distribution of disaster-related information using SNS information when a disaster occurs is under study.

In Patent Document 2, SNS information is collected, the collected SNS information is analyzed, and real-time information such as the age group of the sender of the SNS information, gender, evacuation status of surrounding people, disaster status, type of disaster, etc. Outputting item information is disclosed.

JP-A-2004-197554 JP 2014-164381 A

As described above, SNS is a service that allows users to easily post events that occur in their immediate surroundings, and various services can be provided using SNS information. Therefore, the inventor considered creating a hazard map that is utilized by many users by using SNS information.

Here, Patent Literature 1 does not disclose creating a hazard map using SNS information. Further, Patent Document 2 is a technique for acquiring and analyzing SNS information when a disaster occurs and distributing disaster-related information. However, in order to apply it to a hazard map, it is necessary to analyze the acquired SNS information and output digitized disaster information. Patent Literature 2 does not disclose outputting digitized disaster information using SNS information. Therefore, even if the technology disclosed in Patent Document 2 is used, it is impossible to create a hazard map using SNS information.

An object of the present disclosure is to solve such problems, and to provide an information processing device, a hazard map generation method, and a program that can create a hazard map using SNS information.

The information processing apparatus according to the first aspect, when a disaster occurs, includes location information, pre-registered information indicating danger, and safety among posted information related to the disaster posted by a plurality of users. an acquisition unit that acquires posted information including any of a plurality of keywords including information indicating and the posted information that is included in each of the acquired posted information based on the keywords included in the acquired posted information; and classifying each of the obtained posted information into one of a plurality of predetermined areas based on location information included in the obtained posted information. a determination unit that determines the impact level of the entire area for each area based on the impact level set for the posted information classified in the area; and the impact level of the entire area for each area. a determination unit for determining whether the area is dangerous; and for the area determined by the determination unit to be dangerous, a hazard map is generated by superimposing the influence level of the entire area on map information. and a generator.

In the hazard map generation method according to the second aspect, when a disaster occurs, out of the posted information related to the disaster posted by a plurality of users, location information, pre-registered information indicating danger and safety and any one of a plurality of keywords including information indicating and, based on the keywords included in the acquired posted information, the posted information indicated by the posted information for each of the acquired posted information is acquired. setting an impact level of a disaster, and classifying each of the obtained posted information into one of a plurality of predetermined areas based on location information included in the obtained posted information; , based on the impact level set for the posted information classified in the area, determines the impact level of the entire area, and for each area, based on the impact level of the entire area, determines whether the area is dangerous. A hazard map generating method in an information processing apparatus, for determining whether or not a dangerous area is present, and for an area determined to be dangerous, superimposing the influence level of the entire area on map information to generate a hazard map.

A program according to a third aspect, when a disaster occurs, includes location information, pre-registered information indicating danger and information indicating safety among posted information related to the disaster posted by a plurality of users. a step of obtaining posted information including one of a plurality of keywords including and, based on the keyword included in the obtained posted information, the disaster indicated by the posted information in each of the obtained posted information and classifying each of the acquired posted information into one of a plurality of predetermined areas based on the location information included in the acquired posted information; and determining the impact level of the entire area based on the impact level set for the posted information classified in the area; and generating a hazard map by superimposing the impact level of the entire area on the map information for the area determined to be dangerous. is.

According to the above aspect, it is possible to create a hazard map using SNS information.

1 is a block diagram showing a configuration example of an information processing apparatus according to an outline of an embodiment; FIG. 1 is a schematic configuration diagram showing a configuration example of an information processing system according to a first embodiment; FIG. It is a figure which shows an example of a disaster information table. It is a figure which shows an example of a place information table. It is a figure which shows an example of a keyword table. 4 is a diagram for explaining the concept of determination processing performed by a determination unit according to Embodiment 1; FIG. 4 is a diagram for explaining the concept of determination processing performed by a determination unit according to Embodiment 1; FIG. 4 is a diagram for explaining the concept of determination processing performed by a determination unit according to Embodiment 1; FIG. It is a figure which shows an example of the produced|generated hazard map. 4 is a flowchart for explaining an operation example of the information processing apparatus according to the first embodiment; FIG. 10 is a diagram showing the concept of processing performed by a processing unit according to the second embodiment; FIG. 10 is a diagram illustrating a hazard map generated by a generator according to the second embodiment; FIG. 9 is a flowchart for explaining an operation example of the information processing apparatus according to the second embodiment; 9 is a flowchart for explaining an operation example of the information processing apparatus according to the second embodiment; FIG. 11 is a schematic configuration diagram showing a configuration example of an information processing system according to a third embodiment; It is a figure which shows an example of a time information table. 10 is a flowchart for explaining an operation example of the information processing apparatus according to the third embodiment; FIG. 11 is a schematic configuration diagram showing a configuration example of an information processing apparatus according to another embodiment;

Hereinafter, embodiments will be described with reference to the drawings. In addition, in the embodiments, the same elements are denoted by the same reference numerals, and overlapping descriptions are omitted.
(Overview of Embodiment)
First, prior to the description of the embodiments, an outline of the embodiments will be described. An information processing apparatus 10 according to the outline of the embodiment will be described with reference to FIG. FIG. 1 is a block diagram of a configuration example of an information processing apparatus according to an outline of an embodiment.

The information processing apparatus 10 may be, for example, an information processing apparatus such as an SNS server, a server that provides a hazard map, or an SNS server that provides a hazard map. Alternatively, the information processing device 10 may be a mobile phone terminal, a smartphone terminal, a tablet terminal, a personal computer device, or the like. The information processing device 10 includes an acquisition unit 11 , a processing unit 12 , a determination unit 13 , a determination unit 14 and a generation unit 15 .

When a disaster occurs, the acquiring unit 11 retrieves a plurality of pieces of posted information related to the disaster posted by a plurality of users, including location information and pre-registered information indicating danger and information indicating safety. Retrieve post information containing any of the keywords and Posted information may be posted information (SNS information) posted by a user on SNS such as Twitter and Facebook.

The location information may be a specific place name, a building name, or information indicating a municipality name.
The multiple keywords are information including information indicating danger and information indicating safety. The keyword is information registered in advance, and is information regarding whether the posted content is danger information or safety information. A keyword can be said to be information that serves as a reference for determining whether posted content is dangerous information or safety information. A keyword can also be said to be information from which it is possible to guess whether a place or position indicated by location information included in posted information is dangerous or safe due to a disaster. Keywords include, for example, "dangerous", "dangerous", "dangerous", "stay away", "evacuation", "safe", "okay", "no problem", "nothing happening", "safe", etc. information.

The acquisition unit 11 may directly acquire disaster-related posted information including location information and keywords from a plurality of users, or from an SNS server where posted information posted by a plurality of users is collected. may be obtained.

The processing unit 12 sets the disaster impact level indicated by the posted information to each of the acquired posted information based on the keyword included in the acquired posted information. In addition, the processing unit 12 classifies each piece of acquired posted information into one of a plurality of predetermined areas based on the location information included in the acquired posted information.

The processing unit 12 sets the impact level of the disaster to each piece of the acquired posted information based on the correspondence relationship between the pre-registered keyword and the impact level. The impact level may be, for example, three stages of high, medium, and low, or may be ten stages.

The processing unit 12 classifies each acquired piece of posted information into one of a plurality of predetermined areas based on the previously registered correspondence relationship between the location information and the area information.

The predetermined area may be, for example, an area in units of "city" such as Yokohama City or Kawasaki City, or may be an area in units of "wards, towns and villages." Alternatively, the predetermined area may be an area divided by predetermined distances based on the disaster site. Alternatively, the predetermined area may be an area divided by a predetermined distance based on the location where the largest number of pieces of posted information are posted among the pieces of posted information acquired by the acquisition unit 11 .

For each area, the determination unit 13 determines the influence level of the entire target area based on the influence level set for the posted information classified into the area. The influence level of the entire area may be the average or median of the influence levels set for the classified posted information. Alternatively, the impact level of the entire area may be determined by further classifying the classified posted information into two according to a predetermined criterion and using the classified impact levels of the posted information.

For each area, the determination unit 14 determines whether or not the area is dangerous based on the influence level of the entire area. The determination unit 14 may determine that the target area is dangerous when the influence level of the entire area is equal to or higher than a predetermined threshold.

The generation unit 15 generates a hazard map by superimposing the influence level of the entire area on the map information for the area determined to be dangerous by the determination unit 14 . The generation unit 15 may generate the hazard map by setting the influence level of the entire area determined by the determination unit 14 to be dangerous in map information stored in advance. Alternatively, the generation unit 15 may acquire a hazard map from a server that provides the hazard map, and superimpose the influence level of the entire area on the acquired hazard map to generate the hazard map.

As described above, the information processing apparatus 10 according to the outline of the embodiment acquires post information related to disasters, and sets the disaster impact level for each of the acquired post information. Information processing apparatus 10 determines the influence level of the entire area based on the influence level set for each piece of posted information. This makes it possible to create data for reflecting the acquired posted information on the hazard map.

Further, the information processing device 10 determines whether or not the area is dangerous based on the impact level of the entire area, and creates a hazard map in which the impact level of the entire dangerous area is superimposed on the map information. do. Since the hazard map sets the predicted damage situation at the time of disaster only for dangerous areas, by doing the above, disaster information can be displayed only for dangerous areas in the same way as the current general hazard map. can be provided. Therefore, according to the outline of the embodiment, it is possible to create a hazard map using SNS information.

(Embodiment 1)
Embodiments of the present disclosure will be described below with reference to the drawings. Embodiment 1 is an embodiment in which the outline of the embodiment is detailed.

An information processing system 100 according to the first embodiment will be described with reference to FIG. FIG. 2 is a schematic configuration diagram showing a configuration example of the information processing system according to the first embodiment; The information processing system 100 includes a disaster information providing server 20 , an SNS server 21 , a hazard map providing server 22 , an information processing device 40 and a communication terminal 50 .

The disaster information providing server 20 is, for example, a server installed in a government office such as the Meteorological Agency or a municipality, and is a server that provides disaster information when a disaster occurs. The disaster information providing server 20 connects to the information processing device 40 via the Internet 30 . The disaster information providing server 20 may be connected to the SNS server 21 and the hazard map providing server 22 via the Internet 30 .

When a disaster occurs, the disaster information providing server 20 delivers disaster information including the type of disaster, the location of the disaster, the date and time of the disaster, the scale of the disaster, and the like. The disaster information providing server 20 may distribute other information in addition to the above information, or may distribute only a part of the above information.

The SNS server 21 is, for example, a server that collects SNS information such as Twitter and Facebook, and collects posted information from a plurality of users who have subscribed to the SNS. The SNS server 21 connects to the information processing device 40 via the Internet 30 . Posted information may be text data, image data, video data, audio data, or may be a combination of the above information such as text data and image data, text data and video data.

The SNS server 21 provides the collected posted information to other users who have subscribed to the SNS. In other words, users who have subscribed to the SNS can view posted information posted by other users. In the following description, the SNS server 21 is assumed to be a server that provides SNS information by Twitter. In addition, since posted information is sometimes referred to as a so-called "tweet" or "tweet" on Twitter, posted information may be referred to as a "tweet" or a "tweet" in the following description. .

The hazard map providing server 22 is, for example, a server installed in a municipality, which provides a general current hazard map created based on past disaster information. The hazard map providing server 22 connects to the information processing device 40 via the Internet 30 .

The communication terminal 50 is a communication device capable of receiving the hazard map generated by the information processing device 40 and displaying the received hazard map. The communication terminal 50 may be, for example, a communication device such as a mobile phone terminal, a smartphone terminal, a tablet terminal, or a personal computer device. In addition, although only one communication terminal 50 is shown in FIG. 2, a plurality of communication terminals may be provided.

The information processing device 40 is a device corresponding to the information processing device 10 in the overview of the embodiments. The information processing device 40 includes an acquisition unit 41 , a storage unit 42 , a processing unit 43 , a determination unit 44 , a determination unit 45 , a generation unit 46 , a distribution unit 47 and a display unit 48 .

The acquisition unit 41 corresponds to the acquisition unit 11 in the overview of the embodiments. Acquisition unit 41 connects to disaster information providing server 20 , SNS server 21 , and hazard map providing server 22 via Internet 30 . The acquisition unit 41 can also be called a communication unit because it connects and communicates with other devices. The acquiring unit 41 acquires disaster information from the disaster information providing server 20 when a disaster occurs. Furthermore, the acquisition unit 41 acquires a general current hazard map from the hazard map providing server 22 .

Further, when a disaster occurs, the acquiring unit 41 acquires posted information related to the disaster that has occurred, from among posted information posted to the SNS server 21, and includes location information and a keyword. do. In other words, the acquisition unit 41 collects only tweets about the disaster that is currently occurring from among tweets posted by users who have subscribed to the SNS via the Internet. The acquiring unit 41 determines and acquires the posted information to be acquired by performing natural language processing such as morphological analysis on the text data included in the posted information.

The acquisition unit 41 refers to a disaster information table T1 in which disaster-related information is set, a location information table T2 in which location information is set, and a keyword table T3 in which keywords are set, Identify and acquire post information.

An example of the disaster information table T1 will now be described with reference to FIG. FIG. 3 is a diagram showing an example of a disaster information table. The disaster information table T1 is a table that associates and registers disasters that have occurred and related disaster information that indicates disasters that can occur simultaneously after the disaster that has occurred. A disaster type and related disaster information are set in the disaster information table T1.

The type of disaster is set in the disaster type. In the example shown in FIG. 3, "earthquake", "volcanic eruption", "heavy rain", and "fire" are set as disaster types.
The related disaster information contains information about related disasters that can occur simultaneously after the disaster indicated by the disaster type set in the same row. In the example shown in FIG. 3, for example, when the disaster type is "earthquake", "tsunami", "fire", and "fire" can occur simultaneously after the earthquake. , "Fire", and "Fire" are set. Of course, the disaster types and related disaster information shown in FIG. 3 are only examples, and other disaster types and related disaster information may be set.

Next, an example of the location information table T2 will be described with reference to FIG. FIG. 4 is a diagram showing an example of a location information table. In the location information table T2, location information with which a position can be specified and area information indicating which area the location information belongs to are registered in association with each other.

As the location information, for example, information capable of specifying a location such as an address, landmark information, place name, etc. is registered. In the example shown in FIG. 4, "Station A", "Station B", "Station C", and "Tower D" are set as the location information. Note that, of course, other information may be registered in the location information.

The area information is set with area information indicating to which area the location information set in the same row belongs. In the example shown in FIG. 4, the area information is described as area information for each town, indicating that "A station" belongs to the "a town" area. It should be noted that, of course, the area information may be set to a wider area than the town unit, such as a city unit, instead of the town unit area, or may be set to a narrower area than the town unit. . Alternatively, an area arbitrarily determined by the administrator of the information processing device 40 may be set in the area information instead of the town or city unit.

Next, an example of the keyword table T3 will be described with reference to FIG. FIG. 5 is a diagram showing an example of a keyword table. The keyword table T3 is a table that associates and registers keywords related to whether the posted content is danger information or safety information and the impact level estimated by the disaster that has occurred. Keywords and influence levels are set in the keyword table T3.

The keyword is pre-registered information, and a plurality of pieces of information including information indicating danger and information indicating safety are set. Information about whether the posted content is dangerous information or safety information is set in the keyword. It can be said that the keyword is set with information that serves as a reference for determining whether the posted content is dangerous information or safety information. In addition, it can be said that the keyword is set with information that enables estimation of whether the place or position indicated by the location information included in the posted information is dangerous or safe due to a disaster. In the example shown in FIG. 5, the keywords include, for example, "safe", "no problem", "okay", "safe", "no worries", "damage", "shake", "get closer", "danger". , “dangerous”, “evacuation”, “dangerous”, “emergency”, etc. are set.

In the impact level, an impact level associated with a keyword and indicating the degree of danger estimated by a disaster is set. In this embodiment, the impact level is represented by 10 levels, and the larger the number, the higher the level of impact caused by the disaster. The example shown in FIG. 5 indicates that the impact level "1" is set for "safety" and the impact level "2" is set for "unconcerned". Note that, of course, the keywords and influence levels shown in FIG. 5 are only examples, so other keywords may be registered, and the influence levels associated with the keywords may be different.

Here, an example of posted information acquired by the acquisition unit 41 will be described with reference to FIGS. 3 to 5. FIG. For example, it is assumed that posted information includes posted information such as "The building at A station collapsed due to the recent earthquake and is in danger" and "I am in Tower D now, but I am safe even if the earthquake occurred 10 minutes ago." Since the information "earthquake" is included in the related disaster information of the disaster information table T1, the obtaining unit 41 determines that the posted information about the disaster is included. Further, since the information "A Station" and "D Tower" are included in the location information of the location information table T2, the acquiring unit 41 determines that the posted information includes location information. Furthermore, since the information "dangerous" and "safety" are included in the keywords of the keyword table T3, the obtaining unit 41 determines that the posted information includes the keywords. Therefore, the acquisition unit 41 acquires the above-mentioned posted information such as "The building at A station will collapse due to the earthquake just now and it is dangerous" and "I am in Tower D now, but I am safe even if the earthquake happened 10 minutes ago". is determined and acquired.

Note that when the posted information includes current location information of the poster called a GEO tag, the acquiring unit 41 determines that the posted information includes location information, and uses the location information indicated by the GEO tag as the location. It may be used as information.
Further, it is assumed that the same user posts a plurality of items of posted information. In this case, the acquiring unit 41 may acquire one of the plurality of pieces of posted information of the same user. This is because, if all the pieces of posted information from the same user are used, the content indicated by the posted information may be biased. In addition, after a disaster occurs, the acquiring unit 41 may periodically acquire posted information including location information and keywords from disaster-related posted information posted by a plurality of users. .

Next, returning to FIG. 2, the storage unit 42 will be described. The storage unit 42 stores a disaster information table T1, a location information table T2 and a keyword table T3. The storage unit 42 also stores the hazard map that the acquisition unit 41 has acquired from the hazard map providing server 22 . Then, the storage unit 42 classifies the posted information acquired by the processing unit 43 from various viewpoints, and stores the listed data (posted information).

Next, the processing section 43 will be described. The processing unit 43 corresponds to the processing unit 12 in the overview of the embodiments. The processing unit 43 sets the disaster impact level indicated by the posted information to each piece of posted information acquired by the acquiring unit 41 based on the keyword included in the posted information acquired by the acquiring unit 41 . Specifically, the processing unit 43 searches the keyword table T3 for a keyword that matches the keyword included in each of the acquired posted information, and converts the influence level associated with the searched keyword to the acquired posted information. set as the impact level of the disaster for each of

For example, if the posted information is "dangerous because the building at A station collapsed due to the recent earthquake", referring to the keyword table T3, the impact level corresponding to "dangerous" is "7". set an impact level of 7. Also, if the posted information is "I'm in D Tower now, but it's safe even if the earthquake happened 10 minutes ago", referring to the keyword table T3, the impact level corresponding to "safety" is "1". , set impact level 1 to the posted information. In addition, it is assumed that the posted information includes a plurality of keywords. Or you can set the lowest impact level. Alternatively, the processing unit 43 may set a median value or an average value of influence levels corresponding to each of a plurality of keywords.

In addition, the processing unit 43 classifies each piece of acquired posted information into one of a plurality of predetermined areas based on the location information included in the acquired posted information. Specifically, the processing unit 43 searches the location information table T2 for location information that matches the location information included in each piece of acquired posted information, and identifies area information associated with the retrieved location information. do. The processing unit 43 classifies each piece of acquired posted information into the specified area. In the following explanation, it is assumed that the predetermined area is an area in units of "town".

For example, if the posted information is "Dangerous because the building at A station collapsed due to the recent earthquake", the area information corresponding to "A station" is the "a town" area in the location information table T2. Therefore, the processing unit 43 classifies the posted information into the "a town" area. For example, it is conceivable that the location information included in the acquired posted information is location information indicating an area larger than the classified area (in units of "town"), such as "K city". In this case, the processing unit 43 may replace "K City", which is the location information included in the posted information, with "K Station", which is a representative station of "K City". Alternatively, the processing unit 43 may replace "K city", which is the location information included in the posted information, with "K city hall" where the city hall of "K city" exists or the address where the K city hall exists.

The processing unit 43 classifies the posted information acquired by the acquiring unit 41 according to the type of the posted information, such as posted information including an image, posted information including a video, and posted information including a text, and lists the posted information. become In addition, the processing unit 43 classifies and lists posted information such as posted information by date, posted information by time, posted information by area, and posted information by influence level. The processing unit 43 causes the storage unit 42 to store the post information classified as described above. In this way, if the posted information is classified in advance from various viewpoints, the processing time for processing the posted information can be shortened.

Next, the determination unit 44 will be described. The determination unit 44 corresponds to the determination unit 13 according to the outline of the embodiment. The determination unit 44 determines the influence level of the entire area for each area based on the influence level set for the posted information classified into the area.

Specifically, for each area, the determination unit 44 selects posted information with an impact level of 1 to 5 and posts with an impact level of 6 to 10 among the impact levels set for the posted information classified in the area. classified into information and That is, the determination unit 44 sets the classification threshold to 5, and classifies the posted information into the posted information with the influence levels of 1 to 5 and the posted information with the influence levels of 6 to 10. Posted information with impact levels 1 to 5 can also be said to be posted information indicating that the degree of impact of a disaster is low and that it is safe. Posted information with impact levels 6 to 10 can also be said to be posted information indicating that the disaster has a high degree of impact and is dangerous. Therefore, the determination unit 44 classifies the posted information into safe posted information and dangerous posted information. In the following description, posted information with an impact level of 1 to 5 may be referred to as a "safe tweet", and posted information with an impact level of 6 to 10 may be referred to as a "dangerous tweet". Further, although the classification threshold is set to 5 in the following description, it may be a value that can be changed by the administrator of the information processing device 40 as appropriate.

Next, the determining unit 44 calculates the average impact level of safe tweets and the average impact level of dangerous tweets for each area. The determination unit 44 determines the difference between the average impact level of safe tweets and the average impact level of dangerous tweets as the impact level of the disaster for the entire area. In the following description, the difference between the average impact level of safe tweets and the average impact level of dangerous tweets may be referred to as a "difference impact level".

Here, the concept of determination processing for determining the influence level of the entire area performed by the determination unit 44 will be described with reference to FIGS. 6 to 8. FIG. 6 to 8 are diagrams for explaining the concept of determination processing performed by the determination unit according to Embodiment 1. FIG.

FIG. 6 is a diagram showing a state before the determination unit 44 performs determination processing, and shows a state after the processing unit 43 sets the influence level to each piece of posted information and classifies it into a plurality of areas. Also, FIG. 6 shows posted information in a certain area among a plurality of classified areas. Assume that there are 50 tweets of posted information (tweets) classified into a certain area. The circles shown in FIG. 6 are individual tweets, representing a portion of the 50 tweets. In addition, the “shadow X (X: an integer of 1 or more)” written in each circle represents the level of impact caused by the disaster set for each tweet. indicates a high degree of danger.

FIG. 7 shows a state after the determination unit 44 classifies tweets into safe tweets and dangerous tweets in the state of FIG. As shown in FIG. 7, out of 50 tweets classified into a certain area, 10 tweets are safe tweets and 40 tweets are dangerous tweets.

FIG. 8 shows a state in which the determination unit 44 has calculated the average impact level of safe tweets, the average impact level of dangerous tweets, and the difference impact level between them. As shown in FIG. 8, if the average impact level of safe tweets is 2.8 and the average impact level of dangerous tweets is 6.8, the differential impact level is 4. The determination unit 44 determines the differential impact level "4" as the impact level for the entire area.

In addition, users who have subscribed to SNS can post information based on their subjectivity. It is also assumed that there is a possibility that Therefore, the determination unit 44 may determine the influence level of the entire area when the number of pieces of posted information acquired per unit time is, for example, 50 or more for each classified area. By doing so, the determining unit 44 can determine the influence level of the entire area based on more objective information.

Further, the determination unit 44 may determine that a disaster requiring urgency has occurred when the number of pieces of posted information in a certain area is equal to or greater than a predetermined value (eg, 50 pieces) per unit time (eg, 1 minute). . In this case, the determining unit 44 may set the impact level of the entire area for this area and instruct the generating unit 46 to immediately generate the hazard map. Also, in this case, for example, the generator 46 may be instructed to generate a hazard map every five minutes.

On the other hand, the determination unit 44 may determine that urgency is not required when the number of pieces of posted information in a certain area is less than a predetermined value (eg, 50 pieces) per unit time (eg, 1 minute). In this case, the determination unit 44 may set the influence level of the entire area when tweets equal to or greater than a predetermined value are collected.

Next, the determination unit 45 will be described. The determination unit 45 corresponds to the determination unit 14 according to the outline of the embodiment. For each area, the determination unit 45 determines whether or not the area is dangerous based on the influence level of the entire area. Specifically, when the influence level of the entire area is equal to or higher than the determination threshold, the determination unit 45 determines whether or not the area is dangerous. For example, as shown in FIG. 8, it is assumed that the determination unit 44 has determined the influence level of the entire area to be 4. When the determination threshold is set to 4, the determination unit 45 determines that the area is dangerous.

Next, the generator 46 will be described. The generation unit 46 corresponds to the generation unit 15 according to the outline of the embodiment. The generation unit 46 generates a hazard map by superimposing the influence level of the entire area on the map information for the area determined to be dangerous by the determination unit 45 . Specifically, the generation unit 46 superimposes the influence level of the entire area on the area determined to be dangerous by the determination unit 45 on the hazard map acquired by the acquisition unit 41 from the hazard map providing server 22 to create a hazard map. Generate.

Here, an example of the hazard map generated by the generator 46 will be described with reference to FIG. 9 . FIG. 9 is a diagram showing an example of a generated hazard map. As shown in FIG. 9, it is assumed that the predetermined areas are a town area including A station, b town area including B station, and c town area including C station and D tower. Further, the determination unit 44 sets the influence level of the entire area of the town a to 5, the influence level of the entire area of the town b to 6, and the impact level of the entire area of the town c to 4. Assume that the area is determined to be dangerous. In this case, as shown in FIG. 9, the generation unit 46 draws hazards with the same visual representation for the same impact level so that the user who uses the hazard map can easily grasp it visually. Generate a map. Note that the generation unit 46 may generate a hazard map by displaying the difference impact degree numerically in the map information. may be displayed in color. Alternatively, the generating unit 46 may generate the hazard map by setting the map information on the X-axis-Y-axis plane and making the magnitude of the difference impact level correspond to the value in the Z-axis direction.

It should be noted that, for example, if the acquisition unit 41 no longer acquires disaster information from the disaster information providing server 20, or if it no longer acquires post information related to disasters, the disaster in this area has calmed down and no urgency is required. can be judged. In this case, the generation unit 46 may delete the information about the influence level of the entire area superimposed on the map information. In other words, the generation unit 46 may use a general current hazard map generated by adding information from a fixed-point camera or a local government as a hazard map to be generated.

Returning to FIG. 2, the distribution unit 47 will be described. The distribution unit 47 distributes the hazard map generated by the generation unit 46 to the communication terminal 50 . The distribution unit 47 can also be called a communication unit because it communicates with the communication terminal 50 .
The display unit 48 is a display capable of displaying the hazard map generated by the generation unit 46 .

Next, an operation example performed by the information processing apparatus 40 will be described with reference to FIG. 10 . 10 is a flowchart for explaining an operation example of the information processing apparatus according to the first embodiment; FIG. FIG. 10 is implemented periodically when a disaster occurs and after a disaster occurs.

First, post information about a disaster including location information and keywords is acquired (step S1). Specifically, the acquiring unit 41 extracts posted information including the information registered in the related disaster information of the disaster information table T1 from among the plurality of pieces of posted information. Further, the acquisition unit 41 acquires post information including the location information registered in the location information of the location information table T2 and the keyword registered in the keyword of the keyword table T3.

Next, an impact level indicating the degree of impact of the disaster that has occurred is set for each of the acquired posted information (step S2). Specifically, the processing unit 43 refers to the keyword table T3, acquires from the keyword table T3 the influence level corresponding to the keyword included in each of the acquired posted information, and determines the level of influence on each acquired posted information. Set level.

Next, each piece of the acquired posted information is classified into one of a plurality of predetermined areas (step S3). Specifically, the processing unit 43 refers to the location information table T2, acquires area information corresponding to the location information included in each of the acquired posted information, and converts each acquired posted information into the area information. Categorize into designated areas.

Next, the posted information is classified by data type and stored by classified data type (step S4). Specifically, the processing unit 43 acquires the posted information according to the type of the posted information, such as posted information including an image, posted information including a video, or posted information including a text, for the posted information acquired by the acquisition unit 41 . are classified and listed. In addition, the processing unit 43 classifies and lists posted information such as posted information by date, posted information by time, posted information by area, and posted information by influence level. The processing unit 43 causes the storage unit 42 to store the post information classified as described above.

Next, steps S5 to S7 are executed for each area classified in step S3. As step S5, based on the impact level set for the classified posted information, the disaster impact level for the entire area is set (step S5). Specifically, the determination unit 44 compares the impact level set for the classified posted information with the classification threshold, and classifies the posted information into the posted information below the classification threshold and the posted information above the classification threshold. . The determination unit 44 calculates the differential impact level between the average impact level of the posted information below the classification threshold and the average impact level of the posted information above the classification threshold, and determines the impact level of the entire area. .

Next, based on the comparison between the influence level of the entire area and the determination threshold value, it is determined whether or not the area is dangerous (step S6). Specifically, the determination unit 45 determines that this area is a dangerous area when the influence level of the entire area is equal to or higher than the determination threshold, and determines that this area is not a dangerous area when it is less than the determination threshold. I judge.

In step S6, if it is determined that the area is dangerous (YES in step S6), the impact level of the entire area is set in the general current hazard map provided by the hazard map providing server 22 (step S7). ). Specifically, if the impact level of the entire area is equal to or higher than the determination threshold (YES in step S6), the generation unit 46 displays the impact level of the entire area on the general current hazard map acquired from the hazard map providing server 22. A level is superimposed (step S7).

On the other hand, in step S6, if the influence level of the entire area is less than the determination threshold value, that is, if it is determined that the area is not dangerous (NO in step S6), steps S5 to S7 are performed for the next area. to run.

After executing steps S5 to S7 for all areas, the generator 46 generates a hazard map (step S8).

The generated hazard map is distributed and displayed (step S9). The distribution unit 47 distributes the generated hazard map to the communication terminal 50 . Also, the display unit 48 displays the generated hazard map.

As described above, according to the information processing apparatus 40 according to the first embodiment, post information related to disasters is acquired, and the disaster impact level is set for each of the acquired post information. Information processing device 40 determines the influence level of the entire area based on the influence level set for each piece of posted information. The information processing device 40 determines whether or not the area is dangerous based on the impact level of the entire area, and creates a hazard map in which the impact level of the entire dangerous area is superimposed on the map information. Therefore, according to Embodiment 1, it is possible to create a hazard map using SNS information.

Furthermore, in this embodiment, a general current hazard map is acquired from the hazard map providing server 22, and a new hazard map is created by superimposing the impact level of the entire area determined from SNS information on the general current hazard map. can be generated. Therefore, it becomes possible to add a further amount of information to the general current hazard map. Therefore, the hazard map generated by the information processing apparatus 40 according to the present embodiment makes it possible to provide a hazard map that is more useful than before.

(Embodiment 2)
Next, Embodiment 2 will be described. The second embodiment is an improved example of the first embodiment. An object of the present embodiment is to specify, as a landmark, a position having the largest number of pieces of posted information in the area in the first embodiment.

An information processing system according to the second embodiment is the same as that of the first embodiment, so description thereof is omitted. Further, since the configuration example of the information processing apparatus 40 according to the second embodiment is also basically the same as that of the first embodiment, only the differences from the first embodiment will be described with reference to FIG. An information processing device 40 according to the second embodiment will be described. The information processing apparatus 40 according to the second embodiment differs in the configuration of the processing unit 43 , the determination unit 44 and the determination unit 45 .

In addition to the configuration of the processing unit 43 according to the first embodiment, the processing unit 43 identifies the position indicated by the location information having the largest number of posted information in the area from the classified posted information for each area. Places with the largest number of posted information are generally considered to be large cities within the area. Therefore, in the present embodiment, processing unit 43 identifies the location with the largest number of posted information, and identifies the position indicated by the identified location as a landmark within the classified area in the first embodiment. For convenience of explanation, the area classified by the processing unit 43 according to the first embodiment will be explained as the first area.

Specifically, after classifying each piece of posted information acquired by acquisition unit 41 into a plurality of first areas, processing unit 43 counts the number of location information included in the posted information for each first area. By counting, the position indicated by the location information with the largest number of posted information is identified. For each first area, the processing unit 43 calculates the distance between the position indicated by the location information included in the acquired posted information and the location indicated by the location information with the largest number of posted information. Then, the processing unit 43 divides each of the acquired posted information into a plurality of second divisions by a predetermined distance from the position indicated by the location information having the largest number of posted information based on the calculated distance. Categorize into areas. In this embodiment, the predetermined distance is assumed to be 2 km. It should be noted that, of course, the predetermined distance may be, for example, 50 m, or may be another value.

Here, the concept of processing performed by the processing unit 43 will be described with reference to FIG. 11 . FIG. 11 is a diagram illustrating a concept of processing performed by a processing unit according to the embodiment; The processing unit 43 classifies the posted information into the town a area and the town b area (first area) in FIG. 11 using the location information of the acquired posted information.

Next, the processing unit 43 identifies the position indicated by the location information with the largest number of pieces of posted information from the pieces of posted information classified into the town a area and the town b area. In FIG. 11, among the pieces of information posted in town a, the number of pieces of information posted with station A as the location information is the largest, and among the pieces of information posted in town b, the number of pieces of information posted with station B as the location information is the largest. do. Then, the processing unit 43 identifies the A station and the B station. Then, the processing unit 43 calculates the distance between the position indicated by the location information included in each piece of the acquired posted information and the A station and the B station.

Next, based on the calculated distance, the processing unit 43 classifies each piece of the acquired posted information into one of a plurality of areas (second areas) divided by predetermined distances. Dotted lines shown in FIG. 11 are lines representing area boundaries every 2 km with A station as a reference. A dashed-dotted line is a line representing an area boundary every 2 km with B station as a reference. For example, if the position indicated by the location information included in posted information T is the position shown in FIG. 11 and the distance from station A is 3 km, processing unit 43 classifies posted information T into areas of 2 km to 4 km. do.

Returning to FIG. 2, the determination unit 44 will be described. In Embodiment 1, the determining unit 44 calculates the influence level of the entire first area for each first area. In the present embodiment, the determination unit 44 determines the influence level of the entire second area for each second area. Since the determination unit 44 determines the influence level of the entire area for each second area in the same manner as in the first embodiment, the description is omitted.

Next, the determination unit 45 will be described. In Embodiment 1, the determination unit 45 determines whether each first area is a dangerous area based on the influence level of the entire area of the first area. In the present embodiment, the determination unit 45 determines whether each second area is a dangerous area based on the influence level of the entire second area. The determination unit 45 determines whether or not it is a dangerous area as in the first embodiment, so the description is omitted.

Next, FIG. 12 shows an example of the hazard map generated by the generator 46. FIG. FIG. 12 is a diagram for explaining a hazard map generated by the generating unit according to the embodiment; Note that the configuration of the generator 46 according to the present embodiment is the same as that of the generator 46 according to the first embodiment. However, since the generated hazard maps are different, the hazard map generated by the generation unit 46 will be described.

As shown in FIG. 12 , the generation unit 46 selects “A station”, which has the largest number of posted information in the a town area (first area), as a reference, and selects the A hazard map is generated by setting the influence level of the entire area for the area determined to be a dangerous area. Similarly, the generating unit 46 determines a dangerous area among a plurality of areas (second areas) at intervals of 2 km based on "B station" which has the largest number of posted information in the town b area (first area). Generate a hazard map that sets the impact level for the entire area for the designated area. Then, the generation unit 46 generates a hazard map by combining both hazard maps as a final hazard map.

As shown in FIG. 12, the area hatched with horizontal lines indicates an impact level of seven, and the area hatched with vertical lines indicates an impact level of six. The dotted area indicates an impact level of 5. The area indicated by dotted diagonal lines indicates an area with an impact level of four. A non-hatched area indicates an area determined by the determination unit 45 not to be a dangerous area.

Assume that the influence level is 7 in the area from 0 km to 2 km with A station as the reference. Assume that the influence level is 6 in an area of 2 km to 4 km from station A as a reference. Assume that the influence level is 5 in the area of 4 km to 6 km with A station as the reference. Assume that the determining unit 45 determines that the distance after 6 km from station A is not dangerous. Then, as shown in FIG. 12, the influence level of the entire area determined by the determination unit 44 is set for each 2-km area determined by the determination unit 45 to be dangerous.

Similarly, it is assumed that the influence level is 4 in the area from 0 km to 2 km with B station as a reference. Assume that the influence level is 5 in an area of 2 km to 4 km from station b. Assume that the determination unit 45 determines that the distance after 4 km from station b is not dangerous. Then, as shown in FIG. 12, the influence level of the entire area determined by the determination unit 44 is set for each 2-km area determined by the determination unit 45 to be dangerous.

In the example shown in FIG. 12, the influence level in the 0-2 km area with A station as the reference is higher than the influence level in the 0-2 km area with B station as the reference. Therefore, the user can judge that it is safer to evacuate to B station than to evacuate to A station.

In FIG. 12, among the areas of 2 km to 4 km based on Station A, there is an area that overlaps with the area of 2 km to 4 km based on Station B, and the overlapping areas are hatched. generated to overlap. However, for this area, the average value of the impact level of the area of 2 km to 4 km with respect to Station A and the impact level of the area of 2 km to 4 km from Station B is calculated as the influence of the overlapping area. You may make it a level.

Next, an operation example of the information processing apparatus 40 according to the present embodiment will be described with reference to FIGS. 13A and 13B. 13A and 13B are flowcharts for explaining an operation example of the information processing apparatus according to the second embodiment. 13A and 13B basically correspond to FIG. Therefore, processing that performs the same operations as those in the first embodiment will be given the same reference numerals, and description will be omitted as appropriate. Figures 13A and 13B are performed periodically when and after a disaster occurs.

First, steps S1 to S4 shown in FIG. 13A are the same as in the first embodiment. In addition, since the area of Embodiment 1 is set to the 1st area, the area classified in step S3 is described as the 1st area. The operation following step S4 is shown in FIG. 13B.

In FIG. 13B, steps S11 to S16 are performed for each first area. Although the details will be described later, steps S14 to S16 are further processed for each second area.

In step S11, location information with the largest number of posted information is specified for each first area, and the position indicated by the location information is specified (step S11). Specifically, the processing unit 43 classifies the acquired posted information for each first area, counts the location information of the posted information for each first area, and identifies location information with the largest number of posted information. do. The processing unit 43 identifies the position indicated by the location information. By performing this process, it becomes possible to determine the landmark in the first area.

Next, using the location information included in each piece of posted information acquired in step S1 and the position specified in step S11, the distance from the position specified in step S11 is calculated (step S12). Specifically, the processing unit 43 identifies the position from the location information included in each piece of posted information acquired in step S1, and calculates the distance from the position identified in step S11.

Next, based on the calculated distance, each piece of the acquired posted information is classified into one of a plurality of second areas every 2 km (step S13). Specifically, the processing unit 43 uses the distance calculated in step S12 for each of the acquired posted information to move the corresponding area out of a plurality of areas every 2 km based on the position identified in step S11. Classify.

Next, steps S14 to S16 are performed for each second area. Steps S14 to S16 are processes performed for each second area, but since they are the same as the processes in steps S5 to S7 in the first embodiment, detailed description thereof will be omitted. The generator 46 generates a hazard map for all second areas (step S8). The distribution unit 47 distributes the generated hazard map to the communication terminal 50, and the display unit 48 displays the generated hazard map (step S9).

As described above, in the present embodiment, basically similar to the first embodiment, acquired posted information is classified into predetermined areas, and a hazard map is generated in which the influence level is set for each area. do. Therefore, according to the information processing apparatus 40 according to the present embodiment, it is possible to obtain the same effect as in the first embodiment.

In addition, in the present embodiment, processing unit 43 identifies, as a landmark, the position indicated by the location information with the largest amount of posted information in the area (first area) in the first embodiment. Then, the processing unit 43 calculates the distance from the specified position from the location information set in each piece of the acquired posted information, and classifies the posted information into areas (second areas) according to the distance. Here, in the first area, it is estimated that many people are present in the position indicated by the location information with the largest amount of posted information. The user can check the hazard map generated in the present embodiment and easily determine which of the plurality of landmarks to evacuate to. Therefore, the user can easily determine a safer landmark, so that the user can evacuate with peace of mind. Therefore, according to the present embodiment, it is possible to generate a hazard map that is easier for users to use than in the first embodiment.

(Embodiment 3)
Next, Embodiment 3 will be described. The third embodiment is an improved example of the first and second embodiments. Therefore, the description of the present embodiment will be made using the first embodiment, and the contents different from the first embodiment will be described. Acquisition unit 41 acquires posted information including location information and keywords in the first embodiment, but acquires posted information further including time information in the present embodiment.

First, a configuration example of the information processing system 100 and the information processing device 40 according to the third embodiment will be described with reference to FIG. 14 . FIG. 14 is a schematic configuration diagram showing a configuration example of an information processing system according to a third embodiment; The information processing system 100 according to the third embodiment differs from the information processing system 100 according to the first embodiment only in the configuration of the information processing device 40 . Therefore, the description of the configuration example of the information processing system 100 according to the third embodiment is omitted.

Next, a configuration example of the information processing apparatus 40 according to this embodiment will be described. Since the configuration example of the information processing apparatus 40 according to the present embodiment is basically the same as that of the first embodiment, only differences from the first embodiment will be described. In the information processing apparatus 40 according to the third embodiment, the storage section 42 in the first embodiment is replaced with a storage section 49 . In addition, the information processing apparatus 40 according to the third embodiment has different configurations of the acquisition unit 41, the processing unit 43, and the generation unit 46. FIG.

Acquisition unit 41 acquires posted information including location information, keywords, and time information from posted information related to disasters. That is, as compared with the first embodiment, acquisition unit 41 acquires posted information that further includes time information. Specifically, the acquiring unit 41 refers to the time information table T4 to acquire posted information that further includes the time information registered in the time information table T4.

Here, the time information table T4 will be explained using FIG. The time information table T4 is a table that associates and registers time information and estimated time/time information.

As shown in FIG. 15, the time information is, for example, "now", "now", "just now", "a little while ago", "today", "yesterday", "x o'clock". This is information that can be used to estimate the date and time indicated by the posted information from the posted date and time.

The estimated time/time information is information associated with the time information, and is information for estimating when the posted information indicates from the time information. In the example shown in FIG. 15, if the time information is "now now", it can be estimated that the posted information indicates information from 10 minutes ago. 10 minutes before" is set. If the time information is "a little while ago", it can be assumed that the posted information is one hour ago. It is If the time information is "today", "12:00 (0:00 PM) of the posting date" is registered in the estimated time/time information. If the time information is "yesterday", the estimated time/time information is set to "12:00 (0:00 PM) the day before the posting date". If the time information is "hh o'clock", the estimated time/time information is set to "hh o'clock of the posting date". Note that, of course, the time information and the estimated time/time information shown in FIG. 15 are examples, and the present invention is not limited to this. For example, the estimated time/time information may be set in units of seconds, such as "hh hours mm minutes ss seconds of the posting date".

Returning to FIG. 14, the processing unit 43 will be described. The processing unit 43 estimates the date and time indicated by the posted information using the time information included in the acquired posted information and the posted date and time of the acquired posted information. In addition, the processing unit 43 extracts, from the acquired posted information, posted information whose estimated date and time are within a predetermined time period from the current time.

Specifically, the processing unit 43 searches the time information table T4 for time information that matches the time information included in the acquired posted information, and identifies estimated time/time information associated with the retrieved time information. . The processing unit 43 estimates the date and time indicated by the posted information using the specified estimated time/time information and the posted date and time. Then, the processing unit 43 extracts posted information whose estimated date and time is within a predetermined time period, such as within three hours, from the current time. It should be noted that, of course, the predetermined time is not limited to three hours, and is a value that can be changed as appropriate.

Next, the generator 46 will be described. The generation unit 46 generates a hazard map, for example, for each time (for example, three hours) used when the processing unit 43 extracts specific posted information. That is, the generator 46 always generates a hazard map using the latest information.

Next, the storage unit 49 will be explained. The storage unit 49 stores a time information table T4 in addition to the configuration of the storage unit 42 in the first embodiment.

Next, an operation example of the information processing apparatus 40 according to this embodiment will be described with reference to FIG. 16 is a flowchart for explaining an operation example of the information processing apparatus according to the third embodiment; FIG. FIG. 16 basically corresponds to FIG. Therefore, processing that performs the same operations as those in the first embodiment will be given the same reference numerals, and description will be omitted as appropriate. FIG. 16 is performed periodically when and after a disaster occurs.

First, post information about a disaster including location information, keywords, and time information is acquired (step S21). Specifically, the acquisition unit 41 refers to the disaster information table T1, the location information table T2, the keyword table T3, and the time information table T4 to acquire post information related to the disaster including location information, keywords, and time information.

Next, the date and time indicated by the posted information are estimated, and posted information within a predetermined time period from the present is extracted (step S22). Specifically, the processing unit 43 refers to the time information table T4, and uses the time information included in the posted information and the posted date and time of the posted information to estimate the date and time indicated by the posted information. Then, the processing unit 43 extracts posted information within a predetermined time (for example, within three hours) from the present.

Next, steps S2 to S7 are executed. Steps S2 to S7 are the same as the operation example described with reference to FIG. 10, so description thereof is omitted.

After executing steps up to step S7, the generation unit 46 generates a hazard map every predetermined time (for example, every three hours) (step S23). The distribution unit 47 distributes the generated hazard map to the communication terminal 50, and the display unit 48 displays the generated hazard map (step S9).

As described above, the present embodiment is basically the same as the first embodiment, so that it is possible to obtain the same effect as the first embodiment. Further, in the present embodiment, acquiring unit 41 acquires posted information that further includes time information, and processing unit 43 estimates the date and time indicated by the posted information, and extracts posted information within a predetermined time period. Then, the generator 46 generates a hazard map every predetermined time. Therefore, according to the present embodiment, it is possible to generate a real-time hazard map in which the latest information is updated every predetermined time. Therefore, according to the present embodiment, users can evacuate appropriately using a hazard map that reflects newer information, so damage caused by a disaster can be minimized. becomes.

In the above description, the first embodiment was used, but the second embodiment can also be applied. Therefore, according to this embodiment, it is possible to obtain the same effects as those of the second embodiment.

(Modification)
In the third embodiment, the processing unit 43 estimates the date and time indicated by the acquired posted information, and extracts the posted information whose estimated date and time are within a predetermined time period from the current time, among the acquired posted information. However, without being limited to this, the processing unit 43 may further classify the acquired posted information into posted information for each predetermined time based on the estimated date and time, for example. In this case, the determination unit 44 determines the impact level of the entire area at predetermined time intervals, and the determination unit 45 determines whether or not each of the classified areas is a dangerous area at predetermined time intervals. , the generation unit 46 generates a hazard map every predetermined time. By doing so, the user can browse the hazard map for each predetermined time. In other words, the user can check the situation of the area to be evacuated in chronological order.

(Other embodiments)
FIG. 17 is a block diagram showing a configuration example of the information processing apparatuses 10 and 40 (hereinafter referred to as information processing apparatuses 10 and the like) described in the above embodiment. Referring to FIG. 17, the information processing apparatus 10 and the like include a network interface 1201, a processor 1202, and a memory 1203. FIG. The network interface 1201 is used to communicate with other network node devices that make up the communication system. Network interface 1201 may include, for example, a network interface card (NIC) conforming to the IEEE 802.3 series.

The processor 1202 reads and executes software (computer program) from the memory 1203 to perform the processing of the information processing apparatus 10 and the like described using the flowcharts in the above embodiments. The processor 1202 may be, for example, a microprocessor, an MPU (Micro Processing Unit), or a CPU (Central Processing Unit). Processor 1202 may include multiple processors.

The memory 1203 is composed of a combination of volatile memory and non-volatile memory. Memory 1203 may include storage remotely located from processor 1202 . In this case, processor 1202 may access memory 1203 via an I/O interface, not shown.

In the example of FIG. 17, memory 1203 is used to store software modules. The processor 1202 reads and executes these software modules from the memory 1203, thereby performing the processing of the information processing apparatus 10 and the like described in the above embodiments.

As described with reference to FIG. 17, each of the processors included in the information processing apparatus 10 and the like executes one or more programs including instruction groups for causing the computer to execute the algorithm described with reference to the drawings.

In the above examples, the programs can be stored and delivered to computers using various types of non-transitory computer readable media. Non-transitory computer-readable media include various types of tangible storage media. Examples of non-transitory computer-readable media include magnetic recording media (eg, floppy disks, magnetic tapes, hard disk drives), magneto-optical recording media (eg, magneto-optical disks). Further examples of non-transitory computer readable media include CD-ROMs (Read Only Memory), CD-Rs, and CD-R/Ws. Further examples of non-transitory computer-readable media include semiconductor memory. The semiconductor memory includes, for example, mask ROM, PROM (Programmable ROM), EPROM (Erasable PROM), flash ROM, and RAM (Random Access Memory). The program may also be delivered to the computer on various types of transitory computer readable medium. Examples of transitory computer-readable media include electrical signals, optical signals, and electromagnetic waves. Transitory computer-readable media can deliver the program to the computer via wired channels, such as wires and optical fibers, or wireless channels.

It should be noted that the present disclosure is not limited to the above embodiments, and can be modified as appropriate without departing from the scope of the present disclosure. In addition, the present disclosure may be implemented by appropriately combining each embodiment.

In addition, part or all of the above-described embodiments can be described as the following additional remarks, but are not limited to the following.
(Appendix 1)
When a disaster occurs, one of a plurality of keywords including location information, information indicating danger and information indicating safety registered in advance, among posted information related to the disaster posted by a plurality of users, and an acquisition unit that acquires post information including
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. a processing unit that classifies each piece of the acquired posted information into one of a plurality of predetermined areas based on the
a determination unit that determines an impact level of the entire area for each area based on the impact level set for the posted information classified into the area;
a determination unit that determines, for each area, whether or not the area is dangerous based on the impact level of the entire area;
and a generation unit that generates a hazard map by superimposing the influence level of the entire area on map information for the area determined to be dangerous by the determination unit.
(Appendix 2)
For each of the areas, the determination unit divides each of the posted information classified into the area into first posted information whose influence level is less than a first threshold and second posted information whose influence level is equal to or higher than the first threshold. The information processing apparatus according to appendix 1, wherein the information is classified into the posted information and the impact level of the entire area based on the impact level of the first posted information and the impact level of the second posted information. .
(Appendix 3)
Supplementary Note 2: The determining unit determines a differential impact level between an average impact level of the first posted information and an average impact level of the second posted information as the impact level of the entire area. The information processing device according to .
(Appendix 4)
4. The information processing apparatus according to any one of appendices 1 to 3, wherein the determination unit determines that the area is dangerous when the influence level of the entire area is equal to or higher than a second threshold.
(Appendix 5)
the area is a first area,
The processing unit identifies location information having the largest number of posted information for each first area, and the first location indicated by the identified location information and the location information included in the acquired posted information are calculating a distance between the second position shown and the calculated distance, and dividing each piece of the acquired posted information by a predetermined distance based on the first position based on the calculated distance; classified into one of a plurality of second areas;
The determination unit determines an impact level of the entire area for each second area,
5. The information processing apparatus according to any one of appendices 1 to 4, wherein the determination unit determines whether or not the second area is dangerous for each of the second areas.
(Appendix 6)
The acquisition unit acquires posted information further including time information,
The processing unit estimates the date and time indicated by the posted information using the time information included in the acquired posted information and the posted date and time of the acquired posted information, and, of the acquired posted information, extracting posted information whose estimated date and time is within a predetermined time from the present;
6. The information processing apparatus according to any one of appendices 1 to 5, wherein the generating unit generates the hazard map every predetermined time.
(Appendix 7)
7. The information processing apparatus according to any one of appendices 1 to 6, further comprising a distribution unit that distributes the generated hazard map information to communication terminals.
(Appendix 8)
further comprising a management table for managing the keywords and the impact levels in association with each other;
8. The information processing apparatus according to any one of appendices 1 to 7, wherein the processing unit sets the influence level to each piece of the acquired posted information using the management table.
(Appendix 9)
9. The information processing apparatus according to any one of appendices 1 to 8, further comprising a display unit that displays the generated hazard map.
(Appendix 10)
When a disaster occurs, one of a plurality of keywords including location information, information indicating danger and information indicating safety registered in advance, among posted information related to the disaster posted by a plurality of users, and , to get the post information, including
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. classifying each of the acquired posted information into one of a plurality of predetermined areas based on
determining the impact level of the entire area for each area based on the impact level set for the posted information classified in the area;
determining, for each area, whether the area is dangerous based on the impact level of the entire area;
A hazard map generating method in an information processing apparatus, for generating a hazard map by superimposing an influence level of the entire area on map information for an area determined to be dangerous.
(Appendix 11)
When a disaster occurs, one of a plurality of keywords including location information, information indicating danger and information indicating safety registered in advance, among posted information related to the disaster posted by a plurality of users, and , obtaining post information including
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. classifying each piece of the acquired posted information into one of a plurality of predetermined areas based on the
determining, for each area, the impact level of the entire area based on the impact level set for the posted information classified into the area;
determining, for each area, whether the area is dangerous based on the impact level of the entire area;
A program for causing a computer to execute a step of superimposing an impact level of the entire area on map information to generate a hazard map for an area determined to be dangerous.
(Appendix 12)
The step of determining the influence level of the entire area includes, for each area, each piece of posted information classified into the area, first posted information whose influence level is less than a first threshold; and second posted information that is equal to or greater than a threshold value of, and determining the impact level of the entire area based on the impact level of the first posted information and the impact level of the second posted information. 12. The program of clause 11, comprising:
(Appendix 13)
an SNS (Social Networking Service) server that collects posted information posted by a plurality of users;
an information processing device;
The information processing device is
When a disaster occurs, among the posted information related to the disaster, post information containing location information and any of a plurality of pre-registered keywords including information indicating danger and information indicating safety an acquisition unit that acquires from the SNS server;
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. a processing unit that classifies each piece of the acquired posted information into one of a plurality of predetermined areas based on the
a determination unit that determines an impact level of the entire area for each area based on the impact level set for the posted information classified into the area;
a determination unit that determines, for each area, whether or not the area is dangerous based on the impact level of the entire area;
and a generating unit that generates a hazard map by superimposing the influence level of the entire area on map information for the area determined to be dangerous by the determining unit.
(Appendix 14)
For each of the areas, the determination unit divides each of the posted information classified into the area into first posted information whose influence level is less than a first threshold and second posted information whose influence level is equal to or higher than the first threshold. 14. The information processing system according to appendix 13, wherein the influence level of the entire area is determined based on the influence level of the first posted information and the influence level of the second posted information. .

10, 40 information processing device 11, 41 acquisition unit 12, 43 processing unit 13, 44 determination unit 14, 45 determination unit 15, 46 generation unit 100 information processing system 20 disaster information providing server 21 SNS server 22 hazard map providing server 30 Internet 42, 49 storage unit 47 distribution unit 48 display unit 50 communication terminal

Claims (10)

Acquisition unit for acquiring posted information about a disaster posted by a plurality of users, the posted information including location information and a pre-registered keyword relating to whether the posted information is danger information or safety information. and,
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. a processing unit that classifies each piece of the acquired posted information into one of a plurality of predetermined areas based on the
a determination unit that determines an impact level of the entire area for each area based on the impact level set for the posted information classified into the area;
and a generating unit that generates a hazard map by superimposing the influence level of the entire area on map information. For each of the areas, the determination unit divides each of the posted information classified into the area into first posted information whose influence level is less than a first threshold and second posted information whose influence level is equal to or higher than the first threshold. 2. The information processing according to claim 1, wherein the information is classified into the posted information and the impact level of the entire area based on the impact level of the first posted information and the impact level of the second posted information. Device. 3. The determination unit determines a differential impact level between an average impact level of the first posted information and an average impact level of the second posted information as the impact level of the entire area. 3. The information processing device according to 2. 4. The information processing apparatus according to any one of claims 1 to 3, further comprising a determination unit that determines that said area is dangerous when the influence level of said entire area is equal to or higher than a second threshold. the area is a first area,
The processing unit identifies location information having the largest number of posted information for each first area, and the first location indicated by the identified location information and the location information included in the acquired posted information are calculating a distance between the second position shown and the calculated distance, and dividing each piece of the acquired posted information by a predetermined distance based on the first position based on the calculated distance; classified into one of a plurality of second areas;
The determination unit determines an impact level of the entire area for each second area,
5. The information processing apparatus according to claim 4, wherein said determination unit determines whether said second area is dangerous for each of said second areas. The acquisition unit acquires posted information further including time information,
The processing unit estimates the date and time indicated by the posted information using the time information included in the acquired posted information and the posted date and time of the acquired posted information, and, of the acquired posted information, extracting posted information whose estimated date and time is within a predetermined time from the present;
The information processing apparatus according to any one of claims 1 to 5, wherein said generator generates said hazard map every said predetermined time. The information processing apparatus according to any one of claims 1 to 6, further comprising a distribution unit that distributes the generated hazard map information to communication terminals. further comprising a management table for managing the keywords and the impact levels in association with each other;
The information processing apparatus according to any one of claims 1 to 7, wherein the processing unit sets the influence level to each piece of the acquired posted information using the management table. Obtaining post information about a disaster posted by a plurality of users, the post information including location information and a pre-registered keyword relating to whether the post information is danger information or safety information;
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. classifying each of the acquired posted information into one of a plurality of predetermined areas based on
determining the impact level of the entire area for each area based on the impact level set for the posted information classified in the area;
A hazard map generation method in an information processing device, wherein the hazard map is generated by superimposing the influence level of the entire area on the map information. a step of obtaining posted information about a disaster posted by a plurality of users, the posted information including location information and a pre-registered keyword relating to whether the information is danger information or safety information;
Based on the keyword included in the acquired posted information, set the impact level of the disaster indicated by the acquired posted information to each of the acquired posted information, and set the location information included in the acquired posted information. classifying each piece of the acquired posted information into one of a plurality of predetermined areas based on the
determining, for each area, the impact level of the entire area based on the impact level set for the posted information classified into the area;
A program for causing a computer to execute a step of superimposing the impact level of the entire area on map information to generate a hazard map.

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