Method and system for alerting users of incident-prone locations

1 . A computer-implemented method for alerting a user of incident-prone locations, comprising:

receiving, by one or more processors from a user device, location data of the user device and a destination input by the user;

determining, by the one or more processors, based upon the location data, that the user device is approaching the destination;

loading, by the one or more processors, an incident density map surrounding the destination, wherein the incident density map is generated by a chatbot, the chatbot being trained with a plurality of training incident density maps and historical or hypothetical incident data associated with the plurality of training incident density maps;

determining, by the one or more processors, based upon the incident density map, at least one non-incident-prone parking spot, wherein the at least one non-incident-prone parking spot meets at least one predetermined criterion; and

presenting, by the one or more processors via the user device, an indication of the at least one non-incident-prone parking spot.

2 . The computer-implemented method of claim 1 , further comprising:

receiving, by the one or more processors from the user device, an indication of whether the user accepts the at least one non-incident-prone parking spot;

responsive to receiving an indication that the user accepts the at least one non-incident-prone parking spot, determining, by the one or more processors, a first insurance-related action; and

responsive to receiving an indication that the user rejects the at least one non-incident-prone parking spot, determining, by the one or more processors, a second insurance-related action.

3 . The computer-implemented method of claim 2 , wherein:

the first insurance-related action is at least one of maintaining a current insurance policy for the user, decreasing an insurance premium for the user, and/or decreasing an insurance coverage for the user; and

the second insurance-related action is at least one of maintaining a current insurance policy for the user, increasing an insurance premium for the user, and/or increasing an insurance coverage for the user.

4 . The computer-implemented method of claim 1 , wherein at least a portion of the historical incident data is at least one of an insurance claim document, an image, an audio, and/or a video associated with one or more incidents.

5 . The computer-implemented method of claim 1 , wherein the at least one predetermined criterion includes at least one of a distance between a location of the at least one non-incident-prone parking spot and the destination, a frequency of incidents associated with the at least one non-incident-prone parking spot, a type of incidents associated with the at least one non-incident-prone parking spot, a danger level of incidents associated with the at least one non-incident-prone parking spot, a recency of a latest incident associated with the at least one non-incident-prone parking spot, a similarity between a current time and a time of an incident associated with the at least one non-incident-prone parking spot, and/or a similarity between a current economic index and an economic index associated with a time of an incident associated with the at least one non-incident-prone parking spot.

6 . A system for alerting a user of incident-prone locations, comprising:

one or more processors, and

a non-transitory memory storing one or more instructions, the one or more instructions, when executed by the one or more processors, cause the one or more processors to:

receive, from a user device, location data of the user device and a destination input by the user;

determine, based upon the location data, that the user device is approaching the destination;

load an incident density map surrounding the destination, wherein the incident density map is generated by a chatbot, the chatbot being trained with a plurality of training incident density maps and historical or hypothetical incident data associated with the plurality of training incident density maps;

determine, based upon the incident density map, at least one non-incident-prone parking spot, wherein the at least one non-incident-prone parking spot meets at least one predetermined criterion; and

present, via the user device, an indication of the at least one non-incident-prone parking spot.

7 . A computer-implemented method for alerting a user of incident-prone locations, comprising:

receiving, by one or more processors from a user device, location data of the user device;

determining, by the one or more processors, based upon the location data, that the user has parked a vehicle in a particular location;

loading, by the one or more processors, an incident density map surrounding the particular location, wherein the incident density map is generated by a chatbot, the chatbot being trained with a plurality of training incident density maps and historical or hypothetical incident data associated with the plurality of training incident density maps;

determining, by the one or more processors, based upon the incident density map, that the particular location is an incident-prone location, wherein the incident-prone location meets at least one predetermined first criterion;

determining, by the one or more processors, based upon the incident density map, at least one non-incident-prone parking spot, wherein the at least one non-incident-prone parking spot meets at least one predetermined second criterion; and

presenting, by the one or more processors via the user device, an indication of at least one non-incident-prone parking spot.

8 . The computer-implemented method of claim 7 , wherein:

the at least one predetermined first criterion includes at least one of a frequency of incidents associated with the particular location, a type of incidents associated with the particular location, a danger level of incidents associated with the particular location, a recency of a latest incident associated with the particular location, a similarity between a current time and a time of an incident associated with the particular location, and/or a similarity between a current economic index and an economic index associated with a time of an incident associated with the particular location; and

the least one predetermined second criterion includes at least one of a distance between the at least one non-incident-prone parking spot and the particular location, a frequency of incidents associated with the at least one non-incident-prone parking spot, a type of incidents associated with the at least one non-incident-prone parking spot, a danger level of incidents associated with the at least one non-incident-prone parking spot, a recency of a latest incident associated with the at least one non-incident-prone parking spot, a similarity between a current time and a time of an incident associated with the at least one non-incident-prone parking spot, and/or a similarity between a current economic index and an economic index associated with a time of an incident associated with the at least one non-incident-prone parking spot.

9 . The computer-implemented method of claim 7 , further comprising:

receiving, by the one or more processors from the user device, an indication of whether the user has moved the vehicle to the at least one non-incident-prone parking spot;

responsive to receiving an indication that the user moved the vehicle to the at least one non-incident-prone parking spot, determining, by the one or more processors, a first insurance-related action; and

responsive to receiving an indication that the user has parked the vehicle in the particular location for a predetermined time period, determining, by the one or more processors, a second insurance-related action.

10 . The computer-implemented method of claim 7 , wherein at least a portion of the historical incident data is at least one of an insurance claim document, an image, an audio, and/or a video associated with one or more incidents.

11 . A computer-implemented method for alerting a user of incident-prone locations, comprising:

receiving, by one or more processors from a user device, location data of the user device and a destination input by the user;

determining, by the one or more processors, based upon the location data, that the user device is approaching the destination;

loading, by the one or more processors, an incident density map surrounding the destination, wherein the incident density map is generated by:

receiving a prompt for generating an incident density map;

transmitting the prompt to a chatbot to generate a script for generating the incident density map, wherein the script is compliant for use by a density map generator; and

transmitting, to the density map generator, the script and historical incident data to cause the density map generator to generate the incident density map;

determining, by the one or more processors, based upon the incident density map, at least one non-incident-prone parking spot, wherein the at least one non-incident-prone parking spot meets at least one predetermined criterion; and

presenting, by the one or more processors via the user device, an indication of the at least one non-incident-prone parking spot.

12 . The computer-implemented method of claim 11 , wherein transmitting, to the density map generator, the script and the historical incident data to generate the incident density map includes:

transmitting, to the density map generator, the script and the historical incident data to cause the density map generator to generate the incident density map that shows at least one of frequencies of crimes incidents distributed on the incident density map, types of crimes incidents distributed on the incident density map, and/or danger levels of incidents distributed on the incident density map.

13 . The computer-implemented method of claim 11 , wherein the chatbot is trained with a plurality of prompts for generating incident density maps, and a plurality of scripts for generating the incident density maps compliant for use by the density map generator.

14 . A computer-implemented method for alerting a user of incident-prone locations, comprising:

receiving, by one or more processors from a user device, location data of the user device and a destination input by the user;

determining, by the one or more processors, based upon the location data, that the user device is approaching the destination;

loading, by the one or more processors, an incident density map surrounding the destination;

determining, by the one or more processors, based upon the incident density map, at least one non-incident-prone parking spot, wherein the at least one non-incident-prone parking spot meets at least one predetermined first criterion;

presenting, by the one or more processors via the user device, an indication of the at least one non-incident-prone parking spot;

receiving, by the one or more processors, real-time incident data associated with a real-time incident;

determining, by the one or more processors, whether the real-time incident data meets at least one predetermined second criterion; and

responsive to determining that real-time incident meets the at least one predetermined second criterion, presenting, by the one or more processors via the user device, an indication of the real-time incident.

15 . The computer-implemented method of claim 14 , wherein the at least one predetermined second criterion includes at least one of a distance between a location of the user device and a location of the real-time incident, a type of the real-time incident, an impact scope of the real-time incident, an impact level of the real-time incident, a reporting time of the real-time incident, an expected impact duration of the real-time incident, and/or an expected impact end time of the real-time incident.

16 . A system for alerting a user of incident-prone locations, comprising:

one or more processors, and

a non-transitory memory storing one or more instructions, the one or more instructions, when executed by the one or more processors, cause the one or more processors to:

receive, from a user device, location data of the user device and a destination input by the user;

determine, based upon the location data, that the user device is approaching the destination;

load an incident density map surrounding the destination, wherein the incident density map is generated by:

receiving a prompt for generating an incident density map;

transmitting the prompt to a chatbot to generate a script for generating the incident density map, wherein the script is compliant for use by a density map generator; and

transmitting, to the density map generator, the script and historical incident data to cause the density map generator to generate the incident density map;

determine, based upon the incident density map, at least one non-incident-prone parking spot, wherein the at least one non-incident-prone parking spot meets at least one predetermined criterion; and

present, via the user device, an indication of the at least one non-incident-prone parking spot.