Cognitive-based incident response

• US 10,679,493 B2
• Filed: 09/18/2017
• Issued: 06/09/2020
• Est. Priority Date: 09/18/2017
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Kumhyr, David B., Behnken, John F., Dickens, Louie A., Lopez, Rodolfo
• Primary Examiner(s): Cass, Jean Paul
• Application Number:
  US15/707,712
• Publication Number:
  US 20190088114A1
• Time in Patent Office: 995 Days
• Field of Search: 701117
• CPC Class Codes: G06F 16/95 Retrieval from the web
• CPC Class Codes: G08G 1/0104 Measuring and analyzing of parameters relative to traffic conditions
• CPC Class Codes: G08G 1/0112 from the vehicle, e.g. floating car data [FCD]
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/012 from other sources than vehicle or roadside beacons, e.g. mobile networks
• CPC Class Codes: G08G 1/048 with provision for compensation of environmental or other condition, e.g. snow, vehicle stopped at detector
• CPC Class Codes: G08G 1/205 Indicating the location of the monitored vehicles as destination, e.g. accidents, stolen, rental
• CPC Class Codes: H04W 4/021 Services related to particular areas, e.g. point of interest [POI] services, venue services or geofences
• CPC Class Codes: H04W 4/40 for vehicles, e.g. vehicle-to-pedestrians [V2P]
• CPC Class Codes: H04W 4/90 Services for handling of emergency or hazardous situations, e.g. earthquake and tsunami warning systems [ETWS]

Abstract

An apparatus, method, program product, and system are disclosed for cognitive-based incident response. A sensor module captures baseline environment data related to a traffic incident using one or more sensors at a location of the traffic incident. A recommendation module generates and makes available, in real-time, one or more recommendations for responding to the traffic incident using cognitive computing processes based on the baseline environment data, the one or more recommendations comprising precautionary information for managing one or more emergency situations at the traffic incident. An update module continuously captures new environment data for the traffic incident using the one or more sensors, supplements the baseline environment data with the new environment data, and generates and makes available, in real-time, one or more updated recommendations based on the supplemented environment data using the supplemented environment data and the cognitive computing processes.

Claims

1. An apparatus comprising:

a sensor module that captures baseline environment data related to a traffic incident using one or more sensors at a location of the traffic incident, the baseline environment data transmitted to one or more cognitive computing processes over a computer network;

a recommendation module that;

generates, in real-time, one or more recommendations for responding to the traffic incident using cognitive computing processes based on the baseline environment data, the cognitive computing processes scraping one or more online data sources for information related to the traffic incident for generating the one or more recommendations, the scraped information ranked by relevance to the traffic incident such that highest-ranked information is used to generate the one or more recommendations, the one or more recommendations comprising precautionary information for managing one or more emergency situations at the traffic incident; and

provides the one or more recommendations to first responders that are in transit to the traffic incident;

an update module that;

continuously captures new environment data for the traffic incident using the one or more sensors;

supplements the baseline environment data with the new environment data; and

generates and makes available, in real-time, one or more updated recommendations to first responders at the traffic incident based on the supplemented environment data, the supplemented environment data and the one or more recommendations provided to the cognitive computing processes to scrape the one or more online data sources for information related to the traffic incident and generate the one or more updated recommendations;

a weather module that;

determines, on an ongoing basis during the traffic incident, weather information from the environment data captured by the one or more sensors, the one or more sensors comprising a weather station;

provides the weather information to the cognitive computing processes to determine one or more conditions at the traffic incident that may change responsive to the weather information, the cognitive computing processes accessing weather data from one or more external weather sources; and

updates the one or more recommendations, in real-time, based on the one or more conditions that may change; and

an RFID module that;

determines, on an ongoing basis during the traffic incident, radio-frequency identification (“

RFID”

) information from the environment data captured by the one or more sensors, the one or more sensors comprising an RFID tag reader;

provides the RFID information to the cognitive computing processes to determine contents of one or more containers at the traffic incident, the cognitive computing processes referencing one or more of electronic manifests and payload data using the RFID information to determine the contents of the one or more containers; and

updates the one or more recommendations, in real-time, based on the determined container contents.

2. The apparatus of claim 1, wherein the cognitive computing processes are located on a remote server accessible to one or more computer networks comprising information related to the traffic incident, the environment data transmitted from the traffic incident to the remote server over the one or more computer networks.

3. The apparatus of claim 1, further comprising an alert module that immediately generates and sends an alert to responders at the traffic incident in response to the cognitive computing processes determining a high-risk situation at the traffic incident based on the environment data.

4. The apparatus of claim 1, wherein the cognitive computing processes further access and analyze traffic incident data from previous traffic incidents for traffic incident data that is similar to one or more conditions of the traffic incident to generate the one or more recommendations for responding to the traffic incident.

5. The apparatus of claim 1, further comprising an individual module that:

determines, on an ongoing basis during the traffic incident, image data from the environment data captured by the one or more sensors, the one or more sensors comprising a camera;

provides the image data to the cognitive computing processes to identify one or more persons present at the traffic incident and to determine background information for the one or more identified persons, the cognitive computing processes accessing background check and medical record data to determine the background information for each of the one or more persons; and

updates the one or more recommendations, in real-time, in response to the background information indicating that one or more individuals at the traffic incident one or more of poses a threat and has a documented medical condition.

6. The apparatus of claim 1, further comprising a temperature module that:

determines, on an ongoing basis during the traffic incident, thermal imaging data from the environment data captured by the one or more sensors, the one or more sensors comprising a thermal camera;

provides the thermal imaging data to the cognitive computing processes to identify one or more areas of the traffic incident where the temperature indicates one or more of an area that is a fire risk and an area where the temperature is abnormal; and

updates the one or more recommendations, in real-time, based on the identified areas.

7. The apparatus of claim 1, further comprising an OCR module that:

determines, on an ongoing basis during the traffic incident, one or more images of the environment data captured by the one or more sensors that comprises textual information, the one or more sensors comprising a camera;

provides the one or more images comprising textual information to the cognitive computing processes to recognize and determine identifying information for one or more of parties involved in the traffic incident, companies associated with parties involved in the traffic incident, and shipping containers involved in the traffic incident; and

updates the one or more recommendations, in real-time, based on the identifying information.

8. The apparatus of claim 1, further comprising a medical module that:

determines, on an ongoing basis during the traffic incident, medical transponder information from the environment data captured by the one or more sensors, the one or more sensors comprising a medical transponder frequency scanner;

provides the medical transponder information to the cognitive computing processes to determine whether conditions at the traffic incident may be detrimental to persons that have medical conditions associated with the medical transponders; and

updates the one or more recommendations, in real-time, based on the medical transponder information.

9. The apparatus of claim 1, wherein the one or more recommendations further comprises recommendations for equipment that may be needed to manage one or more situations at the traffic incident, the equipment comprising one or more of medical equipment, fire extinguishing equipment, and chemical handling equipment.

10. The apparatus of claim 1, wherein the one or more sensors are associated with one or more of a vehicle involved in the traffic incident, a vehicle proximate to the traffic incident, a traffic signal control system, a responder'"'"'s device, and a driver'"'"'s device.

17. The apparatus of claim 1, wherein the recommendation module is further configured to send an image of a placard on a semi-truck hauling chemicals that is involved in the traffic incident to a remote server to be analyzed using one or more cognitive computing processes, the image captured by the one or more sensors at the location of the traffic incident, the image being processed for text information that can be used to scrape the online data sources for handling information related to safely handling the chemicals in the semi-truck, the handling information provided as a recommendation for the first responders.

11. A system comprising:

one or more local devices at a traffic incident;

one or more sensors communicatively coupled to the one or more local devices;

a remote server communicatively coupled to the one or more local devices over one or more computer networks, the remote server executing one or more cognitive computing processes;

a sensor module that captures baseline environment data related to a traffic incident using one or more sensors at a location of the traffic incident, the baseline environment data transmitted to one or more cognitive computing processes over a computer network;

a recommendation module that;

generates, in real-time, one or more recommendations for responding to the traffic incident using cognitive computing processes based on the baseline environment data, the cognitive computing processes scraping one or more online data sources for information related to the traffic incident for generating the one or more recommendations, the scraped information ranked by relevance to the traffic incident such that highest-ranked information is used to generate the one or more recommendations, the one or more recommendations comprising precautionary information for managing one or more emergency situations at the traffic incident; and

provides the one or more recommendations to first responders that are in transit to the traffic incident;

an update module that;

continuously captures new environment data for the traffic incident using the one or more sensors;

supplements the baseline environment data with the new environment data; and

generates and makes available, in real-time, one or more updated recommendations to first responders at the traffic incident based on the supplemented environment data, the supplemented environment data and the one or more recommendations provided to the cognitive computing processes to scrape the one or more online data sources for information related to the traffic incident and generate the one or more updated recommendations;

a weather module that;

determines, on an ongoing basis during the traffic incident, weather information from the environment data captured by the one or more sensors, the one or more sensors comprising a weather station;

provides the weather information to the cognitive computing processes to determine one or more conditions at the traffic incident that may change responsive to the weather information, the cognitive computing processes accessing weather data from one or more external weather sources; and

updates the one or more recommendations, in real-time, based on the one or more conditions that may change; and

an RFID module that;

determines, on an ongoing basis during the traffic incident, radio-frequency identification (“

RFID”

) information from the environment data captured by the one or more sensors, the one or more sensors comprising an RFID tag reader;

provides the RFID information to the cognitive computing processes to determine contents of one or more containers at the traffic incident, the cognitive computing processes referencing one or more of electronic manifests and payload data using the RFID information to determine the contents of the one or more containers; and

updates the one or more recommendations, in real-time, based on the determined container contents.

12. The system of claim 11, wherein the captured environment data is transmitted from the one or more local devices to the remote server over the one or more computer networks to be processed using the cognitive computing processes.

13. The system of claim 11, further comprising an alert module that immediately generates and sends an alert to responders at the traffic incident in response to the cognitive computing processes determining a high-risk situation at the traffic incident based on the environment data.

14. The system of claim 11, wherein the one or more sensors are associated with one or more of a vehicle involved in the traffic incident, a vehicle proximate to the traffic incident, a traffic signal control system, a responder'"'"'s device, and a driver'"'"'s device.

16. The method of claim 14, wherein the cognitive computing processes are located on a remote server accessible to one or more computer networks comprising information related to the traffic incident, the environment data transmitted from the traffic incident to the remote server over the one or more computer networks.

18. The system of claim 11, wherein the recommendation module is further configured to send an image of a placard on a semi-truck hauling chemicals that is involved in the traffic incident to a remote server to be analyzed using one or more cognitive computing processes, the image captured by the one or more sensors at the location of the traffic incident, the image being processed for text information that can be used to scrape the online data sources for handling information related to safely handling the chemicals in the semi-truck, the handling information provided as a recommendation for the first responders.

15. A method comprising:

capturing baseline environment data related to a traffic incident using one or more sensors at a location of the traffic incident, the baseline environment data transmitted to one or more cognitive computing processes over a computer network;

generating, in real-time, one or more recommendations for responding to the traffic incident using cognitive computing processes based on the baseline environment data, the cognitive computing processes scraping one or more online data sources for information related to the traffic incident for generating the one or more recommendations, the scraped information ranked by relevance to the traffic incident such that highest-ranked information is used to generate the one or more recommendations, the one or more recommendations comprising precautionary information for managing one or more emergency situations at the traffic incident;

providing the one or more recommendations to first responders that are in transit to the traffic incident;

continuously capturing new environment data for the traffic incident using the one or more sensors;

supplementing the baseline environment data with the new environment data;

generating and making available, in real-time, one or more updated recommendations to first responders at the traffic incident based on the supplemented environment data, the supplemented environment data and the one or more recommendations provided to the cognitive computing processes to scrape the one or more online data sources for information related to the traffic incident and generate the one or more updated recommendations;

determining, on an ongoing basis during the traffic incident, weather information from the environment data captured by the one or more sensors, the one or more sensors comprising a weather station;

providing the weather information to the cognitive computing processes to determine one or more conditions at the traffic incident that may change responsive to the weather information, the cognitive computing processes accessing weather data from one or more external weather sources;

updating the one or more recommendations, in real-time, based on the one or more conditions that may change;

determining, on an ongoing basis during the traffic incident, radio-frequency identification (“

RFID”

) information from the environment data captured by the one or more sensors, the one or more sensors comprising an RFID tag reader;

providing the RFID information to the cognitive computing processes to determine contents of one or more containers at the traffic incident, the cognitive computing processes referencing one or more of electronic manifests and payload data using the RFID information to determine the contents of the one or more containers; and

updating the one or more recommendations, in real-time, based on the determined container contents.