| CPC G06Q 10/0635 (2013.01) [G06Q 30/0205 (2013.01); G06Q 30/0245 (2013.01); G06Q 50/01 (2013.01)] | 20 Claims |
|
1. A device, comprising:
a processing system including a processor; and
a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations, the operations comprising:
obtaining environmental data from a plurality of environmental data sources;
receiving, via a user interface (UI), a request that specifies a location, wherein the environmental data includes data associated with the location;
accessing profile information relating to a user or an entity;
based on the request, evaluating the environmental data in accordance with the profile information relating to the user or the entity;
generating a report or a recommendation for the location based on the evaluating, wherein the generating involves risk calculations for the location that are performed using a reinforcement learning algorithm, wherein the reinforcement learning algorithm is trained at least in part on a periodic basis based on tracking of actions or activities associated with the user or the entity, and wherein the actions or the activities associated with the user or the entity include user or entity feedback submitted via the UI;
causing the UI to output the report or the recommendation, thereby providing environmental-based information for the location that is personalized to the user or the entity, wherein the location comprises a geographic region, wherein the report or the recommendation comprises different grades across different areas of the geographic region, including a first grade for a first area of the geographic region and a second grade for a second area of the geographic region that is lower than the first grade, and wherein the causing involves presenting a map that shows the first area and the second area, displaying a first boundary line for the first area and a second boundary line for the second area such that a first manner of presentation of the first boundary line is periodically adjusted while a second manner of presentation of the second boundary line remains unchanged, and applying a first blinking fill in the first area while applying a second fill in the second area that blurs the second area such that the second area is determined to be less visually clear than the first area, so as to visually highlight the first area as having a higher grade than the second area; and
after the causing the UI to output the report or the recommendation:
detecting particular user or entity feedback that is submitted via the UI regarding accuracy associated with the report or the recommendation,
detecting a relocation of the user or the entity from one location at which the user or the entity has resided or conducted operations to a different location,
causing the reinforcement learning algorithm to be re-trained based on the detecting the particular user or entity feedback and also based on the detecting the relocation of the user or the entity, resulting in a re-trained reinforcement learning algorithm that provides improved risk calculations, relative to the reinforcement learning algorithm, when evaluating candidate locations for the user or the entity with respect to environmental risk, and
utilizing the re-trained reinforcement learning algorithm to perform one or more risk calculations for the user or the entity in relation to another location responsive to receiving another request to evaluate other environmental data that includes data associated with the another location, thereby facilitating output of another report or another recommendation for the user or the entity.
|