Secure system utilizing a learning engine
Methods and systems are disclosed for determining resource suitability based at least in part on physical geographic mapping data. An artificial intelligence/learning engine may be trained to determine such resource suitability using training data. The trained artificial intelligence/learning engine may then me used to generate suitability indicators. The suitability indicators may be rendered in association with a map comprising the resource. The resource may be configurable to be shared amongst a plurality of physical resource users in a time displaced manner.
1. A computer implemented method, the method comprising:
accessing, via a computer interface, data from a plurality of databases related to at least a first geographical area, wherein the first geographical area comprises a plurality of resources;
using a first learning engine to evaluate the data from the plurality of databases related to the first geographical area to generate an area suitability indicator for the first geographical area;
causing the generated area suitability indicator to be rendered in association with a map comprising the first geographical area so that the area suitability indicator is displayed at a same time as the map comprising the first geographical area;
determining whether the generated area suitability indicator, associated with the map, satisfies a first threshold;
at least partly in response to determining that the generated area suitability indicator satisfies the first threshold, using a second learning engine to evaluate data related to a first resource, comprising a housing unit, within the first geographical area to generate a resource suitability indicator indicating a suitability of the first resource to be shared amongst a plurality of physical resource users in a time displaced manner;
at least partly in response to determining that the generated resource suitability indicator satisfies a second threshold, enable a first action to be taken, comprising an initiation of an acquiring process with respect to the first resource.
2. The computer implemented method as defined in claim 1 , wherein the data, from the plurality of databases, related to the first geographical area comprises a size of the first geographic area, a number of housing units with the first geographic area, a number of housing units in the first geographic area that are owner occupied, a percentage of housing units in the first geographic area that are owner occupied, a number of housing units in the first geographic area that are short term rentals, a percentage of housing units in the first geographic area that are short term rentals, a number of housing units in the first geographic area that are long term rentals, a percentage of housing units in the first geographic area that are long term rentals, a median inventory age of housing units in the first geographic area, a density of vacation housing units within the first geographic area, a preference index, buffer data for vacation housing units within the first geographical area, an indication as to whether rules prohibit or restrict the use of a housing unit with respect to a first use, and/or demographics of the first geographic area.
3. The computer implemented method as defined in claim 1 , wherein the first learning engine comprises an input layer, one or more hidden layers, and an output layer.
4. The computer implemented method as defined in claim 1 , wherein the first learning engine comprises a neural network, an expert system, a rules-based systems, and/or a support vector machine.
5. The computer implemented method as defined in claim 1 , the method further comprising receiving a suitability query regarding at least one geographical area, wherein the suitability query is received via an encrypted communication encrypted using a public key.
6. The computer implemented method as defined in claim 1 , the method further comprising receiving a suitability query regarding at least one geographical area, wherein the suitability query is received via an encrypted communication encrypted using symmetric encryption.
7. The computer implemented method as defined in claim 1 , wherein the generated area suitability indicator comprises a sentiment indicator.
8. Non-transitory computer readable memory having program instructions stored thereon that when executed by a computer system device cause the computer system to perform operations comprising:
access data from one or more databases related to at least a first geographical area, wherein the first geographical area comprises a plurality of resources;
use a first learning engine to evaluate the data from the one or more databases related to the first geographical area to generate an area suitability indicator for the first geographical area;
cause the generated area suitability indicator to be rendered in association with a map comprising the first geographical area so that the area suitability indicator is displayed at a same time as the map comprising the first geographical area;
use a second learning engine to evaluate data related to a first resource comprising a housing unit, within the first geographical area to generate a resource suitability indicator indicating a suitability of the first resource to be shared amongst a plurality of physical resource users in a time displaced manner; and
at least partly in response to determining that the generated resource suitability indicator satisfies a second threshold, enable a first action to be taken comprising an initiation of an acquiring process with respect to the first resource.
9. The non-transitory computer readable memory as defined in claim 8 , wherein the data, from the one or more databases, related to the first geographical area comprises a size of the first geographic area, a number of housing units with the first geographic area, a number of housing units in the first geographic area that are owner occupied, a percentage of housing units in the first geographic area that are owner occupied, a number of housing units in the first geographic area that are short term rentals, a percentage of housing units in the first geographic area that are short term rentals, a number of housing units in the first geographic area that are long term rentals, a percentage of housing units in the first geographic area that are long term rentals, a median inventory age of housing units in the first geographic area, a density of vacation housing units within the first geographic area, a preference index, buffer data for vacation housing units within the first geographical area, an indication as to whether rules prohibit or restrict the use of a housing unit with respect to a first use, and/or demographics of the first geographic area.
10. The non-transitory computer readable memory as defined in claim 8 , wherein the first learning engine comprises an input layer, one or more hidden layers, and an output layer.
11. The non-transitory computer readable memory as defined in claim 8 , wherein the first learning engine comprises a neural network, an expert system, a rules-based systems, and/or a support vector machine.
12. The non-transitory computer readable memory as defined in claim 8 , the operations further comprising receiving a suitability query regarding at least one geographical area, wherein the suitability query is received via an encrypted communication encrypted using a public key.
13. The non-transitory computer readable memory as defined in claim 8 , the operations further comprising receiving a suitability query regarding at least one geographical area, wherein the suitability query is received via an encrypted communication encrypted using symmetric encryption.
14. The non-transitory computer readable memory as defined in claim 8 , wherein the generated area suitability indicator comprises a sentiment indicator.
15. A system configured to determine resource suitability, the system comprising:
a network interface;
at least one processing device operable to:
receive over a network, using the network interface, an encrypted communication from a client hosted on a user device requesting a resource suitability indicator for a first geographical area with respect to a first resource type configured to be shared amongst a plurality of physical resource users in a time displaced manner;
access data from a plurality of databases related to at least the first geographical area, wherein the first geographical area comprises a plurality of resources;
use a first learning engine to evaluate the data from the plurality of databases related to the first geographical area to generate an area suitability indicator;
generate a multilayer map comprising the first geographical area and a surrounding geographical area, so that the area suitability indicator is displayed at a same time as the multilayer map comprising the first geographical area and the surrounding geographical area;
cause the generated area suitability indicator, associated with the multilayer map, to be rendered in association with the multilayer map comprising the first geographical area and the surrounding geographical area;
determine whether the generated area suitability indicator satisfies a first threshold;
at least partly in response to determining that the generated area suitability indicator satisfies the first threshold, use a second learning engine to evaluate data related to a first resource, comprising a housing unit, within the first geographical area to generate a resource suitability indicator indicating a suitability of the first resource, comprising a housing unit, to be shared amongst a plurality of physical resource users in a time displaced manner; and
at least partly in response to determining that the generated resource suitability indicator satisfies a second threshold, enable a first action to be taken, comprising an initiation of an acquiring process with respect to the first resource.
16. The system as defined in claim 15 , wherein the data from the plurality of databases related to the first geographical area comprises a size of the first geographic area, a number of housing units with the first geographic area, a number of housing units in the first geographic area that are owner occupied, a percentage of housing units in the first geographic area that are owner occupied, a number of housing units in the first geographic area that are short term rentals, a percentage of housing units in the first geographic area that are short term rentals, a number of housing units in the first geographic area that are long term rentals, a percentage of housing units in the first geographic area that are long term rentals, a median inventory age of housing units in the first geographic area, a density of vacation housing units within the first geographic area, a preference index, buffer data for vacation housing units within the first geographical area, an indication as to whether rules prohibit or restrict the use of a housing unit with respect to a first use, and/or demographics of the first geographic area.
17. The system as defined in claim 15 , wherein the first learning engine comprises an input layer, one or more hidden layers, and an output layer.
18. The system as defined in claim 15 , wherein the first learning engine comprises a neural network, an expert system, a rules-based systems, and/or a support vector machine.
19. The system as defined in claim 15 , wherein the encrypted communication is encrypted using a public key.
20. The system as defined in claim 15 , wherein the encrypted communication is encrypted using symmetric encryption.
21. The system as defined in claim 15 , wherein the generated area suitability indicator comprises a sentiment indicator.
22. The system as defined in claim 15 , wherein the system is configured to generate a standard deviation of an expected probability distribution with respect to the area suitability indicator.