Intelligent method to orchestrate transactions on spatial computing internet-of-things (“IoT”) device on facial trust anchors and passkey

1 . A method for processing and executing transactions using a spatial computing Internet-of-Things (“IoT”) device, the method comprising:

generating a map from mapping, using a light detection and ranging (“LiDAR”) analyzer, an environment surrounding a spatial computing IoT device;

scanning the map by using a facial biometric scanner, the facial biometric scanner being a part of the spatial computing IoT device;

identifying, from the scanning, an image of a face included in the map;

retrieving, from the scanning, user identifier information (“UII”) of the identified face;

dividing the image of the identified face into a plurality of pixels;

storing the UII in the plurality of pixels, one discrete bit of the UII stored in each pixel;

encrypting the UII into an encrypted UII algorithm, the encrypted UII algorithm stored as a public key;

transmitting, via an institution integration module located in the spatial computing IoT device, the public key to an entity computing system;

decoding, at the spatial computing IoT device, the public key into a plurality of numbers, each number in the plurality of numbers corresponding to a color included in a plurality of colors;

arranging each color over a discrete one of the plurality of pixels;

overlaying each color over each discrete pixel;

encrypting the overlayed colors into an encrypted facial biometric algorithm, the encrypted facial biometric algorithm stored as a private key;

converting the private key into a user trust score, the user trust score corresponding to the identified face;

verifying, by a threshold trust score, an authenticity of a user associated with the identified face, said verifying being based upon the user trust score; and

executing a transaction requested by a user associated with the spatial computing IoT device, said transaction associated with a user associated with the identified face, said executing using the private key and the public key as a dynamic passkey for the transaction.

2 . The method of claim 1 further comprising:

identifying, from the scanning, images of a plurality of faces included in the map;

retrieving, from the scanning, UII for each of the plurality of identified faces;

dividing the images of the plurality of identified faces into a plurality of pixels;

storing the UII in the pixels, one discrete bit of the UII stored in each pixel;

encrypting the UII into encrypted UII algorithms, the encrypted UII algorithms stored as public keys;

transmitting, via an institution integration module located in the spatial computing IoT device, the public keys to an entity computing system;

decoding, at the spatial computing IoT device, the public keys into a plurality of numbers, each number in the plurality of numbers corresponding to a color included in a plurality of colors;

arranging each color over a discrete one of the plurality of pixels;

overlaying each color over each discrete pixel;

encrypting the overlayed colors into encrypted facial biometric algorithms, the encrypted facial biometric algorithms stored as private keys;

converting the private keys into user trust scores, the user trust scores corresponding to the plurality of identified faces;

verifying, by a threshold trust score, the authenticities of users associated with the plurality of identified faces, said verifying being based upon the user trust scores; and

executing transactions requested by a user associated with the spatial computing IoT device, said transactions associated with a plurality of users associated with the plurality of identified faces, said executing by using the private keys and the public keys as dynamic passkeys for the transactions.

3 . The method of claim 2 wherein the threshold trust score is 0.9.

4 . The method of claim 2 wherein the spatial computing IoT device is associated with the entity computing system.

5 . The method of claim 2 wherein the LiDAR analyzer forms a part of the spatial IoT computing device.

6 . The method of claim 2 wherein:

grouping the UII into agglomerations based on an IP addresses of last user transactions; and

basing the public key on the agglomerations.

7 . The method of claim 1 wherein the threshold trust score is 0.9.

8 . The method of claim 1 wherein the spatial computing IoT device is associated with the entity computing system.

9 . The method of claim 1 wherein the LiDAR analyzer forms a part of the spatial IoT computing device.

10 . The method of claim 1 further comprising:

grouping the UII into agglomerations based on an IP address of a last user transaction; and

basing the public key on the agglomerations.

11 . Apparatus for processing and executing a user transaction, the apparatus comprising:

a spatial computing Internet-of-Things (“IoT”) device;

a light detection and ranging (“LiDAR”) analyzer, said LiDAR analyzer configured to generate a map from mapping an environment surrounding the spatial computing IoT device; and

the spatial computing IoT device configured to:

scan the map by using a facial biometric scanner, the facial biometric scanner being a part of the spatial computing IoT device;

identify, from the scan, an image of a face included in the map;

retrieve, from the scan, user identifier information (“UII”) of the identified face;

divide the image of the identified face into a plurality of pixels;

store the UII in the pixels, one discrete bit of the UII stored in each pixel;

encrypt the UII into an encrypted UII algorithm, the encrypted UII algorithm stored as a public key;

transmit, via an institution integration module located in the spatial computing IoT device, the public key to an entity computing system;

decode, at the spatial computing IoT device, the public key into a plurality of numbers, each number in the plurality of numbers corresponding to a color included in a plurality of colors;

arrange each color over a discrete one of the plurality of pixels;

overlay each color over each discrete pixel;

encrypt the overlayed colors into an encrypted facial biometric algorithm, the encrypted facial biometric algorithm stored as a private key;

convert the private key into a trust score, the trust score corresponding to the identified face;

verify, by a threshold trust score, an authenticity of a user associated with the identified face, said verifying being based upon the trust score of the user; and

execute a transaction requested by a user associated with the spatial computing IoT device, said transaction associated with a user associated with the identified face, said executing by using the private key and the public key as a dynamic passkey for the transaction.

12 . The apparatus of claim 11 , the spatial computing IoT device further configured to:

identify, from the scanning, images of a plurality of faces included in the map;

retrieve, from the scanning, UII of the plurality of identified faces;

divide the images of the plurality of identified faces into a plurality of pixels;

store the UII in the pixels, one discrete bit of the UII stored in each pixel;

encrypt the UII into encrypted UII algorithms, the encrypted UII algorithms stored as public keys;

transmit, via an institution integration module located in the spatial computing IoT device, the public keys to an entity computing system;

decode, at the spatial computing IoT device, the public keys into a plurality of numbers, each number in the plurality of the numbers corresponding to a color included in a plurality of colors;

arrange each color over a discrete one of the plurality of pixels;

overlay each color over each discrete pixel;

encrypt the overlayed colors into encrypted facial biometric algorithms, the encrypted facial biometric algorithms stored as private keys;

convert the private keys into user trust scores, the user trust scores corresponding to the plurality of identified faces;

verify, by a threshold trust score, the authenticities of users associated with the plurality of identified faces, said verifying being based upon the user trust scores; and

execute, transactions requested by a user associated with the spatial computing IoT device, said transactions associated with a plurality of users associated with the plurality of identified faces, said executing by using the private keys and the public keys as dynamic passkeys for the transactions.

13 . The apparatus of claim 12 wherein the spatial computing IoT device is further configured with a threshold trust score of 0.9.

14 . The apparatus of claim 12 wherein the spatial computing IoT device is associated with the entity computing system.

15 . The apparatus of claim 12 wherein the LiDAR analyzer forms a part of the spatial IoT computing device.

16 . The apparatus of claim 12 wherein the spatial computing IoT device is further configured to:

group the UII into agglomerations based on IP addresses of last user transactions; and

base the public keys on the agglomerations.

17 . The apparatus of claim 11 wherein the spatial computing IoT device is further configured with a threshold trust score of 0.9.

18 . The apparatus of claim 11 wherein the spatial computing IoT device is associated with the entity computing system.

19 . The apparatus of claim 11 wherein the LiDAR analyzer forms a part of the spatial IoT computing device.

20 . The apparatus of claim 11 wherein the spatial computing IoT device is further configured to:

group the UII into agglomerations based on an IP address of a last user transaction; and

base the public key on the agglomerations.