Bank of America Corporation

Abb Technology Ltd

Pictory, Corp

Shailendra Singh

Sandeep Kumar Chauhan

Maneesh Kumar Sethia

Saurabh Gupta

Vasuki Anand

Abhijit Behera

Saurabh Garg

Rama Rao Gaddam

Satyajeet Priyadarshi

Ashutosh Tripathi

Amit Mishra

Durga Prasad Kutthumolu

Saurabh Arora

Krithika Viswanathan

Nandini Rathaur

Sneha Padiyar

Nimish Ravindra Deshpande

Kamlesh Kanayalal Gangaramani

Amardeep Singh Talwar

Amit Kumar Bidhanya

Gowri Sundar Suriyanarayanan

Swadeep Mekala

Sandeep Verma

Prashant Khare

Puneetha Polasa

Govinda Rajulu Nelluri

Subburathinam Krishnan

Sheetal Bhatia

Savitri Jaganath Podal

Saurabh Uprit

Swathi Bussa

Vinod Maghnani

Amrut Gopal Nayak

Bhagat Kumar Allugubelly

Saravanan Balasubramanian

Santosh Kumar Miryala

Zhanwei Tu

Ramarao Gaddam

Suryanarayana Adivi

Divya Sharma

Pushkar Taneja

Ajay Kumar Gowni

Moses Salagala

Thomas Boffin James

Manimaran Sundaravel

Pavan Kumar Gauji

Jai Issrani

Debarati Aich

Govinda Ramam Gonna Satya Sai

Ankit Dholakiya

Arup Francis

Savitri Sibaram Desulu

Suresh K S

Pushpa Neelakantan

Shreya Manocha

Subbiahthever Dukkaiappan

Vikram Chalana

Vishal Chalana

Vaddi Sreenivasulu Reddy

Ashish Kumar Dwivedi

Salma Umme

Sarabjeet Kaur

Divya Nagarajan

Suresh Loganathan

Gaurav Sachdeva

Sukanya V

Tushar Agarwal

Kavitha Hariharan

Raj Kiran Akkera

Sharvani Ganachary

Charles Joseph Fernandez

Shyam Prasad Rokula

Abid Ali Mohammed

Anu Joy

Amaresh Gunasekar

Arul Victor Benjamin

Arrangements for leveraging LiDAR for user validation are provided. A computing platform may receive, from a spatial computing device, first data of a first user environment at a first time captured via LiDAR. A first spatial computing map of the first user environment at the first time may be generated and scored to indicate a likelihood that a user of the spatial computing device is valid. The computing platform may receive a request to process an event. In response, the computing platform may cause the spatial computing device to capture, via LiDAR, second data of a current environment of the user at a current time. A second spatial computing map based on the current environment of the user at the current time may be generated and scored. The score for the second spatial computing map may be compared to a threshold to determine whether to process the requested event.

Leveraging spatial computing lidar feedback to dynamically generate identity profiles

Systems, computer program products, and methods are described herein for auto-establishing secure connections for interrupted data transmissions. The present disclosure is configured to identify an interrupted data transmission comprising a transmission data request; transform the transmission data request to a distributed channel data format to generate a distributed channel data request; transmit the distributed channel data request to an active acquirer switching platform; identify, by the active acquirer switching platform, an acquirer server(s); select, by the active acquirer switching platform, a primary active acquirer server for the distributed channel data request; generate, based on the distributed channel data request and the primary active acquirer server, an acquirer data packet comprising authorized data from at least the transmission data request and device handler data of the primary active acquirer server in the distributed channel data format; and transmit the acquirer data packet to the primary active acquirer server.

Systems and methods for auto-establishing secure connections for interrupted data transmissions

Method and apparatus for processing and executing a user transaction using a spatial computing Internet-of-Things ('IoT') device. The method and apparatus may include generating a map from mapping an environment surrounding the spatial computing IoT device. The method and apparatus may include identifying an image of a face on the map. The method and apparatus may include retrieving user identifier information (“UII”) of the face. The method and apparatus may include storing UII in pixels on the face. The method and apparatus may include using UII as a public key. The method and apparatus may include using trust score colors as a private key. The method and apparatus may include executing, using the private key and the public key as a dynamic passkey, a transaction requested by a user associated with the spatial computing IoT device. The transaction may be associated with the user associated with the identified face.

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

Systems, methods, and apparatus are provided for AI-based generation of a secure network path and corresponding encryption protocols. AI algorithms may detect network nodes for data transfer from an origin point to a destination point. The nodes may be located in different countries. Nodes may be selected based on security levels and regulatory profiles generated for each node. AI algorithms may analyze the transfer data and output encryption algorithms for generating synthetic data from the transfer data. The encryption algorithms may be mapped to the nodes based on security levels and regulatory profiles associated with the nodes. A node may receive the transfer data and apply the mapped encryption algorithm. Successive nodes may iteratively encrypt the transfer data. A data packet header may include an identifier for each encryption algorithm applied to the transfer data.

Artificial intelligence (AI) based secure network protocols with dynamic multilayer encryption

Systems and processes are disclosed to monitor and control toxic configuration in software container deployment. AI-based monitor in each node provides end-to-end fault management system that can detect, diagnose, classify, and suggest remediation actions for non-virtualized cloud-based misconfiguration vulnerabilities. Anomalies are diagnosed using pre-computed fault signatures and automated remediation is integrated with a cloud management stack. Multiple monitoring layers within nodes secure the container-based virtualization environment. Container-based 'CSTC security framework' virtualization technology provides security and identifies potential toxic configuration threats. CSTC security locates container-based systems at severe risk for DDOS attacks to kernel vulnerability/container breakout and ensures appropriate privilege configuration for user processes. Resource access limited based on policies and CSTC security profiles as well as provide AI-based monitoring of container runtime behavior to provide additional security layer that ensures safety and protection in container-based virtualization.

Monitor and control toxic configuration in container deployment

A system for dynamically caching information includes a memory for storing location information and user information and a processor configured to periodically receive geolocation data associated with a first external device and store that geolocation data, along with a time stamp, as location information in the memory. After a predetermined period of time, the processor retrieves from the memory the location information corresponding to the predetermined time period. Machine learning is used to determine the probability of a first action. When the probability is higher than the first predetermined amount, the processor is configured to retrieve information needed to perform a first action and send the retrieved information to a second external device to store the information as cached information. This cached information is then used to perform a first action using the cached information on the second external device.

Dynamic caching based on a user's temporal and geographical location

The present disclosure provides a method. The method includes receiving a request from a user to generate content using generative artificial intelligence based on an original prompt having a first specific parameter and a second specific parameter. The method includes determining an authority level of the user and determining an authority level of the first specific parameter and the second specific parameter. The method includes determining whether the user is authorized to access the first specific parameter and the second specific parameter based on the authority level of the user. The method includes modifying the first specific parameter into a first generalized parameter and modifying the second specific parameter into a second generalized parameter. The method includes creating a modified prompt to generate the content using the generative artificial intelligence, wherein the modified prompt obfuscates the content of the original prompt using the first and second generalized parameter.

System and method for controlling generative artificial intelligence output based on user entitlements

A method includes rendering, on displays of an extended reality (XR) device, an XR environment, and detecting, based on sensor data obtained from sensors of the XR device, a device capability associated with the XR device and one or more environmental conditions associated with the XR environment. The method further includes receiving a request corresponding to one or more user interactions with an XR application. In response to receiving the request, the method includes generating, based the device capability and the environmental conditions, a dynamic digital profile to be associated with the user, in which the dynamic digital profile is dynamically generated to be responsive to one or more input modalities associated with the request, and render, on the displays, the dynamic digital profile. The rendered dynamic digital profile includes a set of elements responsive to the one or more input modalities of the request.

System and method for generating and securing a user-specific application in an extended reality environment

Embodiments of the present invention provide a system for secure validation, registration, and distribution of resources in a distributed electronic network. In particular, the system may be configured to determine that a user is at a third party entity location for acquiring computing device provided by a third party entity associated with the third party entity location, establish a connection between a user device of the user and the computing device, cause the user device to extract computing device information associated with the computing device, via the connection, receive an input associated with acquiring the computing device, transfer funds associated with acquiring the computing device from a resource pool of the user to an entity resource pool associated with the third party entity, via the user device, and establish a smart contract between the user and the third party entity associated with the computing device.

System and method for secure validation, registration, and distribution of resources in a distributed electronic network

A method is provided herein for evaluating a physical building, utilizing an automated image capture apparatus, a spatial computing apparatus, a machine learning model, a blockchain network, and a computer processor, the method including capturing and analyzing images of the building, dividing the building into sections, identifying defective characteristic(s) in and assigning a status to each section, sharing the images and status identifiers with a remote user, the remote user reviewing the images and identifiers, and receiving feedback from the remote user. When a section lacks sufficient images to determine whether a defect is present, the section may be flagged, and a supplemental image(s) may be captured and provided by the remote user. When no additional images are needed, the section may be indicated as completed. Otherwise, the section may retain its flagged status, and the aforementioned steps may be repeated as necessary.

Methods and systems for evaluating buildings

Apparatus and methods for securing a communication link. The apparatus may include a microprocessor. The apparatus may include a memory cell. The apparatus may include a photovoltaic circuit. The apparatus may include a radio frequency transceiver circuit. The apparatus may include an organic light emitting diode display circuit. The microprocessor may be embedded in an information card. The memory cell may be embedded in the information card. The photovoltaic circuit may be embedded in the information card. The radio frequency transceiver may be embedded in the information card. The organic light emitting diode display may be embedded in the information card. The display circuit may include an array of separately excitable diode fields. The display circuit may include a display controller that is in electronic communication with each of the fields.

Mobile phone pairing for dynamic spatial activation of communication device

A registered lower orbit satellite-powered generative artificial intelligence ('AI')-based lost active smart card (“ASC”) tracking and reporting mechanism. The methods and systems may include detecting a threshold distance between a lost ASC and a user device. The lost ASC may initiate a reporting, may include a microwave communication transceiver, and may be associated with an originating entity. The methods and systems may include determining a threshold time that the lost ASC was located at least the threshold distance from the user device. The methods and systems may include tracking the geolocation of the lost ASC by submitting instructions to the lost ASC, instructing the lost ASC to emit a beeping noise, and reporting lost ASC geocoordinates to the originating entity. The lost ASC may emit the beeping noise in response to receipt of the instructions from a satellite network.

Registered lower orbit satellite-powered generative artificial intelligence ('AI')-based lost card tracking and reporting mechanism

A system includes a memory and a processor that validates an interaction between an initiating and a receiving device. An encrypted request is received to perform the interaction and the processor extracts an initiating device identification, a receiving device identification, and one or more numerical values associated with the interaction. Using this extracted information, the processor produces a verification key by applying a hash function and a verification checksum value using a checksum function. The verification key and verification checksum value are then compared with an authentication key and authentication checksum value that were produced in a same manner prior to the interaction being initiated. If it is determined that either the verification key and the authentication key do not have the same value, or verification checksum value and authentication checksum value do not have the same value, then the interaction is reversed.

System and method for validating an interaction using an agreement key

A method for modifying smart card properties of a smart card leveraging a spatial computing device is provided. The spatial computing device may be in electronic communication with an entity server. The method may include identifying the smart card within a field of view of the spatial computing device. The method may include establishing a wireless communication between the smart card and the spatial computing device. The method may further include generating a digital copy of the smart card and displaying the digital copy of the smart card on a display of the spatial computing device. The method may further include displaying a plurality of selectable options for modifying card properties of the smart card and in response to a detection of a selection of one of the selectable options, transmitting a request to the entity server to modify a property of the smart card based on the selected option.

Leveraging spatial computing to modify smart card properties

A method for providing a QR code. The method includes generating a map of an environment surrounding a spatial computing device. The map may be converted into a video. The video may be stored in a database. The video may be divided into multiple frames. A pattern may be arranged for placement of the frames. The frames may be placed inside the QR code in accordance with the pattern. The QR code may be scanned. The pattern may be decoded. The video frames may be retrieved, and the video may be restored. A request associated with the QR code may be executed.

Spatial computing device powered lidar technology enabled dynamic quick response ('QR') code generation mechanism

Growing community of inventors

Maharashtra, India

Shailendra Singh