International Business Machines Corporation

Rodolfo Lopez

Louie Arthur Dickens

Julio Alejandro Maldonado

Gandhi Sivakumar

Juan G Rivera

Pedro V Torres

David B Kumhyr

Michael C Hollinger

John F Behnken

David Michael Green

Stephen M Tee

Chang Chen

Michael R Reddock

Jonathan Terner

Jarom Pena

Mara Miranda Bautista

Alberto Garza

Emile L Kowalski

Alexander David Hames

Donna L Johnson

Zhibao Hu

Jose Morales

Ricardo Daniel Zamora Ruvalcaba

A method, computer program product and computer system to automatically generate augment reality-based guides for maintenance procedures is provided. A processor retrieves non-structured text instructions to perform a maintenance procedure on a device within a data center. A processor extracts at least one imperative statement from the non-structured text instructions. A processor identifies a named entity in the extracted at least one imperative statement from the non-structured text instructions. A processor generates a mapping of the named entity to be used by an augmented reality device, where the mapping indicates the position of the named entity on the device within a data center. A processor provides to the augmented reality device the extracted at least one imperative statement and the mapping of the named entity, where the augmented reality device displays the extracted imperative statement and the mapping of the named entity to a user of the augmented reality device.

Data center guide creation for augmented reality headsets

Deployment updates in multivendor cloud environments are provided by obtaining, from an administrative user, deployment objectives for a network deployment; identifying currently deployed infrastructure in the network deployment; identifying information sources to provide information for evaluating candidates for additional infrastructure to include in the network deployment to meet the deployment objectives; performing a cognitive computing analysis based on the deployment objectives to identify a configuration of the network deployment that includes the additional infrastructure selected from the candidates provided by the information sources; and providing the administrative user with the configuration.

Deployment updates in multivendor cloud environments

System, apparatus, and/or a method for checking hardware components in an information handling system is disclosed that includes selecting a hardware component for testing; supplying power to the hardware component independent from the power supply provided by the information handling system; performing testing on the selected hardware component using power supplied by the independent power supply; determining the success or failure of the testing on the selected hardware component; indicating the result of the testing on the selected hardware component; and if the result of the testing on the selected hardware component is successful indicate the hardware component passed the testing, and if the result of the testing on the selected hardware component is not successful re-seat the hardware component and perform the testing on the selected hardware again.

System and method for hardware component connectivity verification

Systems and methods for replacing and testing a data storage device are disclosed. In disclosed embodiments, a system including a data storage array (DSA) including a plurality of data storage devices (DSDs) in an enclosure. The system further includes an I/O server coupling the DSA to a client node and configured to provide data access between the client node and the DSA. The system further includes a management server coupled to the DSA, configured to detect a failed DSD in the DSA, detect a replacement DSD in the enclosure that replaces the failed DSD, and add the replacement DSD to a logical path of the DSA. The management server is further configured to display an indication of a state of the DSA based on the comparing.

Servicing data storage devices in a data storage array

An approach to determining if a corpus is obsolete for the selected purpose. The approach can receive a corpus and a context from a user. The approach can extract terms from the corpus based on the context. The approach can generate a temporal context mapping of the terms. The approach can analyze the terms based on the temporal context mapping. The approach can determine if a further analysis of the temporal context mapping by a subject matter expert (SME) is necessary and if so, employ an SME for the analysis. The approach can determine if the corpus is obsolete for the selected purpose based on the temporal context mapping. The approach can delete the corpus from the repository and send the user an obsolete notice if the corpus is obsolete or can generate a corpus report and send the user the corpus report if the corpus is not obsolete.

Corpus temporal analysis and maintenance

A computer-implemented method according to one embodiment includes identifying locations of a plurality of components to be implemented within a site, identifying characteristics of the site, and determining details for each of the plurality of components to be implemented within the site, utilizing the location of the plurality of components and the characteristics of the site.

Cognitive component selection and implementation

A method for cognitive-based traffic incident snapshot triggering comprises acquiring data, via a first agent, from each of a plurality of local sensors. The first agent is configured to acquire the data from each of the plurality of local sensors in windows having a first window size. The method also comprises acquiring data, via a second agent, from each of a subset of the plurality of local sensors in windows having a second window size; detecting a pattern in the data acquired via the second agent, the pattern indicating a traffic incident; and in response to detecting a pattern indicating the traffic incident, aggregating all data acquired via the first agent from a time when the pattern was detected until motion of the vehicle stops with the pre-determined number of windows of data stored at the time when the pattern was detected.

Cognitive-based traffic incident snapshot triggering

A sourcing interface enables a particular device communicatively connected on a network to share one or more resources of the particular device with other devices communicatively connected to the network and coordinate task bidding with the other through broadcasting requests on the network. The sourcing interface manages dispatch of a particular task to one or more selected devices, the one or more selected devices selected based on one or more bids received by the particular device that best match a service level of particular request by the particular device, the dispatched task migrated to the one or more selected devices instead of handled by a web service provider. The sourcing interface monitors, at the particular device, for a result of execution of the particular task from the one or more selected devices, the one or more selected devices collecting telemetry data for usage reporting to the web service provider.

Managing resource sharing and task bidding on the internet of things (IoT)

Systems and computer program products to perform an operation comprising receiving an indication of a type and a target of a fault to inject in a network, the network comprising a plurality of devices and a plurality of network elements, generating at least a first predicted network map depicting a predicted configuration of the plurality of devices and network elements subsequent to injecting the fault in the network, injecting the fault at the target in the network, generating an actual network map depicting an actual configuration of the plurality of devices and network elements, identifying, based on a comparison of the first predicted network map and the actual network map, at least one difference in the predicted and actual configurations, and outputting for display an indication of the identified at least one difference.

Testing and delivering verification of network configurations

Methods to perform an operation comprising receiving an indication of a type and a target of a fault to inject in a network, the network comprising a plurality of devices and a plurality of network elements, generating at least a first predicted network map depicting a predicted configuration of the plurality of devices and network elements subsequent to injecting the fault in the network, injecting the fault at the target in the network, generating an actual network map depicting an actual configuration of the plurality of devices and network elements, identifying, based on a comparison of the first predicted network map and the actual network map, at least one difference in the predicted and actual configurations, and outputting for display an indication of the identified at least one difference.

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.

Cognitive-based incident response

Systems, methods, and computer program products to perform an operation comprising identifying a plurality of data sources, receiving input specifying one or more of the plurality of data sources and a set of parameters, wherein the set of parameters comprise at least a product and a due date for the product, generating, based on a machine learning (ML) model and data received from each of the specified one or more data sources, a resource allocation plan for a product specified in the input, wherein the resource allocation plan specifies at to allocate at least one resource to the product, wherein the at least one resource comprises one or more of hardware resources and software resources, and responsive to receiving input accepting the generated resource allocation plan, allocating the at least one resource in the resource allocation plan to develop the product.

Growing community of inventors

Austin, TX, United States of America

Rodolfo Lopez