Intel Corporation

Enphase Energy, Inc.

Walmart Apollo, LLC

Emc IP Holding Company LLC

Emc Corporation

Wal-mart Stores, Inc.

Ankit Prakash Gupta

Tanay Karnik

David Arditti Ilitzky

Sumit Saraogi

Ashish Bansal

Dileep J Kurian

Sriram Kabisthalam Muthukumar

Samuel Mattathil Joseph

Sandeep Chandran

Rishabh Goel

Jayant Somani

Badrinarayanan Kothandaraman

Ayyapu Reddy Pallam

Jan Spencer Rosen

Venkata Pranay Kumar Sowdaboina

Saurav Shah

Shelesh Chopra

Vaibhav Vaidya

Christopher Schaef

Suhwan Kim

Pranjali S Deshmukh

Saurabh Bhandari

Harish Krishnamurthy

Ilya Klochkov

Akhila M

A method and apparatus for estimating capacity of a system including an energy generation system, an energy storage system or both. The method and apparatus initially estimate the system capacity based on a facility location and size. The initial estimate may be adjusted through adjustment of at least one parameter. An updated capacity estimate is generated and displayed.

Capacity estimator for an energy generation and/or storage system

An apparatus is provided which comprises: a first Power Management Unit (PMU); and a second PMU, wherein the first PMU is to manage transition of the apparatus from a low power state to a first active state, wherein the second PMU is to manage transition of the apparatus from the first active state to a second active state, and wherein the second PMU is to be powered down while the apparatus is to be in the low power state.

Hierarchical power management unit for low power and low duty cycle devices

Systems, apparatuses and methods may provide for early pre-charge with respect to peak power events. Application performance may improve by pre-charging a supercap just prior to initiating a system wake up from a qualified system wake-source trigger. Additionally, the pre-charging of the supercap may be controlled by a time defined pre-charge period and may also be controlled by a predetermined threshold voltage.

Early pre-charge enablement for peak power application in net zero energy devices

A system for computer-aided visual recognition of products may be used by a customer operating a mobile computing device having a camera. A customer can direct the camera at a targeted product for which the customer desires to purchase or learn information. Image recognition operations can be carried out to compare the captured image against images from a prepopulated product image store of known products. Upon a positive match, information regarding the identified product may be gathered and transmitted to the customer and displayed on the mobile computing device. The customer may be presented with various options regarding the identified product, including adding the product to a shopping list, a to-do list, a wish list, or other types of lists.

Computer vision product recognition

The present disclosure provides for the management of power of a NZE IoT device. Managing power can include receiving the one or more asynchronous events from the asynchronous event system, determining if any of the one or more asynchronous events meet a respective charge qualification, generating the power-on command for the power-managed compute system if any of the one or more asynchronous events meet the respective charge qualification, and waiting for a power source to reach a threshold associated with the respective charge qualification if any of the one or more asynchronous events do not meet the respective charge qualification.

Power management of an NZE IoT device

A system for alerting an employee or agent of a retailer regarding an unfavorable condition may include the use of computer-aided visual recognition of products to aid in identifying the location of the unfavorable condition. A user can direct a mobile computing device camera at one or more targeted products displayed on store shelves. Image recognition operations can be carried out to compare the targeted product image(s) against images from a prepopulated product image store of known products. Upon a positive match, shelf location information of the identified targeted product(s) may be used to determine the current location of the user. The employee or agent may be alerted with respect to the unfavorable condition and the location thereof.

Alert notification

An automation framework for internationalization compliant applications is described. The automation framework includes a computer that executes a parser, an execution engine, and a logger. The parser parses a test case from a test case suite to identify script instructions to test an internationalization compliant application. The script instructions include a reference identifier. The execution engine executes the script instructions to test the internationalization compliant application, to identify at least one message identifier and at least one message string based on referencing a lookup database for an automation framework using the reference identifier, and to validate at least one message identifier and at least one message string with the internationalization compliant application. The logger logs a result of executing the script instructions, and outputs the result via an output device.

Method and system for an automation framework for internationalization compliant applications

A system for computer-aided visual recognition of products may help a customer navigate to a selected product in a retail store. A customer can direct a mobile computing device camera at one or more targeted products displayed on store shelves. Image recognition operations can be carried out to compare the targeted product image(s) against images from a prepopulated product image store of known products. Upon a positive match, shelf location information of the identified targeted product(s) may be used to determine the current location of the customer. An in-store destination location is defined by the shelf location for the selected product. A route may be calculated to navigate the customer from the current location to the destination location.

Computer vision navigation

A configurable automation framework includes a computer that executes an execution driver, a parser, a volume population engine, a configuration checker, an execution engine, and a logger. The execution driver receives user input that specifies configuration options and populates a test case suite based on each combination of the configuration options. The configuration options include operating system options, multipathing software options, volume options, array options, snapshot type options, and/or dataset options. The parser parses the test case to identify script instructions to test an application for each combination. The volume population engine creates volumes based on user input that specifies volume options. The execution engine executes the script instructions to test the application if the configuration checker determines that the computer is setup for each combination. The logger logs a result of executing the script instructions for each combination and outputs the result.

Method and system for a configurable automation framework

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Bengaluru, India

Ankit Prakash Gupta