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公开(公告)号：US12283836B2
公开(公告)日：2025-04-22
申请号：US18640871
申请日：2024-04-19
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain
Abstract: Uses of artificial intelligence in battery technology including a method that includes receiving input data associated with at least one sensor. The method includes executing at least one trained model by a processor. Executing the trained model comprises providing the input data to the at least one trained model to generate a model output. The method further includes determining, based on the model output, whether to initiate or terminate selectively charging a first battery cell of a battery.
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公开(公告)号：US11967850B2
公开(公告)日：2024-04-23
申请号：US16999980
申请日：2020-08-21
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain
CPC classification number: H02J7/007 , G06N3/084 , G06N3/086 , H02J7/1423 , H02J7/24
Abstract: Uses of artificial intelligence in battery technology including a method that includes receiving a trained model, receiving sensor data from at least one sensor associated with a battery, and executing the trained model by a processor. Executing the trained model includes providing the sensor data as input to the trained model to generate a model output. The method also includes sending, from the processor to a charge controller coupled to the battery, a control signal that is based on the model output and automatically, by the charge controller, initiating or terminating charging of the battery based on the control signal.
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公开(公告)号：US20220077878A1
公开(公告)日：2022-03-10
申请号：US17467922
申请日：2021-09-07
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain
Abstract: A method includes determining, based at least in part on parameters of a software-defined radio (SDR), waveform data descriptive of an electromagnetic waveform. The method also includes generating feature data based on the waveform data and based on one or more symbols decoded from the electromagnetic waveform. The method further includes providing the feature data as input to a first machine-learning model and initiating a response action based on an output of the first machine-learning model.
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公开(公告)号：US10410116B2
公开(公告)日：2019-09-10
申请号：US14644346
申请日：2015-03-11
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain , Martin Andreas Abel , Qasim Iqbal
IPC: G06N3/08
Abstract: An aspect of the present invention is to provide a system and method for predicting the remaining useful time of mechanical components such as bearings. Another aspect of the present invention is to provide a system and method for predicting the remaining useful time of bearings based on available condition monitoring data. Another aspect of the present invention is to provide a system and method for automatically deciding which columns of input information are the most significant for predicting the remaining useful life of bearings. Another aspect of the present invention is to provide a system and method for performing an analysis of both test bearings and training bearings and determining which training bearings are most similar to a given test bearing. Another aspect of the present invention is to provide a system and method for training an artificial neural network.
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公开(公告)号：US10410111B2
公开(公告)日：2019-09-10
申请号：US15793866
申请日：2017-10-25
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain
Abstract: A computer system includes a memory storing a data structure representing a neural network. The data structure includes a plurality of fields including values representing topology of the neural network. The computer system also includes one or more processors configured to perform neural network classification by operations including generating a vector representing at least a portion of the neural network based on the data structure. The operations also include providing the vector as input to a trained classifier to generate a classification result associated with at least the portion of the neural network, where the classification result is indicative of expected performance or reliability of the neural network. The operations also include generating an output indicative of the classification result.
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Patent Agency Ranking
公开(公告)号：US20190122096A1
公开(公告)日：2019-04-25
申请号：US15793866
申请日：2017-10-25
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain
CPC classification number: G06N3/04 , G06F11/3447 , G06F11/3495 , G06N20/00
Abstract: A computer system includes a memory storing a data structure representing a neural network. The data structure includes a plurality of fields including values representing topology of the neural network. The computer system also includes one or more processors configured to perform neural network classification by operations including generating a vector representing at least a portion of the neural network based on the data structure. The operations also include providing the vector as input to a trained classifier to generate a classification result associated with at least the portion of the neural network, where the classification result is indicative of expected performance or reliability of the neural network. The operations also include generating an output indicative of the classification result.
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公开(公告)号：US10207816B1
公开(公告)日：2019-02-19
申请号：US15704991
申请日：2017-09-14
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain , John Rutherford Allen
Abstract: A distributed sensor module system comprises a plurality of sensor modules configured to be aerially deployable from a deployment device, the deployment device including an unmanned aerial vehicle (UAV) or an aeronautically deployable unitized container, the plurality of sensor modules configured to communicate with each other. A first sensor module comprises a first sensor configured to obtain first sensor information from a first environment proximate to the first sensor, a processor coupled to the first sensor, the processor configured to process the first sensor information to obtain locally processed first sensor information, and a communication transceiver coupled to the processor, the communication transceiver configured to communicate the locally processed first sensor information to a second sensor module, the first sensor module and the second sensor module configured to be aerially deployable.
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8.发明申请公开(公告)号：US20180300630A1
公开(公告)日：2018-10-18
申请号：US15663488
申请日：2017-07-28
Applicant: SparkCognition, Inc.
Inventor： Sari Andoni , Keith D. Moore , Syed Mohammad Amir Husain
Abstract: A method includes determining a trainable model to provide to a trainer, the trainable model determined based on modification of one or more models of a plurality of models. The plurality of models is generated based on a genetic algorithm and corresponds to a first epoch of the genetic algorithm. Each of the plurality of models includes data representative of a neural network. The method also includes providing the trainable model to the trainer. The method further includes adding a trained model, output by the trainer based on the trainable model, as input to a second epoch of the genetic algorithm, the second epoch subsequent to the first epoch.
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公开(公告)号：US09983581B1
公开(公告)日：2018-05-29
申请号：US15705027
申请日：2017-09-14
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain , John Rutherford Allen
CPC classification number: G05D1/0038 , B64C39/024 , B64C2201/042 , B64C2201/121 , B64C2201/141 , B64C2201/146 , G05D1/0027 , G05D1/0088 , H04N7/18 , H04N7/181
Abstract: A method and system comprises a plurality of electronically controlled distributed devices and a supervisory node. The supervisory node comprises a communications interface, a processor, and a display. The supervisory node is configured to communicate with the plurality of electronically controlled distributed devices via the communications interface. The supervisory node is adapted to receive sensor information, to receive functionality information and device status information, to determine useful life prognostics from the functionality information, to obtain human defined policy and strategy directives, to assess the useful life prognostics and device status information based on the human defined policy and strategy directives to provide device assessments, to construct device commands for the plurality of electronically controlled distributed devices based on the device assessments using the processor, and to communicate the device commands to the plurality of electronically controlled distributed via the communications interface.
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公开(公告)号：US20150220850A1
公开(公告)日：2015-08-06
申请号：US14174382
申请日：2014-02-06
Applicant: SparkCognition, Inc.
Inventor： Syed Mohammad Amir Husain
IPC: G06N99/00
Abstract: A system and method for generating a heuristic is provided. A heuristic is capable of identifying data patterns. The method includes: extracting a data set from multiple input sources; creating a set of unique elements used across the data set; organizing the data set into a geometric structure; grouping portions of the data in the geometric structure into a plurality sub geometric structures; determining base attributes for each sub geometric structure using the set of unique elements; identifying trends in the base attributes among the sub geometric structures; and outputting the heuristic as a combination of the base attributes and the trends.
Abstract translation: 提供了一种用于生成启发式的系统和方法。 启发式能够识别数据模式。 该方法包括：从多个输入源提取数据集; 创建一组在数据集中使用的唯一元素; 将数据集组织成几何结构; 将几何结构中的数据的部分分组成多个子几何结构; 使用所述一组唯一元素来确定每个子几何结构的基本属性; 识别子几何结构之间基本属性的趋势; 并输出启发式作为基本属性和趋势的组合。
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