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公开(公告)号：US20220277231A1
公开(公告)日：2022-09-01
申请号：US17187432
申请日：2021-02-26
申请人： Hitachi, Ltd.
发明人： Jeremy OSTERGAARD , Joydeep ACHARYA
摘要： Example implementations described herein involve systems and methods to substantially simultaneously orchestrate machine learning models over multiple resource constrained control edge devices, so that the overall system is more agile to changes in events and environmental conditions where the models have been deployed. The example implementations described herein involve multiple processes that when executed, determine a list of edge devices to be updated along with the corresponding models based on correlation.
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2.发明申请UE INITIATED FREQUENCY PARTITIONING BASED CoMP SCHEME FOR DOWNLINK CELLULAR COMMUNICATIONS 有权用于下行通信的基于UE的基于频率分区的CoMP方案公开(公告)号：US20130137442A1
公开(公告)日：2013-05-30
申请号：US13718484
申请日：2012-12-18
申请人： Hitachi, Ltd.
发明人： Joydeep ACHARYA
IPC分类号： H04W84/04
CPC分类号： H04W84/042 , H04J11/0053 , H04W72/02
摘要： In the embodiments of the present invention, proposed is a method in which a CoMP enabled UE chooses the BSs to be in its cooperating set and a BS partitions its bandwidth to serve its own UEs and UEs from other cells that have requested it to be in its cooperating set.
摘要翻译： 在本发明的实施例中，提出了一种方法，其中启用CoMP的UE选择在协作集合中的BS，并且BS分配其带宽以服务于其自己的UE和来自已请求它进入的其他小区的UE 其合作组合。
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3.发明公开公开(公告)号：US20240046650A1
公开(公告)日：2024-02-08
申请号：US17883590
申请日：2022-08-08
申请人： Hitachi, Ltd.
发明人： Joydeep ACHARYA
摘要： Example implementations described herein involve systems and methods that involve recognizing, from sensor data, an area from the plurality of areas and a candidate task from the one or more candidate tasks associated with the area; estimating a probability of each of the plurality of candidate tasks for the each of the plurality of areas for a specific future period of time, based on referencing historical data of task sequences previously executed; accepting the ones of the plurality of candidate tasks for the each of the plurality of areas having the probability being higher than a threshold; and scheduling one or more sensors to activate and transmit in the specific future period of time in associated areas for the plurality of areas associated with other ones of the plurality of candidate tasks for the each of the plurality of areas not having the probability being higher than the threshold.
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公开(公告)号：US20210034031A1
公开(公告)日：2021-02-04
申请号：US16530448
申请日：2019-08-02
申请人： Hitachi, Ltd.
发明人： Joydeep ACHARYA , Sudhanshu GAUR
IPC分类号： G05B19/05
摘要： In example implementations described herein, the power of time series machine learning is used to extract the statistics of Programmable Logic Controller (PLC) data and external sensor data. The accuracy of time series machine learning is improved by manufacturing context-dependent segmentation of the time series into states which is factory may be in. The invention can capture subtle trends in these time series data and be able to classify them into several outcomes from ICS security attacks to normal anomalies and machine/sensor failures.
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公开(公告)号：US20240265582A1
公开(公告)日：2024-08-08
申请号：US18166394
申请日：2023-02-08
申请人： Hitachi, Ltd.
发明人： Joydeep ACHARYA , Ravneet KAUR , Hidenori OMIYA , Yusaku OTSUKA , Takahiro OHIRA , Toshiki SHIMIZU
摘要： A method for computing and detecting image data drift. The method may include retrieving first segment information of a plurality of segments from a drift database; receiving a number of images from a sensor; partitioning each of the received images into segments of a predetermined number; generating second segment information; computing drift in values between the first segment information and the second segment information; and detecting drift based on the computed drift in values by combining the computed drift in segments to generate overall drift, and comparing the overall drift against a drift threshold.
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公开(公告)号：US20230022356A1
公开(公告)日：2023-01-26
申请号：US17372259
申请日：2021-07-09
申请人： Hitachi, Ltd.
发明人： Andrew WALKER , Joydeep ACHARYA
摘要： Example implementations described herein involve a system for training and managing machine learning models in an industrial setting. Specifically, by leveraging the similarity across certain production areas, it is possible to group such areas together to train models efficiently that use human pose data to predict human activities or specific task(s) that the workers are engaged in. Example implementations remove previous methods of independent model construction for each production area and takes advantage of the commonality amongst different environments.
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公开(公告)号：US20200012860A1
公开(公告)日：2020-01-09
申请号：US16026499
申请日：2018-07-03
申请人： Hitachi, Ltd.
摘要： Example implementations described herein are directed to systems and methods for non-invasive data extraction from digital displays. In an example implementation, a method includes receiving one or more video frames from a video capture device capturing an external display, where the external display is independent the video capture device; determining one or more locations within the external display comprising time varying data of the external display; and for each identified location of the time varying data: determining a data type; applying one or more rules based on the data type; and determining an accuracy of the time varying data within the one or more frames based on the rules.
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公开(公告)号：US20180013635A1
公开(公告)日：2018-01-11
申请号：US15201661
申请日：2016-07-05
申请人： Hitachi, Ltd.
发明人： Joydeep ACHARYA , Sudhanshu GAUR
CPC分类号： H04L41/147 , H04L43/0829 , H04L43/0852 , H04L67/303 , H04W4/029 , H04W4/38 , H04W24/04
摘要： In some examples, a computing device may determine a prediction of a network outage of a network. The computing device may determine a priority of one or more data types expected to be received during the network outage. Further, the computing device may determine a latency category of the one or more data types expected to be received during the network outage. The computing device may store a data transmission rule for the one or more data types at least partially based on the priority and the latency category. The computing device may receive, from one or more data generators, during the network outage, data for transmission to the network. The computing device may transmit at least some of the received data to the network at least partially based on the data transmission rule.
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公开(公告)号：US20240028949A1
公开(公告)日：2024-01-25
申请号：US17869528
申请日：2022-07-20
申请人： Hitachi, Ltd.
IPC分类号： G06N20/00
CPC分类号： G06N20/00
摘要： Example implementations described herein involve systems and methods for providing a reward to a machine learning algorithm, which can include receiving an image, and a task description defined in text; slicing the image into a plurality of sub-images; executing an embedding model to embed the text of the task description and the sub-images to generate a distribution for the sub-images based on relevance to the task description; and generating the reward from the distribution for the sub-images.
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公开(公告)号：US20210375492A1
公开(公告)日：2021-12-02
申请号：US16886428
申请日：2020-05-28
申请人： Hitachi, Ltd.
发明人： Andrew WALKER , Joydeep ACHARYA
摘要： Example implementations described herein can dynamically adapt to changing nature of sensor data traffic and through artificial intelligence (AI, strike a good tradeoff between reducing volume of sensed data, and retain enough data fidelity so that subsequent analytics applications perform well. The example implementations eliminate heuristic methods of setting sensing parameters (such as DAQ sampling rate, resolution etc.) and replaces them with an automated, AI driven edge solution core that can be readily ported on any Internet of Things (IoT) edge gateway that is connected to the DAQ.
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