Sap Se

Xuemin Wang

Jie He

Lin Cai

Hong Tao Liu

Xing Zhao

Jianwei Chen

Rajnish Prasad

Qing Shan Zhang

Xiaoling Zhou

Yubo Lou

Baoguo Zhang

Yanbing Li

Methods, systems, and computer-readable storage media for receiving, by an anomalous operation detection service, current signal data representing a driving current applied to a device over a time period, processing, by an anomalous operation detection service, the current signal data through a deep neural network (DNN) module, a frequency spectrum analysis (FSA) module, and a time series classifier (TSC) module to provide a set of indications, each indication in the set of indications indicating one of normal operation of the device and anomalous operation of the device, processing, by an anomalous operation detection service, the set of indications through a voting gate to provide an output indication, the output indication indicating one of normal operation of the device and anomalous operation of the device, and selectively transmitting one or more of an alert and a message based on the output indication.

Internet-of-Things edge services for device fault detection based on current signals

A computer-implemented method for failure diagnosis using fault tree can include: receiving a fault tree comprising a node representing a top event, a plurality of nodes representing respective basic events, and one or more logic gates connecting the plurality of nodes representing the respective basic events to the node representing the top event; obtaining reliability parameters corresponding to the basic events; calculating fault tree importance measures corresponding to the basic events; calculating failure impact factors of the top event corresponding to the basic events, wherein the failure impact factors of the top event are products of the corresponding reliability parameters and the corresponding fault tree importance measures; ranking the basic events based on the failure impact factors of the top event; and identifying a most significant contributor to the top event, wherein the most significant contributor is a basic event having the highest failure cause probability of the top event.

Systems and methods for failure diagnosis using fault tree

Systems and processes for identifying a pointer in an image of an analog instrument are provided herein. An instrument contour in the image corresponding to the analog instrument may be identified. A plurality of candidate pointer contours in the image may be identified and screened using one or more geometric property screening techniques including an evaluation of a geometric area, a distance parameter, and/or a gravity center of the plurality of candidate pointer contours. Principal component analysis (PCA) may be performed to select an identified pointer contour from among the reduced plurality of candidate pointer contours. A linear regression model may be applied to pixel points in the contour area of the identified pointer contour and a slope and angle of an associated pointer represented by the identified pointer contour may be determined based on an output of the linear regression model.

Pointer recognition for analog instrument image analysis

Disclosed herein are system, method, and computer program product embodiments for tracking shop information using blockchain. In an embodiment, a shop application system may gather information related to a shop using various sensors within the shop. For example, the shop application system may identify a flow rate of traffic within the shop or outside of the shop. The shop application system may securely transmit this information to a blockchain cloud platform to be stored onto a blockchain. The blockchain may also maintain store information from a client application system related to shop ownership or tenancy. In this manner, the blockchain may provide a public means for accessing transactions related to a shop as well as provide confidence in the information provided.

Shop platform using blockchain

Disclosed herein are system, method, and computer program product embodiments for vehicular telematics with virtual-reality monitoring capabilities. An example system may establish a data connection to a plurality of sensors corresponding to at least one component of a vehicle, retrieve status information corresponding to the at least one component of the vehicle, from the plurality of sensors, send the status information retrieved from the plurality of sensors to a data set, receive at least one result of predictive analytics performed with the data set, and generate output via an interface. Other embodiments may additionally place requests for new parts or service based on the at least one result of the predictive analytics. The data set may be a structured database or an unstructured cluster. Big data analytics may use simulations for predictions. Output may leverage virtual reality or augmented reality to improve ease of use and intuitiveness for any role of users.

Growing community of inventors

Shanghai, China

Xuemin Wang