Simulation of Wi-Fi signal propagation in three-dimensional visualization

    公开(公告)号:US12170546B2

    公开(公告)日:2024-12-17

    申请号:US18354478

    申请日:2023-07-18

    Abstract: The present disclosure is directed to 3-D visualization of wireless signal propagation representing wireless signal strength and interference in 3-D space. The present technology can identify a plurality of access points (APs) in the 3-D space, determine a wireless signal strength for each of the plurality of APs, and determine an interference with the wireless signal strength of each of the plurality of APs, wherein the interference is caused by a neighboring AP of the plurality of APs in the 3-D space. The present technology can further present a 3-D visualization of a wireless signal propagation pattern representing the wireless signal strength from each of the plurality of APs in the 3-D space and the interference from the neighboring AP.

    Reducing complexity of workflow graphs through vertex grouping and contraction

    公开(公告)号:US11681545B2

    公开(公告)日:2023-06-20

    申请号:US16815980

    申请日:2020-03-11

    CPC classification number: G06F9/4843 G06F16/2246 G06F16/287

    Abstract: Systems, methods, and computer-readable media for generating and presenting workflow graphs can include the following operations. A workflow graph including vertices is provided. An event is received to reorganize the vertices of the workflow graph. Each of the vertices is classified with a significance level, the significance level is based on at least one of a business rule and a vertex position of a vertex of the vertices. Vertices of the vertices having a low significance level are grouped together. The vertices in the group having the low significance level are combined into a new vertex, and the new vertex is expandable and collapsible to view the vertices in the group having the low significance level.

    Augmented reality wireless planning and troubleshooting

    公开(公告)号:US11410399B1

    公开(公告)日:2022-08-09

    申请号:US17390692

    申请日:2021-07-30

    Abstract: The present technology includes calculating the 3-D RF propagation pattern in a space for at least one Wi-Fi access point and displaying a visualization of the RF propagation pattern in augmented reality (AR). The augmented reality view of the space can be created by capturing at least one image of the space and displaying at least one image of the space on a display with the visualization of the Wi-Fi access point RF propagation pattern on the display overlaid at least one image of the space. The disclosed technology further can calculate the RF propagation properties and render a visualization of the RF propagation patterns in a 3D space by utilizing hardware on a user device. The AR display is useful in visualizing, in-person aspects of a Wi-Fi network and coverage, and can be used in troubleshooting, maintenance, and simulations of equipment variations.

    DYNAMIC PREFETCHING OF ONTOLOGIES BASED ON ML-BASED EXECUTION PATTERN RECOGNITION

    公开(公告)号:US20200334556A1

    公开(公告)日:2020-10-22

    申请号:US16386371

    申请日:2019-04-17

    Abstract: In one embodiment, a device in a network obtains data indicative of one or more execution sequences of a semantic reasoner. The device trains a machine learning model to predict use of an ontology by the semantic reasoner, based on the data indicative of the one or more execution sequences of the semantic reasoner. The device predicts, using the machine learning model, use of a particular ontology by the semantic reasoner. The device prefetches the particular ontology from another device via the network, prior to the semantic reasoner completing an execution sequence that requires the particular ontology.

    OPTIMIZED DETECTION OF NETWORK DEFECT EXPOSURE IN NETWORK ENVIRONMENT

    公开(公告)号:US20200162343A1

    公开(公告)日:2020-05-21

    申请号:US16368735

    申请日:2019-03-28

    Abstract: Present technology is directed to preferred processing and the verification of diagnostic signatures for a plurality of network defect. The disclosed optimization process is based on expressing each Diagnostic Signature as a minimal sum of product Boolean function of associated network commands, followed by ranking of each command reference in the product terms of the Boolean expression as well as each Boolean product terms of the SOP Boolean expressions, and constructing a decision tree based on the provided rankings to thereby determine a minimum set of commands along with an preferred command dispatch sequence for evaluating a Diagnostic Signature. Further aspects include the translation of both the optimization computation (interpretation of network conditions associated with a network defect) and the computed workflow (dispatch of the command) into a series of declarative rules that can be processed by a machine reasoning engine to thereby automate the optimization process.

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