5results about How to "Guaranteed effective use" patented technology

This invention provides a water utility call system, comprising: an extension unit connected to the system via a session boundary controller; a session boundary controller for receiving external call requests from customers via the extension unit, forwarding them to a voice processing module, and simultaneously recording corresponding call target information; and a voice processing module with a built-in call control module for: upon receiving a forwarded call request from a customer, calling a historical call record storage database containing a mapping relationship between call target information and target staff identification; determining the target staff identification recorded in the historical call record storage database based on the call target information; and notifying the session boundary controller to initiate a call request to the target staff through the corresponding extension unit.

The invention provides a crop breeding decision analysis system. The crop breeding decision analysis system comprises a data input module, a data processing module, a data analysis module and a result display module, the data input module is used for receiving user material data uploaded by a user; the data processing module is connected with the data input module and is used for preprocessing the user material data; the data analysis module is connected with the data input module and the data processing module, and is used for analyzing the preprocessed user material data based on the sub-module selected by the user and / or the parameters set by the user to obtain an analysis result; and the result display module is connected with the data analysis module and is used for generating a visual chart and / or a data table based on the analysis result and displaying the visual chart and / or the data table to the user. According to the method, the dependence of breeding personnel on professional bioinformatics knowledge and programming skills can be reduced, key analysis steps in the whole breeding process are simplified, the data analysis efficiency and the integrated support capability of breeding decision are improved, and the application of SNP data in breeding practice is promoted.

The invention relates to the technical field of machine vision, in particular to a new energy field station multi-dimensional monitoring system based on machine vision, which comprises a path planning subsystem and a fault identification subsystem, and has the following functions: the path planning subsystem plans an unmanned aerial vehicle inspection path based on station dynamic demand driving by using a greedy-genetic fusion algorithm; and the fault identification subsystem is used for constructing a multi-modal input neural network, taking the visible light image, the infrared thermal imaging or the fusion of the visible light image and the infrared thermal imaging as input, and identifying a station fault by utilizing machine vision. The unmanned aerial vehicle routing inspection path is planned through the greedy-genetic fusion algorithm, the routing inspection efficiency and the routing inspection precision are improved compared with manual routing inspection, the effectiveness of path planning is guaranteed compared with traditional unmanned aerial vehicle routing inspection, and redundant routing inspection and endurance waste are avoided.

The invention provides an intelligent medical online service system and an online service method. The system comprises a service platform, terminal equipment, a community service station and a hospital service terminal, the service platform is connected with a community service station and a hospital service terminal; the terminal equipment is used for a user to register and access the service platform; the service platform comprises a registration and login module, a self-service module, a doctor-seeing appointment module, a doctor-seeing statistics module, a service appointment module, an evaluation module and an optimization module, a user accesses the platform through the terminal equipment, obtains services through different modules, completes inquiry and evaluation, gives preliminary auxiliary diagnosis suggestions through the platform, and optimizes the diagnosis through the terminal equipment. The user is helped to obtain some reference suggestions before appointment to see a doctor, so that the user can better understand the own illness state; the system can reasonably allocate resources of doctors and treatment equipment, ensures effective utilization of the resources, and improves the accessibility of treatment service; and the system performance and the user experience are improved through continuous optimization.

The present application relates to the field of wind power generation technology, and discloses a wind farm multi-dimensional intelligent diagnosis and fault early warning system based on data driving.The present application comprises a state perception quantization module, a state assumption generation module, a verification generation implementation module, a confidence degree synthesis calculation module and a diagnosis report generation module; the system generates state signals by identifying abnormalities and using dynamic threshold values to monitor wind turbine operation data in real time; generates fault root assumption based on diagnosis knowledge graph and historical cases; plans and executes multi-dimensional verification chain for each fault root assumption, obtains quantitative evidence from power curve, operation data, log records and other sources; fuses the evidence and calculates the reliability of each fault root assumption through a confidence degree synthesis algorithm, and outputs a high confidence degree diagnosis conclusion; finally, a structured report containing abnormal information, diagnosis results, visualized evidence and operation and maintenance suggestions is automatically generated; the present application improves the operation and maintenance efficiency and reliability of the wind farm.