240 results about "Service worker" patented technology

The invention discloses a service scheduling system based on artificial intelligence, and belongs to the technical field of service scheduling. Comprising a data acquisition layer, an artificial intelligence engine layer, a scheduling execution layer, a monitoring management layer and a function module. The data acquisition layer acquires and preprocesses data related to insurance services; the artificial intelligence engine layer integrates natural language processing and machine learning technologies, and identifies and analyzes customer demands; the scheduling execution layer realizes access of customer service staff through a scheduling algorithm according to customer requirements and customer service staff information; and the monitoring management layer monitors and optimizes the service scheduling process. According to the invention, customer demands are intelligently analyzed, appropriate professional service personnel are accurately matched, and zero-delay docking between demands and services is realized; service personnel are intelligently dispatched, the waiting time of clients is greatly shortened, and the satisfaction degree is improved; tasks are deployed according to the insurance business rhythm, the potential of service personnel is mined, idleness is reduced, and the overall service capacity is improved.

The invention discloses an intelligent reply method and device based on natural language processing, equipment and a medium. The method comprises the steps that an initial knowledge graph corresponding to historical reply information is constructed through a knowledge graph construction rule, and a corresponding common reply link is generated; and judging whether the initial knowledge graph contains target reply information matched with the question information input by the user or not according to a natural language matching model, if so, obtaining the target reply information and outputting the target reply information, and if not, sending the question information to a service window so as to transfer service personnel to answer. According to the intelligent reply method, the historical reply information can be analyzed based on the natural language, the initial knowledge graph is constructed, and the common reply link corresponding to the initial knowledge graph is generated, so that a user can click and quickly obtain the reply content; the target reply information matched with the question information input by the user is accurately acquired based on the natural voice matching model and the initial knowledge graph, and the efficiency and accuracy of acquiring the reply information are improved.

The invention discloses an automatic order sending system with an intelligent matching function, and the system comprises a data collection module which is used for collecting customer information, order information, service personnel information, and environment information; the data acquisition module is connected with a plurality of data sources, and obtains customer information such as basic information, historical order data, consumption habits and preferences of customers through an interface protocol; order information such as the type, the amount, the time, the emergency degree and the special requirement of the order is acquired; and service personnel information such as skill level, working experience, working time arrangement and service area preference of the service personnel is obtained. According to the automatic order sending system with the intelligent matching function provided by the invention, the technical aspect of the automatic order sending system with the intelligent matching function is remarkably improved. Through multi-dimensional data acquisition, the system can obtain more comprehensive and accurate information, and a solid data basis is provided for intelligent matching.

The invention relates to the technical field of order allocation, in particular to a housekeeping platform order allocation system based on big data analysis, which comprises the following steps of: comprehensively analyzing housekeeping service request information, identifying service types, emergency degrees of time requirements and resource requirements, and integrating to form a preliminary service order list based on clear rules; the resource allocation is ensured to have pertinence from a demand end, and the matching probability of the order and the service personnel is optimized and calculated by updating the position and state data of the service personnel in real time and adopting the ant colony algorithm, so that the order matching is quickly adjusted and accurately allocated in a dynamic scene, the low-efficiency matching possibility is reduced, the resource utilization rate is improved, and the user experience is improved. The optimal service path is designed from the angles of cost and efficiency through the greedy algorithm, the service response time is ensured to be minimized, meanwhile, the operation cost is reduced, the economical efficiency and the performability of path planning are enhanced, and the distribution efficiency, the user satisfaction degree and the overall operation efficiency of the platform are improved.

The invention provides a data processing method and device, a model training method and device, equipment, a medium and a program, and relates to the technical field of computer application, in particular to artificial intelligence technologies such as knowledge maps and natural language process.The data processing method comprises the steps that current question data input by a current user to a service large model is obtained; determining a user role of the current user according to the current question data; wherein the user role comprises at least one of service personnel and service consulting personnel; and determining current answer data matched with the current question data according to the user role of the current user. According to the embodiment of the invention, the personalized answering service of the large service model to the user can be flexibly adjusted, so that the intelligence and service precision of the large service model are improved.

The invention discloses a hotel guest room service task intelligent scheduling system based on a cloud platform, and relates to the technical field of hotel service management, the intelligent scheduling system comprises a mobile client, a cloud server and a database system; and the mobile client is used for configuring a special mobile application program running on mobile equipment such as a smart phone or a tablet personal computer for hotel guest room service personnel. According to the intelligent hotel guest room service task scheduling system based on the cloud platform, service personnel can quickly respond to service requirements through real-time task pushing and mobile operation, the task waiting time is shortened, the moving speed of the service personnel is increased through positioning and navigation functions, the service response time is shortened, and the service efficiency is improved. Through detailed recording and picture and video uploading in the service process, service quality tracing and supervision are facilitated, weak links of the service process can be found and improved through data analysis, in addition, special requirements of guests are met through personalized service recommendation, and the satisfaction degree of the guests is improved.

The invention discloses an inference type dialogue response method and system based on a large model, and a storage medium, relates to the technical field of service consultation dialogue response, and solves the problems that the existing service consultation dialogue response is generally relatively simple, lacks an active inquiry strategy, only can be passively responded and cannot simulate a questioning mechanism of service personnel, and the service consultation dialogue response cannot be simulated. The technical problems of insufficient suggestion judgment accuracy and high misjudgment rate caused by difficulty in comprehensively and accurately collecting the conditions of the demanders in the prior art are solved. The method comprises the steps of obtaining voice data of a demander for service consultation; the method comprises the steps of performing feature extraction on voice input data to obtain condition feature data; inquiring the demander through a pre-trained condition inquiry model based on the condition characteristic data to obtain judgment data; matching from a historical consultation database based on the condition feature data and the judgment data to obtain a reasoning target; and feeding back a judgment suggestion to the demander based on the reasoning target, thereby solving the technical problem.

The invention discloses a big data-based government affair service window behavior analysis system and method, and relates to the technical field of government affair service analysis. A government affair service window behavior analysis system based on big data comprises a data acquisition module, an object identification module, a behavior analysis module, a service personnel evaluation module, a feature association module and a service optimization module. A correlation analysis model and a graph neural network technology are utilized to perform multi-dimensional analysis on service features of service personnel, group features of service objects and key features of window behaviors, dynamic correlation between service behaviors and feedback behaviors is accurately identified, scores of service efficiency, service attitude, user satisfaction and the like are generated, and the service efficiency, service attitude, user satisfaction and the like are improved. And the accuracy and depth of behavior analysis are obviously improved.

The invention provides a vehicle fault after-sales service method and device, a storage medium and electronic equipment, and is applied to the technical field of after-sales services, and the method comprises the steps: obtaining a fault after-sales request sent by diagnosis equipment; when the fault after-sales request is a tire pressure monitoring system fault diagnosis request, vehicle diagnosis data of a vehicle is obtained through diagnosis equipment, and a target after-sales service person is determined in all after-sales service persons through a recommendation algorithm; and pushing the fault after-sales request and the vehicle diagnosis data to a target after-sales service worker, so that the after-sales service worker uses the vehicle diagnosis data to remotely assist a customer in performing tire pressure detection system fault diagnosis on the vehicle. The fault after-sales request is sent through the diagnosis equipment, the after-sales service system quickly responds to the fault after-sales request, the response time of after-sales service is shortened, vehicle diagnosis data are provided at the first time through the diagnosis equipment, accurate data are provided for after-sales service personnel, the diagnosis work difficulty of the after-sales service personnel is reduced, and the diagnosis accuracy is improved.

The invention discloses a housekeeping platform order sending system based on the Internet technology, and relates to the technical field of housekeeping management systems, the housekeeping platform order sending system comprises a user side and a server side which are used for users and service personnel to place orders and receive orders, and a multi-dimensional portrayal module which is based on the relevant information of the service personnel and is used for sending the orders to the user side and the server side. And the multi-dimensional order sending module is used for processing and analyzing service requirements input by the user by adopting a natural language, extracting implicit requirements except for basic service types, time and places, and generating requirement feature vectors of the user, and is used for carrying out side portrait evaluation on service personnel and carrying out side portrait evaluation on the user according to housekeeping order information of the user as the same, and the multi-dimensional order sending module is used for processing and analyzing the service requirements input by the user by adopting a natural language, and can be used for extracting implicit requirements and generating requirement feature vectors of the user. Through the multi-dimensional portrait module, side portrait evaluation is carried out on service personnel from multiple aspects such as personality, capability, service evaluation, order completion degree, skill and education background, the problem of inaccurate matching caused by single index in a traditional order dispatching mode is avoided, and the order dispatching efficiency and the service quality are improved.

The invention provides a service optimization method and system based on data of old people, electronic equipment and a storage medium, and belongs to the field of services. The method comprises the following steps: acquiring basic information and demand information of old people and current service information provided by a community; using a K-means clustering algorithm to classify and label the old people based on the basic information and demand information of the old people; and optimizing the service according to the label identifier and the current service information provided by the community. By collecting and sorting the data of the old people and performing classification management, accurate data management is realized, so that accurate work guidance is provided for service personnel, and diversified requirements of the old people can be efficiently and accurately met.

The invention relates to the technical field of service management, in particular to a service personnel scheduling optimization method and system based on an intelligent terminal. The method comprises the following steps: collecting user behavior track data and service historical data through an intelligent terminal, extracting regional service request features, and dividing service space partitions; and service personnel data are obtained, a service capability portrait is constructed, and task requirements are accurately matched. Based on regional service features and service space partition, service personnel data are subjected to priority division, and efficient task allocation is ensured. And furthermore, in combination with the behavior track and the ability portrait of the service personnel, cross-regional collaborative scheduling is optimized, and the resource utilization rate is improved. According to the invention, customer demands and service personnel can be accurately matched, dynamic optimization scheduling is realized, the operation efficiency of the foot bath city is improved, the scheduling cost is reduced, and the customer satisfaction is improved.

A method for analysis of in-person attendant interactions according to an embodiment includes determining a location of a person within a monitored area based on sensor data generated by one or more sensors, determining a start queue time associated with a time at which the person is located at a start queue position within the monitored area, determining an end queue time associated with a time at which the person is located at an end queue position, recording interaction data of an interaction between the person and an attendant when the person is located at the end queue position, determining a wait time of the person in the queue based on the start queue time and the end queue time, determining an interaction time of the interaction based on the interaction data, and adjusting an attendant schedule for the monitored area to improve the wait time or the interaction time.

The invention relates to the technical field of artificial intelligence, and discloses a housekeeping service simulation training environment system and device based on AI. According to the system and the device, a housekeeping service basic data set is constructed by collecting user demands, service personnel skills, service scenes and historical feedback data in real time, the comprehensiveness and accuracy of data are ensured, in the data processing stage, key features are extracted, the user demand matching degree is calculated, a pure data set is generated, and the user experience is improved. The model training module utilizes an advanced machine learning algorithm to construct user demand prediction, service duration prediction and service efficiency index models, and the application of the models enables service personnel to more accurately meet diversified user demands, optimize service duration and improve service efficiency. The simulation environment module provides an interactive training platform for users and service personnel, the actual effect of skill training is enhanced, and the evaluation feedback module collects feedback information in real time to realize continuous monitoring and optimization of household service quality.

The utility model discloses a loading machine and an air conditioner condenser installation structure thereof. The air conditioner condenser installation structure comprises a condenser outer cover and a cover plate. The whole condenser outer cover is of a frame-shaped structure with an opening in only one face. A condensation core body is mounted in the condenser outer cover; the cover plate is movably installed on the opening face of the condenser outer cover, and when the whole machine works normally, the cover plate is in a closed state. When the condensation core body needs to be maintained, the cover plate is opened to wash the condensation core body; at least one draught fan is installed on the cover plate, and air is sucked by the draught fan through the surface of the condensation core body and then exhausted. According to the utility model, a user can open the outer cover of the condenser more conveniently and carry out maintenance work such as washing on the condensation core body, so that the probability that the condensation core body is blocked is greatly reduced, service personnel do not need to carry out on-site maintenance, and the working efficiency of the whole vehicle is improved.

The invention discloses an intelligent distribution system based on deep learning and dynamic resource scheduling, and relates to the technical field of resource scheduling. Comprising the steps of 1, creating an intelligent distribution system, 2, integrating an NLP engine through a user request analysis module, carrying out intention recognition and semantic analysis on a user request, extracting a service type and related parameters, carrying out triple positioning by fusing GPS / base station / Wi-Fi, and obtaining user position information, and 3, constructing a service personnel digital portrait library through a dynamic resource management module, 4, calculating the geographic proximity of candidate service personnel and the user position through an intelligent matching module by adopting a Manhattan distance formula, training an LSTM neural network based on historical service data by utilizing a service quality prediction model, and obtaining the current position and the moving speed of the service personnel through the LSTM neural network; and step 5, obtaining user service evaluation data through a feedback module, triggering a service quality prediction model to perform retraining, and outputting a service quality prediction value in the confidence interval, generating a real-time comprehensive priority according to the geographic proximity, the service quality prediction value and the service emergency degree, and recommending services according to the comprehensive priority, and step 5, obtaining user service evaluation data through the feedback module, and triggering the service quality prediction model to perform retraining. And updating the service personnel digital portrait library by adopting an incremental learning strategy.

The invention belongs to the field of data modeling analysis, and provides a tourism management optimization method and system based on tourist behavior analysis, and the method comprises the steps: periodically obtaining the feature data of each node in a scenic spot; obtaining edge feature data of tourists moving among different nodes in the scenic area; in each data acquisition period, performing convolution operation on the feature data of the node, performing weighted aggregation on the features of neighbor nodes by using the edge feature data, and fusing an aggregation result with the features of the current node to obtain convolution output; the convolution output of each collection period serves as time sequence data to be input into the long-short-term memory network; processing the time series data by using a long short-term memory network; predicting the tourist flow of each node in the future time step; and dynamically allocating service personnel and resources of each node in the future time step according to the tourist flow prediction result of each node in the future time step. The scenic spot management can be optimized, and the tourist experience can be improved.

The invention provides a household service supply and demand intelligent docking management method and system based on big data analysis. The method comprises the following steps: collecting original data; processing and splicing the family structure information and the historical order information to obtain a comprehensive feature vector, and inputting the comprehensive feature vector into a multi-layer perceptron to obtain a life cycle stage vector; projecting the life cycle stage vector to a space consistent with a preference vector to obtain a stage service mask; carrying out dimension-by-dimension multiplication operation on the stage service mask, the preference vector and the attention weight to obtain a preference fusion vector; constructing a first service capability vector for each service staff, and reconstructing the preference fusion vector and the service capability vector to obtain a second service capability vector; and calculating an average value to obtain a comprehensive score, sorting the comprehensive scores of all candidate service personnel according to a score descending order, and finally selecting the candidate service personnel with the highest comprehensive score and meeting a threshold condition as an order sending object.

A nursing worker housekeeping law enforcement instrument image processing system disclosed by the present invention comprises a law enforcement instrument terminal which comprises a central controller, a camera, a motor, an edge processor and a battery, the camera is connected with the central controller and is used for collecting an image of a hand position of a service worker, and the motor is used for driving the camera to move and adjusting an image collection angle; the edge processor is used for primarily processing images acquired by the camera, and the battery is connected with the central controller; and the cloud storage module is used for storing and processing the image which is acquired by the camera and is uploaded after primary processing. The invention further discloses an image processing method of the nursing worker housekeeping law enforcement instrument. Compared with the prior art, the technical problem that it is difficult to quickly screen image data collected by an existing law enforcement instrument to obtain effective information is solved.

The invention discloses a high-speed rail business travel service personnel scheduling method based on data analysis, and relates to the technical field of personnel scheduling management. Comprising the following steps: data acquisition and integration: acquiring high-speed rail station operation data, passenger information, service personnel information and environment data; streaming data processing and space-time alignment are carried out on the collected data, and a dynamic main data matrix is constructed; service demand prediction: extracting passenger multi-dimensional features from the dynamic main data matrix, and generating passenger multi-dimensional feature tags; and performing bimodal demand prediction based on the passenger multi-dimensional feature tag in combination with the environmental data to obtain an initial passenger service demand. According to the invention, through establishing the bimodal service demand prediction method, extracting the multi-dimensional features of the passengers, combining environment data and predicting the demands of the passengers, passive response is converted into active prediction, the response speed is accelerated, the waiting time of the passengers is reduced, and the service quality and efficiency are improved.

The invention belongs to the technical field of housekeeping service, and discloses a housekeeping service system which comprises a user system module, a service management module, an order scheduling module and an evaluation risk control module. The user system module supports hierarchical authentication and authority distribution of clients, service personnel and administrators, and generates portrait label drive matching based on behavior data of the clients and the service personnel; the service management module constructs a secondary classification system, and adopts an intelligent recommendation engine driven by a fusion collaborative filtering algorithm and a deep learning algorithm to carry out household service project recommendation; the order scheduling module optimizes a service process by using order period management and an intelligent matching engine; and the evaluation risk control module ensures the justice of service quality monitoring and a credit system through a two-way evaluation mechanism and abnormal evaluation detection. The household service supply and demand matching efficiency can be improved, the service standard is optimized, the credit system is perfected, and a decision basis of data support is provided for large-scale operation.

The invention discloses a call information processing method, which is applied to the technical field of data processing. The method comprises the following steps: acquiring audio information of a user and a service staff in a call process, wherein the audio information comprises first audio information of the user; generating voice feature change trend information of the user according to the voice feature information of the first audio information; target emotional feature information is determined according to the voice feature change trend information, and the target emotional feature information reflects the emotional state of the user in the call process; according to the target emotion feature information, an emotion response identifier of the user is generated, and the emotion response identifier is used for generating a service strategy for the user. The method can improve the accuracy of providing services for users.

A service information processing method based on intelligent interaction equipment comprises the following steps: service request input: inputting text information on a screen of an AI intelligent interaction terminal when a customer has a service demand; or the demand information is input through voice of the AI intelligent interaction terminal; information processing and screening: the AI intelligent interaction terminal sends the processed service request information to an AI server through a wireless communication network; the AI server screens and distributes the service requests to the service personnel through a deep learning algorithm and a preset distribution model according to the real-time working states of the service personnel; information transmission and response: the AI server sends the distributed service request information to the intelligent earphones of the corresponding service personnel; and after receiving the confirmation information, the AI intelligent interaction terminal informs the customer in a popup window display or voice broadcast mode. The problems that the efficiency is low and the cost is increased due to a traditional service request interaction mode in the service process of service personnel are solved.

The embodiment of the invention provides an information recommendation method and device, a storage medium and a program product. In the method, in a multi-modal recommendation model, according to service demand information and historical behavior information of a user, multi-modal demand understanding is carried out to obtain dual demand information of the user, according to multi-modal information of multiple service personnel, ability portraits of the service personnel are constructed, and the ability portraits comprise dominant skill information and recessive traits information; and according to the dual demand information and the ability portrait, performing dual demand matching between the user and the service personnel to obtain identification information of a target service personnel, and according to the identification information of the target service personnel, pushing detail information of the target service personnel to the user terminal equipment so as to recommend the target service personnel to the user. In this way, the service requirements of the user can be more accurately understood, the ability portraits of the service personnel can be more accurately constructed, the adaptation degree between the user and the service personnel is improved based on dual-requirement matching, and the service personnel are more accurately recommended to the user.

The present invention discloses a convenient car washing method and a convenient car washing system, including: a user initiates a car washing request through a user terminal and stores the vehicle key in an Internet of Things key box, and then the system automatically dispatches the service and generates a three-dimensional model to analyze the vehicle stains. The AI-based stain recognition module dynamically customizes the cleaning process to ensure that the most suitable cleaning solution is used for different stains. Before and after cleaning, the service personnel take images of the vehicle, and the central processing unit generates a corresponding three-dimensional model for comparison, intelligently analyzes the cleaning effect, automatically identifies and reports substandard areas, and guides remedial measures. The car washing system also involves a detailed design of an Internet of Things key box, including a display screen, a key storage grid, a wireless Bluetooth device, a power supply battery, etc., and additional sensors and alarm devices are provided to strengthen safety monitoring. The present invention dynamically adjusts the cleaning parameters through AI cleaning technology, ensures the effective treatment of various stains, reduces repetitive work, and improves the efficiency of cleaning.

The invention discloses a building service personnel scheduling method, and relates to the technical field of building service personnel scheduling, and the method comprises the following steps: collecting building data through collection equipment, designing a smart bracelet, collecting building service personnel data, obtaining the completion degree of corresponding building service according to each piece of building service data, and obtaining the completion degree of the building service through a neural network algorithm. Building a building service progress monitoring model, obtaining a building service personnel scheduling result according to the building service personnel data in combination with the building service progress monitoring model, and building a building service personnel scheduling model by using a random forest algorithm; according to the method, the smart bracelet coding technology, the smart bracelet acquisition equipment technology and the big data processing technology are closely combined with the modern information technology, real-time and comprehensive monitoring of the building service progress is achieved, and the intelligent degree in the scheduling process of the building service personnel is remarkably enhanced.

The invention discloses a catering store customer behavior recognition and intelligent service response system, which belongs to the technical field of artificial intelligence and computer vision and comprises a data acquisition module, a data preprocessing module, a target detection module, a posture estimation module, a behavior feature calculation module, a keyword feature recognition module and an initial service demand triggering module. And a final service demand triggering module and a service response module. According to camera behavior recognition or / and voice keyword recognition, after it is recognized that the user has the service requirement, the initial service requirement is triggered, the judgment time is set, and within the judgment time, recognition is conducted again according to camera behaviors or / and voice keywords, so that the service requirement of the user is met. After the fact that the user still has the service demand is recognized, the final service demand is triggered and responded, the situation that the user service demand is self-solved is screened out through a mechanism of initial triggering-secondary verification-screening decision making, the probability of invalid turn-back occurrence of service personnel is reduced, and waste of service resources is avoided.

The invention discloses an active off-line calibration system and method for a vehicle-mounted controller and the vehicle-mounted controller. The method comprises the following steps: generating an off-line calibration file of the vehicle-mounted controller through a calibration tool and uploading the off-line calibration file to a vehicle networking service platform; after the controller is powered on, a request instruction is sent to the Internet of Vehicles service platform through the T-BOX; the car networking service platform responds to the T-BOX, wherein the response comprises a check code for calibrating the file, an FTP address for storing the file, an account number and a password; after receiving the reply, the T-BOX judges whether the calibration file needs to be updated or not, if not, subsequent operation is not carried out, and if yes, FTP is connected to download the calibration file; after the calibration file is downloaded, calibration data are transmitted to the vehicle-mounted controller, the vehicle-mounted controller updates the calibration data and resets the calibration data, and after resetting, the vehicle-mounted controller reads the latest updated calibration data to work. According to the invention, unmanned operation is realized, dependence on service personnel is reduced, labor cost is saved, and the method is suitable for batch processing of vehicles in the market.

The present invention discloses a catering service data processing system and method based on big data, comprising: a public information collection module, a restaurant information database, a restaurant image scanning module, a motion track analysis module, a public data processing module and a dining information feedback module, wherein the seat distribution information of the restaurant and the walking stride data of the service personnel are collected to the restaurant information database through the public information collection module, the position of the service personnel and the vacant seats are monitored in real time through the restaurant image scanning module, and image data are obtained, and the service personnel's dish serving route is predicted through the motion track analysis module, and the stride parameter is added in the process of calculating the dish serving route, and the service personnel who currently serves the fastest dishes are analyzed and selected, and arranged to serve the dishes, and the service personnel's dish serving information is fed back to the customer in time through the dining information feedback module, thereby speeding up the dish serving speed, improving the customer's dining comfort, and realizing the public information exchange between the kitchen, service personnel and customers.

The utility model discloses a voice intercom device, voice intercom device includes: voice emission module, voice receiving module, voice call button 110, MCU control module, MCU control module controls voice emission module to send call signal and user's voice signal, display screen module is used to show digit, first plug module, one end of first plug module is connected to computer interface, and the other end of first plug module is used to power supply voice emission module, voice receiving module, MCU control module and display screen module. The utility model has the beneficial effect that: after user presses voice call button 110, user communicates with the real -time voice of server through voice intercom device. User can obtain seat number or room number information from display screen module when communicating, thereby directly informs service personnel of server, avoids server service personnel after receiving multiple call signals simultaneously and can not confirm the position of user, improves the communication efficiency.