69 results about "Staffing" patented technology

The invention belongs to the technical field of product inventory management, and discloses an e-commerce product inventory management method based on machine vision, which realizes a full-automatic process of product information from acquisition, recognition to statistics by means of a machine vision technology, acquires images in real time from multiple angles by a high-definition industrial camera, inputs the images into a CNN model to extract features after preprocessing, and realizes product inventory management. Through accurate identification classification and quantity statistics, manual intervention of inventory and data entry is not needed; through the automatic inventory management process, the manpower cost expenditure of manual checking, data processing and the like is greatly reduced, and the personnel employment and training cost is reduced. And on the other hand, historical data is deeply mined by using algorithms such as time sequence analysis, the sales trend and the inventory demand are accurately predicted, the replenishment strategy is optimized, capital and storage space occupation caused by inventory overstock is avoided, meanwhile, order loss caused by stockout is prevented, and in addition, a distributed database storage technology ensures data reliability, and the efficiency is improved. And extra cost caused by data errors is reduced.

Systems adapted to auto-approve pending requests of contact center agents based in a dynamic environment and methods, and non-transitory computer readable media, include monitoring operational parameters affecting staffing needs and automatic approval criteria; establishing that a new staffing situation is present based on the monitored operational parameters, automatic approval criteria, or both; determining that the new staffing situation meets a current staffing threshold; identifying a pending schedule change request submitted by a contact center agent; comparing the identified pending schedule change request with the automatic approval criteria; updating a schedule of the contact center agent based on the approved identified pending schedule change request or approved generated recommendation; and sending a schedule notification to the contact center agent.

A method, system, and article of manufacture for modifying a queue assignment for a contact center are provided. At least one computing device determines, by solving for constraints, at least one staffing change for at least one of the first queue or the second queue, using as inputs (a) first time-based service metrics, (b) second time-based service metrics, (c) data describing eligible staffing changes, and (d) at least one predetermined constraint. The at least one staffing change is a modification to the queue assignment of a subset of the computing device instances that is predicted to improve net staffing relating to service targets selected from (a) an average speed of answer (ASA) specifying an average time for one of the computing device instances to initiate handling of a particular task after the particular task has been assigned to the relevant queue and (b) a service level specifying a percentage of tasks for which handling is initiated within a specified time frame after the tasks are assigned to the queue. The at least one staffing change can be implemented by modifying the queue assignment of the subset of the computing device instances.

A method for incentivizing contact center agents with scheduling perks that includes: receiving a workload forecast and staffing plan for a current shift; receiving a service level target; receiving types of scheduling perks; performing a selection routine for determining a select scheduling perk for offering to a select agent; and sending a scheduling perk offer via electronic communication to the select agent. The selection routine may include: selecting a proposed scheduling perks and a proposed agent; modifying the staffing plan to create a proposed staffing plan that reflects the proposed scheduling perk; predicting a proposed forecasted target adherence using the modified staffing plan; determining whether the proposed forecasted target adherence satisfies a threshold defined by an acceptable forecasted target adherence and, if so, deeming the proposed scheduling perk as select scheduling perk and proposed agent as select agent.

The invention provides an operation nursing personnel post matching system and method, a storage medium and electronic equipment, and the system comprises a personnel management module, a capability evaluation module, an operation management module and a post matching module, and the personnel management module is used for constructing a nursing resource library; the ability evaluation module is used for constructing an ability cultivation path for the nursing personnel in the nursing resource library and generating operation ability evaluation results of all the nursing personnel in real time according to the current ability cultivation condition in the ability cultivation path; the operation management module is used for performing operation scheduling on to-be-scheduled operations according to the operation application instruction so as to generate operation scheduling information of each operation room; and the personnel and post matching module is used for matching the operation scheduling information with the operation ability evaluation result to obtain an operation nursing personnel configuration result of each operation room. According to the method, the ability cultivation path is established to clarify the cultivation process, and the operation scheduling information is matched with the operation ability evaluation result, so that the scheduling efficiency of operation nursing personnel is improved.

A computer-implemented method for optimizing a number of sessions of a multi-session meeting based on agents skill requirement during a time-range of scheduled work-shifts, in a cloud-based contact center. The computer-implemented method includes receiving a time-range of scheduled work-shifts, a maximum number of agents in each session of the multi-session meeting, one or more skill-types and a buffer-level for each skill-type, operating a schedule manager MS to provide scheduled work-shifts of agents in the time-range of scheduled work-shifts that include open slots and net staffing data of each skill-type, determining a total number of agents, calculating a lower-bound of sessions and an upper-bound of sessions, iteratively determining a number of sessions of the multi-session meeting and allocating the total number of agents to the determined number of sessions of the multi-session meeting until an optimal number of sessions of the multi-session meeting is reached.

The invention discloses an intelligent medical management system based on artificial intelligence, and relates to the field of data processing, and the system comprises a sensing module which is used for sensing the position information of medical personnel in a hospital and an emergency transportation sickbed in real time; the labeling module is used for labeling available operating rooms on the in-hospital path three-dimensional topology in real time; by sensing the positions of medical workers and emergency transport sickbeds in real time, marking available operating rooms on a three-dimensional topology, intelligently deciding medical worker configuration and sickbed moving paths, visualizing the paths and directions through a public area display, and playing early warning audio to prompt evacuation, the first-aid efficiency is effectively improved, precious time is won for patients, and the medical workers and the emergency transport sickbeds are protected. And the first-aid channel is ensured to be smooth, so that the in-hospital multi-source resource scheduling arrangement of the medical first-aid scene is more scientific, reasonable and orderly.

A system for generating alternative shifts for contact center agent scheduling according to an embodiment includes a system that receives a staffing requirement forecast indicative of a number of agents required to handle a workload forecast. Agent data is received for a plurality of agents. The system receives a service level override value and performs column generation to identify shifts for the agents based on the staffing requirement forecast, agent working rules, and work plan constraints. A subset of the shifts is selected to generate an optimized agent shift schedule. A request to replace an individual shift of the optimized shift schedule with an alternative shift is received. In response, the system identifies the alternative shift from the plurality of shifts based on the service level override value. The individual shift is replaced with the identified alternative shift on the optimized shift schedule.

A dynamic AI-based resource planning system and calculator for optimizing fieldwork in renewable energy construction projects, the system comprising: (a) a data collection module configured to collect real-time and historical data from sources such as worker attendance records, weather data, equipment usage logs and project management software; b) a predictive analytics module configured to process the data using machine learning algorithms to predict work needs, potential project delays, and task prioritization; (c) a resource allocation module configured to dynamically allocate on-site workers to tasks based on forecast results, worker availability, skill levels and project schedules; (d) an interactive planning interface suitable for the visualisation, modification and simulation of personnel plans and project activities in real time; (e) a Smart Operational Resource Dashboard (SORD) configured to monitor and display key performance indicators, detect anomalies, and issue automatic alerts; and f) a reporting module configured to generate work, productivity and compliance reports, The system continuously adjusts labor deployment in response to changing on-site conditions to improve work efficiency and project results.

A system is provided.SOLUTION: A generative AI model means for analyzing the optimal matching between the crew and the shops by using the integrated database, a means for generating an optimal manpower allocation scheme based on the analysis result, a means for notifying the staff of the manpower allocation scheme based on the characteristics of the crew and the characteristics of the shops, and a means for collecting feedback information on the manpower allocation scheme; Means for updating the generative AI model to reflect the collected feedback in a next placement proposal.SELECTED DRAWING: Figure 1

Described herein are systems and methods for determining medical staffing requirements for administering OIT to patients. Specifically, the methods and systems disclosed herein can determine the time required by a medical staff at a given treatment location to devote to administering OIT to patients as well as the number of patients undergoing OIT over a selected time period. The methods and systems disclosed herein can further provide the time required by providers and clinical staff at a given treatment location to devote to administering OIT to patients.

The invention provides a post recommendation method and device, a storage medium and a product, and relates to the technical field of software, and the method comprises the steps: receiving a post recommendation request message sent by a client; acquiring employee data of the to-be-recommended employees from a database based on the employee identifiers; determining an adaptation index of at least one candidate post based on the employee data and the post demand data; generating matching scores of the candidate posts based on the adaptation indexes of the candidate posts; determining a target post from the at least one candidate post based on the matching score of each candidate post; and sending a post recommendation response message to the client. According to the method, on the premise of not additionally increasing the data acquisition cost and being compatible with the existing human resource system architecture of the enterprise, efficient adaptive recommendation of flexible employment posts and employees in the enterprise is realized, and the recommendation accuracy and employment configuration efficiency are remarkably improved.

A method for incentivizing contact center agents with scheduling perks that includes: receiving a workload forecast and staffing plan for a current shift; receiving a service level target; receiving types of scheduling perks; performing a selection routine for determining a select scheduling perk for offering to a select agent; and sending a scheduling perk offer via electronic communication to the select agent. The selection routine may include: selecting a proposed scheduling perks and a proposed agent; modifying the staffing plan to create a proposed staffing plan that reflects the proposed scheduling perk; predicting a proposed forecasted target adherence using the modified staffing plan; determining whether the proposed forecasted target adherence satisfies a threshold defined by an acceptable forecasted target adherence and, if so, deeming the proposed scheduling perk as select scheduling perk and proposed agent as select agent.

A system is disclosed that utilizes multiple workload estimation models defined by reflecting the work environment at various points in time to calculate workloads according to each estimation method for an entire period, and derives staffing forecast results by comprehensively reflecting operational personnel forecasts through regression analysis based on this. The system is characterized by comprising a work management server that generates work-related data, a data acquisition unit that acquires said work-related data through a communication network, and a data processing unit that calculates said workloads through pre-set individual workload estimation methods, generates said regression analysis models for said workloads, generates said staffing forecast models that calculate said staffing forecasts based on said regression analysis models, and integrates said staffing forecasts to generate a final staffing forecast value at a specific point in time.

A system is provided.SOLUTION: A system comprising: means for collecting information on skills and career vision of employees; database means for storing and analyzing the information; generation and AI means for proposing optimum staffing based on the analyzed result; means for periodically performing condition check of employees and analyzing the result; and means for providing feedback based on the result of the condition check.SELECTED DRAWING: Figure 1

We provide the system. [Solution] A data analysis means for collecting and preprocessing surveys, emails, chats, and meeting records, A personality trait evaluation means that uses a generative AI model to perform a process that objectively evaluates the user's personality traits and skills, A personnel placement recommendation tool that calculates the optimal team structure and staffing based on evaluation results and creates a specific placement plan, A feedback analysis tool that analyzes user-provided feedback to evaluate actual performance and team harmony, A database update mechanism that updates personality profiles and skill maps based on feedback and newly collected data, A system that includes this.

A computerized-method for determining critical-time-slots and scheduling focus-activity therefore during WFM scheduling. The computerized-method includes while generating a schedule: a) for each time-slot: (i) retrieving forecast-data of forecasted interaction volumes of traditional-interactions and forecasted active-counts for digital-interactions; (ii) retrieving historic-data of adherence and calculating predicted out-of-adherence percentage for each agent; (iii) determining the time-slot as one of: traditional-interactions-time; and digital-interactions-time, based on the forecasted interaction volumes of traditional-interactions and the forecasted active-counts for digital-interactions; b) for each agent, for each time-slot that has been determined as traditional-interactions-time determining critical-traditional-interactions-time and for each time-slot that has been determined as digital-interactions-time, determining critical-digital-interactions-time based on the retrieved forecasted-data, AHT and maximum staffing; and c) for each agent having in-adherence above adherence-threshold, scheduling focus-activity for digital skills as the activity-type during time-slots that were determined as critical-digital-interactions-time, and focus-activity for traditional skills as the activity-type during the time-slots that were determined as critical-traditional-interactions-time.

The system according to the embodiment aims to automate the process of evaluating the validity of estimates and enable flexible staffing. [Solution] A system according to an embodiment includes a reception unit, a collection unit, an evaluation unit, and a provision unit. The reception unit receives input of quotation data. The collection unit analyzes the quotation data received by the reception unit and collects data on similar past cases or market prices. The evaluation unit evaluates the validity of the quotation based on the data collected by the collection unit. The provision unit provides the evaluation results obtained by the evaluation unit.

A system and method of automated case costing for surgical procedures can include the operations of tracking a real time location of a plurality of staff within a surgery center using wearable tracking devices that monitor the real time location of staff members among the plurality of staff within the surgery center to provide tracked time information, and allocating staffing costs based on actual time spent in an operating room and in other areas of the surgery center including one or more among a waiting room, a Pre-Op area, a recovery area, and a post-recovery area using one or more processors. Such a system can use and integrate with human resources clocking and surgery scheduling software modules.

The system according to the embodiment aims to predict future demand and propose appropriate staffing arrangements. [Solution] A system according to an embodiment includes a collection unit, an analysis unit, a prediction unit, and a proposal unit. The collection unit collects past event data and shift data. The analysis unit analyzes the data collected by the collection unit. The prediction unit predicts future demand based on the analysis results obtained by the analysis unit. The proposal unit proposes staffing arrangements based on the demand predicted by the prediction unit.

A system and methods for optimizing labor scheduling in retail environments by incorporating shrink factors alongside traditional considerations are provided. A machine learning model (MLM) receives traffic data, hourly labor data, overall shrink data, and proven shrink incidents as inputs. The MLM learns the labor-shrink causality across stores, connecting staffing levels to shrink impact. The MLM outputs a recommended labor scheduling plan for both assisted and self-checkout lanes, optimized for overall store margins rather than just labor costs. This approach balances labor efficiency with shrink prevention, potentially improving store profitability. In an embodiment, an application programming interface (API) is provided for consuming recommendations from the MLM as a service to integrate insights into business intelligence dashboards, providing a comprehensive solution for retail labor management.

A computer-implemented system and method are provided. The system and method analyze GIS data and transform the analyzed GIS data based on one or more additional weighted variables into transformed data predictive of optimal locations for one or more enrollers to service and predictive of optimal staffing of enrollments for reducing or minimizing costs while at the same time increasing or maximizing awareness and appropriate utilization of insurance products to thereby boost employee enrollment in various products and / or particular products.

This invention provides a method and system for evaluating organizational structure and staffing based on a large language model. The method includes: collecting industry standard data and evaluation reference data related to organizational structure and staffing; constructing scoring rules for multiple preset dimensions based on the industry standard data and evaluation reference data; obtaining a level judgment threshold for each preset dimension; constructing an evaluation standard knowledge base based on the scoring rules and the level judgment thresholds; collecting data from multiple set data sources to obtain multi-source data of the target organization; using a large language model to perform semantic extraction on the multi-source data to obtain the organizational entities within the target organization and the relationships between them, as well as the operational feedback data of the target organization; and using the evaluation standard database to evaluate the operational feedback data to obtain the evaluation result of the organizational structure and staffing system of the target organization. The technical solution of this invention can improve the accuracy and efficiency of organizational structure and staffing evaluation.

The application discloses a personnel configuration information security storage method and system based on a blockchain, relates to the technical field of blockchain storage, and comprises the following steps: constructing a personnel configuration graph, using an encrypted public key of an employee, and storing the personnel configuration graph into a personnel configuration blockchain; dividing the employee into K employee clustering clusters; setting a minimum data access permission set for each employee clustering cluster according to a historical access data subset of the employee contained in the employee clustering cluster; searching for an employee clustering cluster in which an inquiring employee is located as a target clustering cluster; receiving a knowledge graph query statement input by the inquiring employee; obtaining corresponding query data from the personnel configuration blockchain; and using a decryption private key corresponding to the inquiring employee to decrypt the query data.

A tobacco customer service staff demand prediction method comprises the following steps that X groups of county (or county-level city and district) data are collected, and the X groups of county (or county-level city and district) data comprise the number of existing customer service staff compilation, the planned cigarette sales volume, the territorial area, the number of service persons, the number of terminal customers, the terminal category structure, the customer grade structure, the urban and rural power grid customer structure, the customer volume structure and the retailer dispersity; the existing customer service staff compilation number is taken as a dependent variable, other data is taken as an independent variable, and correlation analysis is carried out by using SPSS. Obtaining n associated variables, and determining X groups of customer service coefficients H; and clustering the H by using a K-means clustering analysis method. And on the basis of an industry quota staff standard, measuring and calculating the quota staff standard of each type of customer service staff by using an expert scoring method in combination with a clustering result, and predicting the customer service staff required by each group. The scientificity and reliability of an analysis result are improved, the reliability and scientificity of decision making are improved, and finally the more accurate number of customer service staff is obtained.

A system is disclosed that utilizes multiple workload estimation models defined by reflecting the work environment at various points in time to calculate workloads according to each estimation method for an entire period, and derives staffing forecast results by comprehensively reflecting operational personnel forecasts through regression analysis based on this. The system is characterized by comprising a work management server that generates work-related data, a data acquisition unit that acquires said work-related data through a communication network, and a data processing unit that calculates said workloads through pre-set individual workload estimation methods, generates said regression analysis models for said workloads, generates said staffing forecast models that calculate said staffing forecasts based on said regression analysis models, and integrates said staffing forecasts to generate a final staffing forecast value at a specific point in time.

The application discloses a kind of medical skill examination intelligent reservation and resource scheduling system based on rule engine, it is related to medical information technology field, including data acquisition module, rule engine module, intelligent reservation module, the dynamic analysis and matching of medical business rules are realized by introducing rule engine module, and resource scheduling strategy and reservation priority sequence are generated;Intelligent reservation module provides personalized recommendation using reservation priority sequence and rehearses detection conflict, realizes zero conflict reservation;Resource scheduling module optimizes equipment, clinic and personnel configuration according to strategy in real time, improves resource utilization;Process control module carries out closed loop tracking and synchronization to reservation and scheduling result.Each module cooperates and operates, it is jointly relieved that traditional medical skill examination is uneven, reservation process rigid, multiple system coordination difficult and the problem that rule adaptation is not flexible, finally reach shorten patient waiting time, reduce hospital operation cost, improve the effect of overall efficiency and intelligent level of medical service.

Disclosed is a platform that provides temporary staff along with administrative infrastructure to employers who have temporary staffing needs. Administrative issues are monitored via dynamically generated geofences and mobile devices (mobile phones) carried by worker-users. The geofences serve as time clock and behavioral monitor zone.

An object of a system according to an embodiment is to appropriately grasp desires and needs of employees and propose an optimal career plan and an appropriate arrangement of materials.SOLUTION: A system includes a collection unit, an analysis unit, an evaluation unit, and a proposal unit. The collection unit collects requests and needs of employees. The analysis unit analyzes the information collected by the collection unit and proposes a career plan. The evaluation part analyzes the resume of the applicant and evaluates the aptitude and skill. The proposal unit proposes an appropriate material arrangement based on the information obtained by the evaluation unit.SELECTED DRAWING: Figure 1

The invention provides a computer-implemented method and system for developing optimized work schedules in workplace environments. Employees are classified into performance categories based on metrics such as sales figures, customer feedback, task completion rates, and adherence to schedules, using an unbiased AI system that excludes factors like gender, race, and age. Availability data, including shift preferences and real-time location, is integrated with anticipated sales targets to determine an optimal staffing mix. Work schedules are generated in compliance with labor laws and workplace policies, ensuring operational efficiency while preventing overtime. Employees can access real-time rankings and performance evaluations, fostering transparency and accountability. The system also integrates with payroll to ensure fair task allocation and evaluates anomalies in sales and profitability, updating policies and schedules to enhance outcomes.