A big data-based intelligent office management system and method

By collecting dynamic and static parameters of the rest area, a control and optimization model is established to generate resource adjustment coefficients. This allows for dynamic adjustment of capacity and personnel management, solving the problem of inflexible personnel adjustment in rest area management and improving resource utilization efficiency and employee experience.

CN119578727BActive Publication Date: 2026-06-26SHENZHEN NUOFEI TECH DEV CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
SHENZHEN NUOFEI TECH DEV CO LTD
Filing Date
2023-09-05
Publication Date
2026-06-26

AI Technical Summary

Technical Problem

The existing rest area management system cannot dynamically adjust the number of people resting according to actual usage, resulting in overcrowding during peak hours and waste of resources during off-peak hours, affecting employees' rest experience and resource utilization efficiency.

Method used

By collecting dynamic and static parameters of the rest area, a control and optimization model is established, resource adjustment coefficients are generated, load levels are analyzed, and buffer or control signals are generated to dynamically adjust the capacity and personnel management, thereby optimizing the operation of the rest area.

Benefits of technology

It has improved the efficiency of rest area resource utilization and environmental improvement, provided a basis for management and decision-making, enhanced the comfort and health of the rest area, and increased employee work enthusiasm and productivity.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application discloses a kind of wisdom office management system and method based on big data, specifically related to wisdom office field, is by obtaining the standard accommodation capacity when rest area design and collecting dynamic parameters and static parameters when rest area runs, establishes control optimization model and obtains resource adjustment coefficient, uses resource adjustment coefficient to analyze running load degree, compares with resource adjustment threshold to generate buffer signal or control signal, combines resource adjustment coefficient with standard accommodation capacity to obtain dynamic accommodation capacity, replaces standard accommodation capacity, calculates the ratio of the number of people in rest area and dynamic accommodation capacity to obtain trigger value, compares with trigger threshold, judges whether to obtain the guidance index of personnel, controls and manages personnel newly entering rest area, optimizes operation, improves resource utilization efficiency and improves environment, provides strong guidance and decision basis for the management and promotion of rest area.
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