Staff Attendance-HUAWEI CLOUD

Business Description
Business Challenges
Solution Architectures
Solution Advantages
Key Functions
Partners

Business Description

·Business Description

Based on HUAWEI CLOUD Face Recognition, this solution analyzes and compares staff and visitor faces. It replaces traditional attendance recording, not only improving enterprise attendance management efficiency, but also preventing cheating within the attendance system. In addition, the big data analysis capability of HUAWEI CLOUD enhances attendance management and job analysis capability

·Business Trend

In today’s Internet society, traditional card-punching can no longer effectively record staff attendance. Multiple drawbacks of card-punching, including the potential high cost of O&M, creates the need for a new solution. As facial recognition and personnel positioning technology become more popular, more and more Enterprises are adopting these advanced technologies to manage staff attendance

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Business Challenges

Staff Attendance

For enterprise managers, it is important to stay informed of employee attendance details. However, card-punching has many loopholes which allow some employees to slip through the net. Even if enterprises manage to obtain genuine attendance data, the O&M Cost is still too expensive, especially for large cross-regional enterprises
Customized Position Management

Generally, different positions require different attendance systems due to their differences. These may be differences in attendance time requirements, fixed or flexible work locations, and more. These differences make it difficult and costly to manage staff attendance effectively
Recognition Algorithms Requires Agile Update

Face Recognition supports basic staff attendance and customized requirements, but for more complex environments, Face Recognition results can be affected by changes in lighting, posture, and facial expressions. Characterized by features extraction and description, Face Recognition requires constant optimization of mathematical descriptions

Solution Architectures

Description

Face Attendance is a video surveillance platform that supports face capturing, storage, comparison and analysis. Edge nodes perform face detection and report surveillance video streams, while back-end cloud services complete storage, facial comparison and other functions

Highlights

Face Recognition: provides face comparison and analysis for staff attendance
Intelligent EdgeFabric (IEF): provides integrated edge and cloud synergetic services
Cost-efficient and scenario-adapted: supports all cameras complying with international standard protocol, adapts to a variety of staff attendance scenarios

Solution Advantages

Face Attendance Analysis

Uploads all facial images of staff members to the Face Recognition Library, captures real-time facial image when a person passes the camera, and compares with the existing faces in the library. If the comparison result matches, attendance information can be displayed
Insensible Real-time Attendance

Attendance is recorded without the need to punch cards. In addition, multiple people can simultaneously record their attendance
Multi-scenario Linkage

Reduces costs and improves efficiency by associating the face attendance system with scenarios such as entry gates and personnel trajectory tracking

Key Functions

Face Recognition Service

Face Recognition quickly detects faces in images, analyzes key facial points, obtains facial attributes, and implements precise face verification and retrieval. This service is perfect for customers working with identity verification, e-attendance, trace tracking, and customer attribute analysis
FunctionStage Service

FunctionStage is an event-driven function hosting and computing service, that compiles function code and configures running conditions without provisioning or managing servers, thus providing a scalable, maintenance-free, and reliable operation environment for functions
Intelligent Edge Platform Cloud Service

Intelligent EdgeFabric (IEF) provides integrated edge-cloud synergy services, and enables remote control, data processing, and analytics of edge computing resources