Does the system require an internet connection to operate?

No. SGI-ST-1.0 adopts a fully offline local deployment方案. All algorithms run on the edge AI box without relying on the cloud, ensuring data privacy and security while achieving high real-time processing performance.

Which sports testing items are currently supported?

The current version primarily supports automatic recognition and counting for sit-ups and pull-ups. The system has good scalability and can be extended to include other items such as jump rope and medicine ball throws upon request.

How is the accuracy and fairness of counting ensured?

The system is based on Machine Vision and AI Vision technologies. Through high-precision motion capture and logical judgment algorithms, it automatically identifies fouls (such as借力 or incomplete movements) and provides synchronized video evidence to ensure objective and fair test results.

SGI-ST-1.0 | AI Vision Sports Testing Solution

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SGI-ST-1.0 is an AI vision automation solution designed for campus sports testing scenarios, based on Edge AI and Machine Vision technologies, featuring motion recognition, automatic counting, and compliance assessment capabilities.

Product Overview

SGI-ST-1.0 is specifically designed for middle school students' physical health testing, integrating high-definition video capture with high-performance edge computing devices. Through advanced AI Vision algorithms, the system can analyze students'运动姿态 in real-time, achieving automated assessment for items such as sit-ups and pull-ups.

This solution abandons traditional manual counting methods. By completing data processing and result output through a localized inference engine, it not only significantly improves testing efficiency but also achieves traceability of results through synchronized video recording, making it an ideal choice for educational informatization and smart campus construction.

Key Features

Edge AI local inference with millisecond-level response, no cloud dependency
High-precision motion recognition and intelligent counting to reduce human error
Automatic scoring and compliance assessment, supporting detection of various foul behaviors
Synchronized storage of recognition data and test videos for easy review
Fully offline operation mode to protect student data privacy and security
Modular design supporting flexible access to various standard cameras

Typical Applications

Standardized sports testing in middle schools and universities
Automated assessment at physical health monitoring stations (sit-ups / pull-ups)
Daily sports training motion evaluation and correction
Regional physical fitness data collection and big data analysis platforms

Technical Specifications

Video Resolution	1080P @ 30fps (HD quality)
Encoding Format	H.264 / H.265 (Efficient compression)
Processing Platform	Dedicated Edge AI Box
Operating System	Linux Embedded System
Interface Type	USB / Ethernet
Data Storage	Local large-capacity storage, supports loop recording
Deployment Method	Plug-and-play, supports rapid site setup

Algorithm Function Modules

Pull-up Recognition Module

Real-time motion detection and precise counting
Standard motion specification recognition and automatic scoring
Intelligent foul recognition: including stepping on the ground for leverage, chin not clearing the bar, arms not fully extended, etc.
Configurable detection parameters to adapt to standards for different age groups

Sit-up Recognition Module

Fully automatic counting and up/down position monitoring
Intelligent motion amplitude judgment to prevent invalid counting
Foul behavior detection: such as improper hand placement behind the head, feet lifting off the ground, etc.
Sensitivity adjustment function to adapt to different site lighting conditions

Frequently Asked Questions

Q1: Does the system need to operate in a networked environment?
A: No. SGI-ST-1.0 adopts a fully offline deployment. All Machine Vision algorithms run on local edge devices, ensuring stable operation even in gymnasiums or playgrounds without network connectivity.

Q2: What if students dispute the counting results?
A: The system features "synchronized motion and video evidence." Each count is associated with the corresponding video segment. Teachers or examiners can replay the footage for manual review at any time to ensure the fairness and impartiality of the exam.

Q3: Can this solution integrate with the school's existing academic management system?
A: Yes. The system provides standard data output interfaces, allowing convenient integration with various campus management platforms or education bureau data centers to achieve automatic uploading and archiving of physical test data.

Contact Us

If you need a demo, quotation support, or wish to discuss customized AI vision solutions for campus sports scenarios, please feel free to contact us directly.

Phone: +86 18668087462 (WeChat available)

Email: contact@3dsensing.cn