大溈（國際）人工智能科技有限公司

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Physical Test Station

AI Height, Weight & BMI Measurement

Leveraging camera-based non-sensing facial recognition, it calculates height via the distance from the top of the head to the sole of the foot (accuracy: ±0.5cm) and weight through volume reconstruction algorithms, instantly computing dynamic BMI values.
Breaking free from traditional formula limitations, it completes detection in just 5 seconds—no need to remove shoes or change clothes—with errors reduced by 37% compared to conventional methods. All data is encrypted locally, complying with international privacy standards, making it ideal for rapid health screening in public spaces. Supports simultaneous measurement for 3 people.

AI long jump

AI long jump uses computer vision algorithms to calculate the take-off area, take-off line and scale lines on the long jump mat, detects the take-off area and the human body to match the long jumper, and finally accurately calculates the long jump results through the human body motion trajectory curve and foot points. The AI technology used in the Winter Olympics ski jumping platform is used to digitize the long jump and analyze its movements, and the same set of software and hardware can be used to digitize multiple sports.

  • Practice mode gesture switching project, test mode DingTalk end switching project
  • Intelligent judgment of fouls such as stepping on the line and going out of bounds, and accurate distance measurement in centimeters
  • Generate motion slices instantly to assist in accurate classroom teaching
  • Sports video playback, support projection screen, frame-by-frame replay and tracing

AI Lung Capacity Measurement

Equipped with high-precision airflow sensors and facial recognition technology, users only need to align with the camera for identity verification before completing the test with a simple breath blow. The system instantly analyzes airflow speed, duration, and total air volume, automatically filtering invalid breath data. It intelligently calibrates lung capacity values based on parameters such as age, gender, height, and weight (accuracy: ±2%), with results displayed on the screen within 3 seconds.
All data is encrypted to comply with medical privacy standards, making it ideal for rapid testing in schools, gyms, and other venues. The error rate is 45% lower than that of traditional methods, and simultaneous testing for multiple users is supported.

AI Sit&Reach

Fully automated measurement is achieved through cameras and laser distance measurement modules. After users complete facial recognition, the system instantly detects hip joint angle (accuracy: ±1°) and knee extension, providing voice guidance to adjust to a standard sitting posture. When pushing the measurement board, a high-sensitivity sensor (accuracy: ±0.3cm) tracks the maximum displacement point and automatically filters invalid movements such as waist compensation.
No manual intervention is required throughout the process. Test data is automatically encrypted and stored, complying with physical fitness test standards. Ideal for rapid flexibility assessment in schools, gyms, and other venues.

AI Sit-ups

Based on convolutional neural networks, real-time detection of key points on the human body and intelligent video analysis are used to achieve intelligent timing counting and standardized exercise evaluation of three people doing sit-ups simultaneously under one camera.

  • Smart timer counting to support 3 people doing sit-ups at the same time
  • Intelligent error correction and foul voice prompts
  • Real-time data display on the big screen, sports data visualization
  • Sports video playback, projection support, frame-by-frame analysis and review, personalized analysis and teaching

AI Pull-ups

Combining neural network analysis and deep learning algorithms for estimating human skeletons, the system intelligently captures human movements based on video to achieve intelligent timing and counting, intelligent error correction prompts, and annotated evaluation of three people doing pull-ups simultaneously under one camera. Help students evaluate their physical fitness through test scenarios and daily training scenarios. It is more intelligent, objective, and systematically recorded to evaluate students’ pull-up exercise tests.

  • Touchless facial recognition, automatic matching and uploading of identity information
  • Intelligent timing and counting, intelligent identification of foul actions, and scientific evaluation of whether the actions meet the standards
  • Big screen visual data real-time feedback, foul reminders and other interactive
  • Practice/physical test dual mode, suitable for various campus scenarios
  • Sports video playback, support projection, frame-by-frame replay and tracing, assisting in precise teaching

AI Hand Grip Strength Test

Integrating facial recognition and high-precision pressure sensing technology, users complete identity authentication first, then grip the dynamometer built with a pressure sensor array (accuracy: ±0.5kg) to exert force. The system tracks the peak grip strength and continuous force curve in real time, automatically filters invalid force applications, and conducts personalized analysis based on age and gender.
Test results—including maximum grip strength (in kg) and the strength difference ratio between left and right hands—are displayed within 3 seconds. All data is encrypted to comply with medical privacy standards, making it ideal for rapid upper limb muscle strength assessment in gyms, rehabilitation centers, and other venues.