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Sensor-based cloud computing data system and long distance running fatigue assessment.

Jing Li¹, ZhiBiao Liu²

¹Sports Health Technology College, Jilin Sports University, Changchun, Jilin 130022, China.

Preventive Medicine

|July 5, 2023

Summary

This study enhances cloud computing data systems using dynamic replication and blockchain transmission for improved performance. It also advances long-distance running fatigue assessment through specialized exercise load experiments and EMG signal analysis.

Keywords:

Cloud computing Data system Exercise fatigue Long-distance run Sensors

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Area of Science:

Cloud Computing
Wireless Sensor Networks
Biomedical Engineering

Background:

Wireless sensor networks are integral to diverse fields like healthcare and environmental monitoring.
Current cloud data systems require dynamic strategies to meet varied user demands.
Assessing long-distance running fatigue needs more precise and reproducible methods.

Purpose of the Study:

To design and implement a dynamic replication strategy for cloud computing data systems.
To develop a multi-source blockchain transmission method for efficient data migration.
To analyze long-distance running fatigue using simulated exercise loads and EMG signal analysis.

Main Methods:

A dynamic replication strategy based on user data access patterns was designed and implemented.
A multi-source blockchain transmission method was developed to reduce data migration time.
Simulated specialized exercise load experiments and surface EMG signal analysis were conducted.

Main Results:

The dynamic replication strategy and blockchain method improved cloud storage data system performance.
The study successfully reproduced exercise fatigue characteristics in athletes.
Amplitude-frequency joint analysis of EMG signals provided insights into fatigue mechanisms.

Conclusions:

The research contributes to the advancement of cloud computing data systems and efficient data management.
The proposed methods enhance the assessment of long-distance running fatigue.
This work integrates sensor networks, cloud computing, and biomechanical analysis.