IoT Sit-Up Detection System Using Multi-Sensor Fusion
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Solution Overview
Problem
Existing sit-up detection systems using infrared probes and visual detection methods are inaccurate and cost-ineffective due to sensitivity to light variations and inability to determine if the body is lifted towards the thighs during a sit-up action.
Innovation Solution
A sit-up motion information management system based on IoT, utilizing a main control chip connected to a laser distance sensor, tilt sensor, and gesture recognition sensor arranged on a thigh, which detects distance, angle, and hand interference to accurately determine the sit-up motion and standardization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If infrared probes are used to detect sit-up actions, then the counting system is simple to implement, but the measurement accuracy deteriorates due to light sensitivity and inability to determine proper body position
Solution Approach 1:
The patent combines multiple sensors (laser distance sensor, tilt sensor, gesture recognition sensor) into an integrated detection system worn on the thigh. This merging of multiple detection mechanisms allows the system to simultaneously monitor distance, angle, and hand position, thereby achieving accurate sit-up detection while maintaining reasonable system complexity through unified sensor integration.
Solution Approach 2:
The patent introduces sensors as intermediary devices that indirectly measure sit-up actions by detecting physical parameters (distance, angle, gesture) rather than directly observing the complete motion. This intermediary approach allows accurate measurement of body position and movement without requiring complex visual systems, resolving the contradiction between simplicity and accuracy.
2Measurement precision
If visual detection systems are used to improve measurement accuracy, then sit-up detection precision improves, but the device cost and complexity increase significantly
Solution Approach 1:
The patent segments the detection function into multiple independent sensors (laser distance sensor for distance measurement, tilt sensor for angle detection, gesture recognition sensor for hand position), each performing a specific measurement task. This segmentation allows the system to achieve comprehensive and accurate sit-up detection through simple, dedicated sensor functions rather than a complex unified visual system.
Solution Approach 2:
The patent replaces complex visual detection systems with mechanical and optical sensors that directly measure physical parameters. By substituting camera-based visual systems with simpler sensors that detect distance, angle, and gesture mechanically or optically, the system achieves equivalent or superior measurement accuracy with reduced complexity and cost.
3Measurement precision
If multiple sensors are integrated to improve detection accuracy, then measurement precision improves, but the device complexity increases
Solution Approach 1:
The patent designs the sensor system with multi-functionality, where the integrated sensor module on the thigh serves multiple detection purposes simultaneously (distance measurement, angle detection, gesture recognition). This universal design allows a single integrated device to perform multiple functions that would otherwise require separate systems, improving accuracy while managing complexity through functional integration.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system achieves higher counting accuracy for sit-up detection by correctly determining the sit-up action through the cooperation of sensors, providing real-time feedback and standardization of exercises.
Implementation Method 1
a laser distance sensor... is configured to detect a distance from the thigh to a trunk
Implementation Method 2
the tilt sensor is configured to detect an angle of the thigh from a horizontal ground
Data Source
AI summary
The present disclosure provides a sit-up motion information management system and detection method based on an Internet of things. The method includes: acquiring detection data of a sensor at present time; determining whether the detection data of the sensors at the present time meet a first counting condition, determining that a sit-up action is correct if yes, and incrementing a flag value by one; acquiring detection data of the sensors at next time; determining whether the detection data of the sensors at the next time meet a second counting condition, determining that a sit-up action is correct if yes, and incrementing a flag value by one; determining whether a flag value is greater than or equal to a preset value to obtain a third determination result; and determining, if the third determination result indicates yes, that one rep of sit-up actions is completed, and recording a number of sit-up reps.