Intelligent technology has not been fully explored and widely used in the field of military sports training and assessment. The formation of military sports big data is inseparable from the data support of intelligent sensing technology. Military sports big data can accurately explore the limits and potential of officers and soldiers' physical training, evaluate the overall performance, growth and physical fitness of officers and soldiers, and scientifically analyze the physical training process and behavioral habits of officers and soldiers in the army, correct unscientific and irregular movements, so as to achieve the best effect of big data training.
1. Verify "assessment identity" with intelligent identification technology
Using intelligent identity identification technology to verify the identity information of participants in the assessment is an important means to block training assessment fraud. On training and assessment equipment such as body measurement, running, snake running, horizontal bar, sit-ups, push-ups, etc., uniformly install biometric fingerprints, video recognition equipment or QR code recognition equipment, use unified identity information and identification, collect and verify the identity information of invigilators and assessees, and store video recordings and record verification information throughout the process.
2. Use intelligent sensing technology to obtain "assessment data"
Use intelligent sensing technology to collect the original data of military sports assessments, and realize automatic timing, automatic counting, automatic analysis, and automatic statistics. For body measurement, pressure, ultrasound, biological penetration and other technologies are used to realize the rapid collection of BMI (physique) and PBF (body fat); for running assessment, RFID recognition technology and video face recognition technology are used to realize dual recognition and intelligent error correction for running assessment; for serpentine running, laser counter-shooting sensor technology and laser positioning technology are used to realize the accurate collection of serpentine running assessments and quickly locate the setting of obstacle poles; for sit-ups, push-ups, pull-ups on the horizontal bar, and horizontal bar flexion hangs, infrared detection technology and posture detection technology are used to realize the accurate detection, identification, and recording of the number, duration, and movement standards of assessments.
3. Use intelligent control technology to determine "assessment standards"
Use intelligent control technology to automatically calculate the assessment standards for each subject according to the participants of different ages, genders, and heights, and automatically set the equipment limit standards; accurately judge whether the actions during the assessment process are up to standard and effective, accurately limit the assessment time and the displacement of the adjustment point equipment, and accurately statistically analyze the assessment results and scores to ensure that the assessment data is true and effective, and avoid human-dominated and objective factors affecting the training assessment results.
4. Use intelligent analysis technology to evaluate "assessment results"
The fairness and justice of the assessment is to ensure that the military sports assessment results are formed through hard training, rather than by taking shortcuts. To plug the loopholes in the assessment, we must fundamentally solve the loopholes in the assessment methods and means, use data and video remote transmission technology to synchronously store the data and video images collected by the front-end equipment sensors to the grassroots and large unit training and assessment data centers to prevent the assessment results from being tampered with; use remote assessment and video monitoring technology to check the assessment status in real time and automatically evaluate the assessment results; use big data analysis technology to deeply mine the training assessment process and result data, deeply analyze the data results of each batch and unit, evaluate whether there is a risk of distortion in the training assessment data, and focus on supervising units and individuals whose assessment data has fluctuated greatly in history, to ensure the openness, fairness and justice of the training assessment.
