Research on the Influence of Sports and Nutrition Matching on Improving Students’ Physique Based on Intelligent Sensor

With the continuous development of social economy, students’ learning is paid more and more attention, but at the same time, their physical condition also deserves attention. In view of these problems and limitations, this paper is based on intelligent sensors, which is different from the traditional physical education teaching, adopts the corresponding prescription for sports teaching, combines teaching with fun for the corresponding health intervention, and realizes the two-way dimensional analysis of compound sports prescription through comprehensive nutrition collocation, so as to improve students’ physical and mental health, in order to improve students’ physical fitness. The simulation results show that the intelligent sensor is effective, which can improve the systematicness and scientificity of students’ participation in exercise in sports activities and improve students’ learning and physical fitness.

Intelligent System for Training and Assessment of Basketball Referee in Sports Event Using Intelligent Sensor

Aiming at the problem of the fairness of the judgment results in the traditional basketball referee training and evaluation process affected by external factors, an intelligent system for training and assessment of basketball referees in sports events based on intelligent sensors is proposed. We collect the judged poses of basketball referees by wearing intelligent sensor devices, store the collected information in the database using the converter, and analyze the pose data with the quaternion pose solution method based on complementary filters. According to the comparator, the analysis result is compared with the standard judgment information, and the action is judged whether the action conforms to the basketball judgment rules of the sports event. The judge’s action pose score is evaluated according to the judgment result, and the training assessment result is outputted. The results show that the system can clearly simulate the acceleration and pose angle data of the referee’s complex actions, the recognition rate of various basketball penalty poses is high, and the error of the pitch, yaw, and roll pose calculations is small. The response time of this system is 4 ms, when the number of requests sent by the client is 200 which is unanimously approved by the referees.

Smart Manufacturing and Jobs

The proper use of new technologies, together with a good management of these by the workers, makes the workplace become a melting pot of new ideas, where professional development and motivation [1] make a difference with past and present times where monotonous and repetitive work was the constant. With the use of artificial intelligence, the cloud and big data, a set of intelligent sensors is necessary, which can monitor a critical variable within the production line, which requires an encrypted communication infrastructure and with information that can be monitored in real time, which allows a better performance of the company, making it a more pleasant place for staff and with working conditions that help to overcome them when performing complex tasks. Due to the educational level that many of the workers currently have and the fact of being born in a technified society, it causes them to be more interested in carrying out activities where they develop their creativity and skills, resulting in economic and psychological well-being.

sensLAB: TESTING MOTION AND PRESENCE SENSORS FOR SMART LIGHTING

For further efforts in saving energy in lighting installations, intelligent sensors are indispensable. Despite the fact such sensors are available precise and reproducible measurements of the coverage areas are missing. Therefore, METAS decided in 2020 to install the world's first manufacturer-independent fully automated measurement system to test passive infrared motion and presence sensors according to the recently published standard IEC 63180:2020. The test facility allows reproducible measurements of radial and tangential movements by moving different scaled and heated dummies on linear tracks. Furthermore, the presence detection can be measured with an automated robot arm. The test results are provided in a digital test report and the data is available in a machine-readable format to be further processed in designing and planning softwares.

Self-Assembly of Silver Clusters into One- and Two-Dimensional Structures as Artificial Intelligent Sensors of Alcohol

Reggeization and response to external stimulus is an important part of artificial intelligence, which would significantly improve the quality of life in the future. The development of new materials for the design of sensitive and responsive sensors has become a crucial component. Here, two silver cluster-based polymers (Ag-CBPs), including one-dimensional (1D) {Ag22(L1)8(CF3CO2)14(CH3OH)2}n chain and two-dimensional (2D) {[Ag12(L2)2(CO2CF3)14(H2O)4(AgCO2CF3)4](HNEt3)2}n film, are designed and used to simulate the human nose - an elegant sensor to smells, to distinguish organic solvents. We study the relationship between the atomic structures of Ag-CBPs determined by X-ray diffraction and electrical properties in the presence of organic solvents (e.g. methanol, ethanol). The ligands, cations and the ligated solvent molecules not only play an important role in the self-assembly process of Ag-CBP materials, but also determine their physiochemical properties. An application of cluster-based polymers is demonstrated in the artificial intelligent sensors.

Application of Intelligent Sensors in Biomarker Detection Using Accurate Data Measurement and Calculation

Cancer has been one of the most serious health issues of the 21st century. Although improvements in the treatment of cancer with new pharmaceutical products and technology remain a significant challenge for cancer biologists and oncologists. Early and accurate screening and analysis technology to diagnose the disease are essential for improving the survival rate and reducing mortality and morbidity. Scientists have discovered the clinical application of cancer biomarkers for cancer diagnosis and treatment. Biosensors technology appears to be the only hope for timely diagnosis and treatment of cancer, since they exhibit remarkable analytical performance. In this review, we will discuss about basic knowledge and classification of biosensors, common cancer biomarkers and some applications of biosensors in cancer biomarker detection.

Study of Cognitive State Recognition and Assistive System for Overall Reading of Foreign Literature Based on Intelligent Sensors

In real life, the text is one of the main carrier forms of information, which carries human civilization, and spreads knowledge to people, and also promotes culture and records history; however, how to read more information in a limited time, that is, to improve reading efficiency, has become a problem to be solved by current technology. The purpose of this paper is to integrate the existing wearable device concept, combined with a wireless intelligent sensor system; design a wearable reading assistance system designed to facilitate the use of blind and partially sighted people, based on the study and comparison of existing text recognition products; improve their functions and implementation platform, combined with wireless network; and design a wearable device that can achieve foreign text recognition and reading cognitive state reading assistance thereby improving reading efficiency. This paper proposes a method to implement foreign text decoding under the embedded platform with relatively few resources and quickly completes image acquisition, binarization, and compressed storage through the bit and storage area and DMA (direct memory access) double buffering mechanism unique to the chip selected in this paper; proposes to use the connected boundary tracking algorithm to find foreign text locators, reducing a large number of floating-point operations; does not rotate the image, instead, the image is directly sampled at the current rotation angle, and then foreign text bitstream information is acquired to realize the decoding of foreign text under the embedded platform with relatively fewer resources.

Principal Component Analysis and Machine Learning Approaches for Photovoltaic Power Prediction: A Comparative Study

Nowadays, in the context of the industrial revolution 4.0, considerable volumes of data are being generated continuously from intelligent sensors and connected objects. The proper understanding and use of these amounts of data are crucial levers of performance and innovation. Machine learning is the technology that allows the full potential of big datasets to be exploited. As a branch of artificial intelligence, it enables us to discover patterns and make predictions from data based on statistics, data mining, and predictive analysis. The key goal of this study was to use machine learning approaches to forecast the hourly power produced by photovoltaic panels. A comparison analysis of various predictive models including elastic net, support vector regression, random forest, and Bayesian regularized neural networks was carried out to identify the models providing the best predicting results. The principal components analysis used to reduce the dimensionality of the input data revealed six main factor components that could explain up to 91.95% of the variation in all variables. Finally, performance metrics demonstrated that Bayesian regularized neural networks achieved the best results, giving an accuracy of R2 = 99.99% and RMSE = 0.002 kW.