Immersive Virtual Reality Teaching in Colleges and Universities Based on Vision Sensors

With the progress of society and the development of economy, people pay more and more attention to education, and traditional teaching methods are gradually unable to meet the modern teaching system. As a leader in modern information technology, virtual reality technology has developed rapidly in recent years, and virtual reality technology has also been introduced into many fields, such as teaching. Based on the immersive and extended characteristics of virtual reality, this paper proposes a virtual reality active visual interaction method based on the visual sensor. Based on virtual teaching, after 3 months of learning, the average, standard deviation, and average standard error of the experimental group’s performance are higher than those of the control group. Compared with the control group, the experimental group’s performance has increased by 8.25%. The difference is statistically significant. Learning significance ( P < 0.05 ), immersive virtual reality teaching has played a significant role in the effect, which can greatly improve the cognitive experience of students and achieve a good learning experience and effect.

Classification of Assembly Operations Using Recurrent Neural Networks

Visual sensor data of manual assembly operations offers rich information that can be extracted in order to analyze and digitalize the assembly. The worker’s interaction with tools and objects, as well as the spatial–temporal nature of assembly operations, makes the recognition and classification of assembly operations a complex task. Therefore, classical methods of computer vision do not provide a sufficient solution. This paper presents a recurrent neural network for the classification of manual assembly operations using visual sensor data and addresses the question as to what extent such a solution is feasible in terms of robustness and reliability. Since complex assembly operations are a combination of basic movements, four main assembly operations of the Methods Time-Measurement base operations are classified using a machine learning approach. A dataset of these four assembly operations, reach, grasp, move and release, containing RGB-, infrared-, and depth-data is used. A Convolutional Neural Network—Long Short Term Memory architecture is investigated regarding its applicability due to the spatial–temporal nature of the data.

Application of Visual Sensing Image Processing Technology under Digital Twins to the Intelligent Logistics System

Since the founding of the People’s Republic of China, the advantages of logistics are neglected, and the scale operation and the welfare in the industry are difficult to achieve due to the influence of the economic system and social environment. Therefore, a new intelligent logistics distribution management system based on machine vision and visual sensor image processing technology is constructed to respond to the shortcomings of the traditional system, including slow efficiency, huge cost, complex data, and low degree of informatization. Through the analysis and research on the visual sensor image processing technology and the order processing, receipt management, distribution management, scheduling management, and return management that affect logistics distribution, a simulation experiment is used to verify that the visual sensor image processing technology is rigorous, intelligent, and efficient and has high precision. The intelligent logistics distribution management system can effectively solve the problems existing in the traditional logistics distribution management. The experimental results show that the visual sensor image processing technology can collect and analyze the target image and effectively track and monitor it in the logistics distribution process. The average distribution precision of the intelligent logistics distribution management system reaches more than 99.5%, which is greatly improved compared with 90% of the traditional logistics distribution. And it can greatly improve the distribution efficiency, which increases by about 26.5%. The study realizes the information management of the logistics system and automatically completes all the work according to the designed program, so that the real-time dynamic distribution can be transmitted to the urban logistics distribution at any time.

Security enhanced optimal trajectoryselection for mobile sink using reinforcement learning

Wireless visual sensor networks (WVSNs) have emerged as a strategic inter disciplinary category of WSN with its visual sensor based intelligence that has garnered considerable attention. The growing demand for energy efficient and maximized life time networks in highly critical applications like surveillance, military and medicine has opened up more prospects as well as challenges in the deployment of WVSNs. Multi-hop communication in WVSN results in overloading of intermediate sensor nodes due to its dual function in the network which results in hotspot effect. This can be mitigated with the help of mobile sinks and rendezvous points based route design. But mobile sinks has to visit every cluster head to gather data which results in longer traversal path and higher latency and power consumption related issues if not addressed properly will impact the performance of the network. Our objective is to analyze and determine the optimal trajectory for mobile sink node traversal with the help of a high quality transmission architecture integrated with reinforcement learning and isolation forest based anomaly detection to propose an energy efficient meta-heuristic approach to enhance the performance of network by reducing the latency and securing the network against possible attacks.

Research Progress on the Molecular Mechanism of EGCG3 ″ Me in the Treatment of Diabetes Based on Visual Sensor Images

Diabetes is a chronic metabolic disease with abnormal blood glucose and lipid metabolism caused by insufficient insulin secretion, which seriously affects human health. For solving the problem of treating diabetes, it is particularly important to observe the research progress of the molecular mechanism of EGCG3 ″ Me in the treatment of diabetes based on visual sensor images. This research has not been verified in practice, but many scientists are already studying it. This article is aimed at studying the molecular mechanism of using EGCG3 ″ Me to treat diabetes based on visual sensor images. This article introduces the concept and application of visual image sensor in detail, using a superpixel segmentation method to realize image observation. The EGCG3 ″ Me was extracted and used in diabetes treatment experiments. The experimental results showed that the blood glucose of the mice in the experimental group had returned to normal 60 minutes after the administration of glucose in the blank control group, and the blood glucose of the mice in the control group had basically returned to normal after 120 minutes. Compared with the model group, the number of acinar paging and the number of cells in the pancreatic islets increased in the mice after EGCG3 ″ Me treatment, indicating that EGCG3 ″ Me has the effect of protecting and repairing pancreatic islet cells.

Design of Robot Vision Servo Control System Based on Image

Visual servo is a closed-loop control system of robot, which takes the image information obtained by visual sensor as feedback. Generally speaking, visual servo plays an important role in robot control, which is one of the main research directions in the field of robot control and plays a decisive role in the development of intelligent robots. In order to make the robot competent for more complex tasks and work more intelligently, autonomously and reliably, it is necessary not only to improve the control system of the robot, but also to obtain more and better information about the working environment of the robot. This paper introduces the principle and basic realization method of robot visual servo based on image, and expounds the problems and solutions in image feature extraction and visual servo controller design. In order to further expand the application field of robots and improve the operation performance of robots, robots must have higher intelligence level and stronger adaptability to the environment, so as to manufacture intelligent robots that can replace human labor.

Design and Research on the Foul Detector of a Long Jump Jumping Line Based on a Vision Sensor

Long jump is one of the important events of modern track and field sports, and it is also one of the regular events of major events. Due to the complexity and technicality of the project, the determination of the results in a formal competition is also very complicated. It is easy for athletes to invalidate their results due to fouls by stepping on the jump line. Therefore, it is very necessary to detect fouls. This paper uses a visual sensor technology to design and develop a foul detector for the situation of athletes stepping on the jump line in a long jump, which can detect fouls well. In the formal competition process, because the long jump time is relatively short, the referee is interfered by many factors and it is easy to misread the movements of the athletes and cause misjudgment. Therefore, on this basis, in order to improve the fairness of the game and create a good competition environment, the design is designed. The long jump stepping line foul detector is studied, and the visual sensor technology is used, which can judge the long jump stepping fouls during the long jump based on the feedback data.

Optimal Method of Vision Sensor Digital Image Edge Detection for Commercial Investment in Film Field

With the rapid development of the national economy, the film industry has risen rapidly under these conditions, and the development of film occupies a more important position in this process, which has led to the development of investment in the film field, an internationally recognized cultural space. This paper studies the commercial investment in the film field based on the edge detection of the digital image of the visual sensor. The purpose of the research is to point out the direction of commercial investment in the film industry by studying the effect of the edge detection of the digital image of the visual sensor on the application of the film object. The image edge detection algorithm based on wavelet transform and morphology and the application of these image edge detection algorithms such as wavelet theory analyze the shortcomings of movie, sound effects, and pictures and make a comparison before and after the improvement. Audiences, as the direct enjoyers of the cultural product of the film, their opinions, and evaluations of the film, largely determine the quality of the work. On the contrary, a good work can attract the public’s attention and bring a large impact. The data acquisition in this process is mainly based on the questionnaire survey of the audience. The experimental results show that before applying digital image edge detection to transform the clip, 7 people thought that the clip needed to be further improved to improve the quality of the film itself, and only 1 person affirmed the film; after the modification, 9 people proposed the film praise; in addition, 15 people audience watched the film processed by the edge detection method and gave high evaluations to the three aspects of sound effects, special effects, and editing, especially the editing part, with a score of 8.9.

Aerobics Movement Decomposition Action Teaching System Based on Intelligent Vision Sensor

With the development of the times, teaching has not only stayed between people, but also gradually developed into the teaching interaction between man and machine. In the past, the teaching form was relatively single and old. Based on the intelligent visual sensor, this paper develops an auxiliary teaching system for the decomposition of aerobics action and reasonably uses the Internet and algorithms to catalog a series of aerobics action systems into the system. The DTW dynamic motion matching algorithm of the system will recognize human actions more accurately. The system will feed back human actions to the system in real time based on human feature recognition. Then, after comparison, the system will display the standard posture of this action and the aerobics posture in the next step. Therefore, this system develops teaching not only in class, but everywhere. The system not only improves the teaching quality of aerobics, but also strengthens the physical quality of teenagers. It has a new understanding of the standardization of aerobics teaching. After the function of the system is complete, the system will be distributed to aerobics learners. In many feedback information, the average use satisfaction has reached about 80%, which is a good performance index for the performance of the system itself.