Optimization and Simulation of an English-Assisted Reading System Based on Wireless Sensor Networks

In this paper, wireless sensor network technology is applied to an English-assisted reading system to highly simulate and restore the context and improve the performance of all aspects of the English-assisted reading system to optimize the English-assisted reading system. The product designed in this paper is based on wireless sensor network technology with Linux as the core operating system and supports POSIX (Portable Operating System Interface Standard) standard application development interface; QT is used as the component and framework of the system to support many applications. Based on player open-source multimedia audio and video technology, optimized and tailored for the hardware platform, it well supports multimedia learning and entertainment functions; this paper also adopts open-source database technology based on SQL (Structured Quevy Language) and Berkeley DB, using them as a platform for data storage and access, supporting a million-level thesaurus and high-speed, example sentence search. In this paper, we describe the user’s personalized needs by creating interest models for the user, recommending the text content, and reading order that can help with understanding through the interest models and reading articles and expanding the recommended text range by making expansions to the reading content through references and related articles to further help the user understand the text. Based on the above work, this paper implements an assisted reading system; finally, a multihop self-organizing network system is formed through a wireless sensor network to make the rigid and boring English reading easy and interesting.

Digitalization and Information Management Mechanism of Sports Events Based on Cooperative Sensing Model of Multisensor Nodes

This paper provides an in-depth study and analysis of the optimization of sports event management systems using wireless sensor networks. Aiming at the monitoring task of a directed wireless sensor network in a three-dimensional environment, the directed sensing nodes scattered inside the designated monitoring area in a random deployment manner usually have uneven distribution and other problems; we analyze the characteristics of the directed sensor nodes, probabilistic sensing model, and the cooperative sensing model of multiple sensor nodes for monitoring target points and propose a sensing optimization strategy in polar coordinates to guide the three-dimensional plane directed orientation adjustment and sensing optimization of sensor nodes, thus enhancing the sensing capability of network nodes. The experimental results confirm that the algorithm can improve the coverage of the area to be monitored and the quality of sensing service, and it reduces the overall energy consumption of the network by using the distributed node synchronization scheduling mechanism to extend the life cycle of the network to maintain good monitoring capability under the premise of the limited total usage of the directed nodes in wireless sensor networks. The application of wireless sensor network technology in sports competition management mainly includes the application of smart wearable devices in sports competition training, the application of goal-line technology in sports competition, and the application of eagle eye technology in sports events, all three technologies have certain advantages in the application of sports competition, and all of their help to promote the improvement of sports event management and the development of sports industry; the second aspect is wireless sensor. The second aspect is the application of wireless sensor network technology in sports event information management, which is mainly used to collect information related to sports events and fully utilize it to make sports event management more informative and digital, which is helpful to improve the level of sports event management; the third aspect is the application of wireless sensor network technology in sports event stadium management, which is mainly based on intelligent stadiums to create a more spectator-friendly and good experience for the audience, a more ornamental and good experience viewing place, to promote the development and growth of sports industry.

Data Mining of Regional Economic Analysis Based on Mobile Sensor Network Technology

With the continuous development of regional economy, the difference of regional economy has also aroused the attention of all walks of life. Due to the limitations of the traditional research methods, the research results are relatively simple and unable to conduct a more comprehensive analysis. The traditional methods include the following: (1) analyze the evolution of regional logistics based on the location Gini coefficient and location quotient of GIS, and reflect the situation of industrial agglomeration from the annual change curve of the location Gini coefficient; (2) use SPSS12.0 software to perform multivariate or event factors, and analyze and calculate the factor score to sum up several principal component factors; and (3) the production function analysis method is used to measure the economies of scale and agglomeration. As an extension, the relationship between the estimated total output and the agglomeration index of the factor input to measure the uniform state of the industrial distribution department is an effective measurement method for the agglomeration economy. In order to promote the sustainable development of regional economy, this paper analyzes the regional economy comprehensively based on the emerging mobile sensor network technology and data mining technology. Firstly, this paper analyzes the location technology of mobile sensor networks based on sequential Monte Carlo, selects the C -means clustering method which is suitable for economic large-sample clustering analysis, and constructs a complete data mining model. Then, the model is used to analyze the economic, social, natural, and educational science and technology indicators of a certain region from 2015 to 2019. The results show that the first principal component weight of economic indicators is the highest proportion of fiscal revenue, which is 0.986. This shows that the role of fiscal revenue in economic indicators is greater. The main index of urban consumption is 72.0, which is the highest. This shows that the population growth rate and the average consumption of urban households in social indicators play a greater role. The first principal component of natural index has the highest weight of pollution emission, which is 0.47, while the second principal component has the highest weight of total energy consumption, which is 0.48. This shows that the pollution emissions and total energy consumption in the natural indicators play a greater role. In the educational science and technology index, the first principal component weight is the highest, which is 0.61. This shows that the education funds play an important role in educational science and technology indicators. Therefore, the data mining model based on mobile sensor network technology can comprehensively and accurately analyze various indicators of regional economy.

Predictive Maintenance in the Automotive Sector: A Literature Review

With the rapid advancement of sensor and network technology, there has been a notable increase in the availability of condition-monitoring data such as vibration, temperature, pressure, voltage, and other electrical and mechanical parameters. With the introduction of big data, it is possible to prevent potential failures and estimate the remaining useful life of the equipment by developing advanced mathematical models and artificial intelligence (AI) techniques. These approaches allow taking maintenance actions quickly and appropriately. In this scenario, this paper presents a systematic literature review of statistical inference approaches, stochastic methods, and AI techniques for predictive maintenance in the automotive sector. It provides a summary on these approaches, their main results, challenges, and opportunities, and it supports new research works for vehicle predictive maintenance.

Fiber Optic Network Technology of Communication of Specialists via Mental Neurointerfaces

Resonance communication of specialists can be carried out at a distance in real time in dialogue mode through a mental neurointerface with two-way communication. Mental neurointerface on the principles of magnetic resonance tomography captures a hologram of brain activity of the internal speech of the inductor specialist and transmits it to the mental neurointerface of the recipient's interlocutor through ultra-sensitive multi section nano resonators waveguides. The mental neurointerface of the recipient's interlocutor perceives the transmitted hologram of the brain activity of internal speech and resonates its internal speech to it. An interlocutor of the recipient with equivalent semantic memory in a resonant way makes sense of the internal speech of the inductor specialist. He forms the response with internal speech and transmits it to the interlocutor with his mental neurointerface through nano resonators in the form of holograms of the brain activity of internal speech. Interlocutors, as specialists in one subject area, have a similar semantic memory. Semantic memories are considered similar if they correspond to the principle of gold section according to a professional thesaurus. Specialists and interlocutors must learn a professional thesaurus before starting a dialogue through mental neurointerfaces. Thus, the problem of transmitting and reading thoughts at a distance using high technology is solved, taking into account the psychological aspects of the interlocutors. The development of mental neurointerfaces and ultra-sensitive multi section nano waveguide resonators for transmitting holograms of internal speech brain activity is just beginning. The use of resonant communication by mental neurointerfaces through nano waveguides resonators waveguides is currently very relevant in many areas of life activity.

Research on the Intelligent Display of Cultural Relics in Smart Museums Based on Intelligently Optimized Digital Images

The smart museum is a new platform for the appreciation and display of cultural relics across time and space. In the era of 3D scanning technology, computer technology, and network technology, it is necessary to deeply study the smarter and more perfect forms of smart museums. This article, through the analysis of the characteristics of the display level of the smart museum, tries to create a new humanized and intelligent display of cultural relics.