Internet Technology Letters最新文献

At present, the living habits of college students are relatively poor, and the amount of exercise is reduced, leading to their physical fitness getting worse and worse. Therefore, people began to study the physical health monitoring of college students. Machine learning and high-performance computing in medical applications provide technical support for intelligent medical technology. With the rapid development of computer network, human beings have entered the information and digital era, and sports health big data has become more and more popular. The combination of sports health big data and student physical health monitoring technology, in a sense, can realize automatic data processing through intelligent medical and sports health database and other information technologies, thus promoting the popularization of health monitoring technology. However, the current health monitoring equipment has many problems, such as complex collection, low accuracy and limited processing of health data. To solve this problem, this paper developed an Application (APP) based on sports health big data technology that can monitor multiple vital signs such as human heart rate and body temperature, and analyze the physical health of college students, so that college students can easily understand their health status in daily life, so as to promote the healthy development of students' physique and encourage them to actively participate in physical exercise. The experiment proved that, in the heart rate monitoring, when the speed is 6 km/h, the error rate of the college students' physical health monitoring APP designed in this paper is 8.15%. The average accuracy rate of student steps monitoring is 97.12%. This showed the accuracy and availability of the APP's monitoring function for human vital signs. It has certain application value and significance to help students improve their physical quality.

This paper introduces the application of blockchain technology in the field of IoT medical information, proposes a secure and trustworthy framework for storing and sharing medical information based on blockchain, containing functions such as tamper-proof storage of IoT medical data, desensitization processing of sensitive information and sharing of medical information security, and predicts the future market state transfer and the construction time of the model framework from the perspective of economics.

This letter studies an OFDM based intelligent reflecting surface (IRS)-aided multiuser simultaneous wireless information and power transfer (SWIPT) system. With subcarrier allocation, users use the assigned subcarriers for information decoding (ID), and use signals received on subcarriers allocated to other users for energy harvesting (EH). An optimization problem is formulated to maximize the system energy efficiency by jointly optimizing subcarrier and power allocation and IRS reflection coefficients matrix. It can be solved by an alternating optimization algorithm. Simulation results reveal that energy efficiency can be enhanced in our proposed scheme compared with the benchmark schemes.

Wireless sensors are important nowadays to collect real-time data in hospital wards. Small sensors can be deployed either on/in patients' bodies or at fixed locations in wards. We propose an autonomous wireless system, where sensors can harvest energy from radio frequency signals, monitor and transmit data using the harvested energy. By properly modeling energy statuses and stochastic distributions of sensors, we analyze the coverage performance using Campbell's theorem, probability generating functional (PGFL), and Gil-Pelaez inversion theorem. The nonlinear energy harvesting model and the general Nakagami-m fading channels are considered in the analysis. Numerical results show that the coverage performance degrades when sensors are distributed more densely, the energy and data links are prolonged, or the transmission rate gets larger, while it improves when higher power is used for the energy transfer, or the energy and data links undergo lighter fading. Our proposed scheme can well facilitate the long-time monitoring tasks in hospital wards, which can greatly alleviate the burdens of medical staff.

The above article, first published online on October 23, 2020 Wiley Online Library (https://onlinelibrary.wiley.com/doi/full/10.1002/itl2.252) has been retracted by agreement between the journal Editor-in-Chief, Luigi Alfredo Grieco, Department of Electrical and Information Engineering (DEI) Politecnico di Bari, Bari, Italy and Wiley Periodicals, LLC. The retraction has been agreed due to pertinent evidence indicating that the peer review process of this paper was compromised. The accepted letter has gone through an additional evaluation by scientific experts who judge that the quality of those contributions was not in line with the standards of the ITL journal. The editorial office did not receive a response from the authors, and so requested underlying experimental data was not available for evaluation. Accordingly, the editors consider the conclusions of this manuscript invalid.

Unmanned aerial vehicle (UAV) assisted wireless communication has been recently proposed as an effective solution to provide wireless connectivity to ground users which can improve the network coverage area and spectral efficiency. In this paper, we consider the post-disaster network scenario where users are isolated from the network infrastructure. We investigate the best positioning of the UAV in terms of the optimal trajectory as well as UAV vertical location to cover as many ground users as possible to improve the spectral efficiency. When the trajectory is optimized, the optimal transmit power within the available power budget is then obtained. The simulation results demonstrate that the proposed UAV-enabled wireless communication technique improves the overall spectral and energy efficiency.