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    30 March 2022, Volume 6 Issue 1
    Topic: IoT Terminals and Chips
    Recent progresses and challenges in smart contact lens
    Jiandong XU, Ruisong LI, Hao CHANG, Yi YANG, Sheng ZHANG, Tianling REN
    2022, 6(1):  1-12.  doi:10.11959/j.issn.2096-3750.2022.00252
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    With advances in the Internet of things, contact lenses not only are limited to vision correction, but also have become an emerging field of the smart wearable device.And with the proposal of the concept of “meta universe”, augmented reality (AR) technology has once again become the mainstream development direction of science and technology.The latest research progress of key technologies of smart contact lenses in physiological signal monitoring, intraocular pressure monitoring, eye-movement tracking, and augmented reality, as well as the energy supply scheme of the contact lenses were summarized comprehensively.And the future development direction of smart contact lenses in intelligent health and augmented reality was looked forward.In the future, smart contact lenses will realize or surpass the functions of smartphone.Their displays can be controlled by eye movement, which enables us to browse various information, such as news, weather, biomarker level, etc.Therefore, the smart contact lens will play an important role in intelligent medical health and meta universe.

    Simulation of film bulk acoustic resonator based on two-dimensional phononic crystals
    Linhao SHI, Weipeng XUAN, Lingling SUN, Shurong DONG, Hao JIN, Jikui LUO
    2022, 6(1):  13-19.  doi:10.11959/j.issn.2096-3750.2022.00251
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    A new structure of film bulk acoustic resonator (FBAR) based on phononic crystal (PnC) was proposed.The phononic crystal was used as the acoustic reflection layer at the bottom of the bulk acoustic wave resonator, which has the characteristics of high reflectivity and low transmittance of elastic wave in its band gap.The band gap characteristics of four kinds of phononic crystals with different structures were calculated by the finite element software COMSOL Multiphysics.The main conclusions are as follows.If the bulk acoustic resonator is working within the band gap of the phononic crystal, PnC can be used as the bottom acoustic reflection layer of the FBAR.With using PnC as the acoustic energy reflect structure, the impedance curve of FBAR is smooth, and the quality factor is closed to traditional FBAR with a value of 859 and effective mechanical coupling coefficient of 6.32%.

    Verification of an artificial intelligence vision chip design for edge computing based on hardware simulation system
    Xuanzhe XU, Ke NING, Xuemin ZHENG, Mingxin ZHAO, Mengmeng XU, Nanjian WU, Liyuan LIU
    2022, 6(1):  20-28.  doi:10.11959/j.issn.2096-3750.2022.00250
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    The rise of visual deep learning algorithms based on convolutional neural network (CNN) has promoted the rapid development of the artificial intelligence (AI) vision chip design research.The step of chip verification is a bottleneck in the development of AI vision chips.A software and hardware verification method for AI vision chip design based on hardware simulation system was introduced.Taking AI vision chip design for edge computing as an example, the chip was run on the hardware simulation system (ZeBu) and the simulation verification work of typical deep learning network MobileNet was completed.The results show that the network model implemented on the hardware chip architecture keeps accuracy while the detection time of a single frame is only 18.51 ms under a 200 MHz clock frequency.The spread of the hardware simulation is 7 times faster than than of the software simulation.

    Theory and Technology
    6G: typical applications, key technologies and challenges
    Ning LUAN, Ke XIONG, Yu ZHANG, Ruisi HE, Gang QU, Bo AI
    2022, 6(1):  29-43.  doi:10.11959/j.issn.2096-3750.2022.00253
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    2020 marked the first year of the era of 5G commercialization in China and the inception of worldwide research in 6G.Compared with 5G networks, 6G networks will have larger information capacity, higher transmission rate, lower transmission delay, larger number of connected devices, higher spectrum efficiency, higher energy efficiency, and can support applications with higher mobile speed.Therefore, 6G networks will involve many new key technologies and also face many challenges.The background, development, typical applications, performance indicators, network architecture, key technologies and future challenges of 6G were systematically reviewed, which are expected to provide some reference for future 6G networks related research.

    Human activity recognition system based on active learning and Wi-Fi sensing
    Guangzhi ZHAO, Zhipeng ZHOU, Wei GONG, Shaoqing CHEN, Haoquan ZHOU
    2022, 6(1):  44-52.  doi:10.11959/j.issn.2096-3750.2022.00262
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    Human activity recognition system based on deep learning and Wi-Fi sensing has gradually become the mainstream research field and has been developed in recent years.However, related systems heavily rely on training with huge labeled samples to reach a high accuracy, which is labor-intensive and unrealistic for many real-world scenarios.To solve this problem, a system that combines active learning with Wi-Fi based human activity recognition—ALSensing was proposed, which was able to train a well-perform classifier with limited labeled samples.ALSensing was implemented with commercial Wi-Fi devices and evaluated in six real environments.The experimental results show that ALSensing achieves 52.83% recognition accuracy using 3.7% of total training samples, 58.97% recognition accuracy using 15% of total training samples, while the existing full-supervised system reaches 62.19% recognition accuracy.It demonstrates that ALSensing has a similar performance with baseline but requires much less labeled samples.

    Research on deep reinforcement learning based intelligent shop scheduling method
    Zihui LUO, Chengling JIANG, Liang LIU, Xiaolong ZHENG, Huadong MA
    2022, 6(1):  53-64.  doi:10.11959/j.issn.2096-3750.2022.00260
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    The unprecedented prosperity of the industrial internet of things (IIoT) has opened up a new path for the traditional industrial manufacturing model.Intelligent shop scheduling is one of the key technologies to achieve the overall control and flexible production of the whole production process.It requires an effective plan with a minimum makespan to allocate multiple processes and multiple machines for production scheduling.Firstly, the shop scheduling problem was defined as a Markov decision process (MDP), and a shop scheduling model based on the pointer network was established.Secondly, the job scheduling process was regarded as a mapping from one sequence to another, and a new shop scheduling algorithm based on deep reinforcement learning (DRL) was proposed.By analyzing the convergence of the model under different parameter settings, the optimal parameters were determined.Experimental results on different scales of public data sets and actual production data sets show that the proposed DRL algorithm can obtain better performances.

    Res-DNN based signal detection algorithm for end-to-end MIMO systems
    Guoquan LI, Yonghai XU, Jinzhao LIN, Zhengwen HUANG
    2022, 6(1):  65-72.  doi:10.11959/j.issn.2096-3750.2022.00256
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    Deep learning can improve the effect of signal detection by extracting the inherent characteristics of wireless communication data.To solve the tradeoff between the performance and complexity of MIMO system signal detection, an end-to-end MIMO system signal detection scheme based on deep learning was proposed.The encoder and the decoder based on residual deep neural network replace the transmitter and the receiver of the wireless communication system respectively, and they were trained in an end-to-end manner as a whole.Firstly, the features of the input data were extracted by encoder, then the communication model was established and was sent to the zero forcing detector for preliminary detection.Finally, the detection signal was reconstructed through the decoder.Simulation results show that the proposed detection scheme is superior to the same type of algorithm, and the detection performance is significantly better than that of the MMSE detection algorithm at the expense of a certain time complexity.

    WSN clustering routing algorithm based on Cuckoo Search algorithm optimized K-means
    Kailei ZHU, Aijing SUN
    2022, 6(1):  73-81.  doi:10.11959/j.issn.2096-3750.2022.00257
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    In order to extend the lifetime of wireless sensor network (WSN), a clustering routing algorithm for WSN based on Cuckoo Search (CS) algorithm optimized K-means was presented.In the clustering stage, the initial cluster centers were selected by CS algorithm, which make the clustering results of the K-means algorithm more uniform to balance node energy consumption.The remaining energy of the node, the distance from the center of the cluster were comprehensively considered in the cluster election, and the weight according to the remaining energy of the node was dynamically adjusted.In the data communication stage, in order to further balance the load of the cluster head, the remaining energy of the relay node and its load, and the cluster head routing energy consumption were comprehensively considered, CS algorithm was combined to plan routing for the cluster head.The simulation results show that the proposed algorithm is better than LEACH-K, LEACH-improve and DTK-means in terms of energy consumption balance.With the death of the first node as the life cycle of the network, the network lifespan was increased by 173%, 21%, and 6% respectively.The proposed algorithm effectively extending the network life cycle.

    Measurement and modeling of wireless body area network propagation characteristics of indoor environment at 10 GHz
    Qin YANG, Lihua YANG, Lulu REN, Shanhu HUANG, Jiahuan LIU
    2022, 6(1):  82-90.  doi:10.11959/j.issn.2096-3750.2022.00259
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    To explore the feasibility of high-frequency in indoor wireless body area network (WBAN) communication, the propagation characteristics of 10 GHz for WBAN in indoor scenario was given.Based on a large number of measurement data, the path loss, the shadow effect and the root-based delay spread of the 10 GHz were present, and a novel path loss model with the body angle was proposed, which utilizes the body angular factor to correct the path loss caused by the change of body angle.Meanwhile, the influence of receiving antenna at different heights of body on path loss was analyzed.Research results show that the path loss exponent has a quadratic function relationship with the body angle, the relationship between the path loss (PBA) caused by the body angle and the body angle can be expressed by a trigonometric function with a coefficient, which has a monotonously decreasing exponential function relationship with the distance between the receiving and sending ends.In addition, when the body is at different angles, the effect of the receiving ends in the human body on the path loss is smaller than when there is no body rotation angle.The above research results can provide the theoretical and practical basis for the use of 10 GHz indoor wireless body area network in the future.

    Research on elite hierarchical task offloading strategy based on reinforcement learning in edge-cloud collaboration scenario
    Juan FANG, Zhiyuan YE, Mengyuan ZHANG, Jiamei SHI, Ziyi TENG
    2022, 6(1):  91-100.  doi:10.11959/j.issn.2096-3750.2022.00258
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    With the development of 5G and the enrichment of application functions, applications have put forward higher requirements on the computing capabilities of terminal devices.In order to improve the computing capabilities of terminal devices on applications and reduce the processing time of tasks, it is aimed at mobile edge computing environments, a task offloading method for edge-cloud collaboration was proposed,and an elite hierarchical evolutionary algorithm combined with reinforcement learning (RL-EHEA) was designed to perform offloading decisions, so that multiple tasks with dependencies and deadlines compete for computing resources.The simulation experiment results show that, compared with genetic algorithm (GA) and elite genetic algorithm (EGA), RL-EHEA can shorten task processing time and obtain better resource allocation strategy.

    Robust optimization of air based relay for internet of things based on UAV
    Wei WANG, Renqian GU, Li3 PENG, Jijun ZHAO, Zhongcheng WEI, Cunxi CHANG
    2022, 6(1):  101-112.  doi:10.11959/j.issn.2096-3750.2022.00261
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    Faced with the need of key regional information transmission in the emergency situation where the perception network lacks of ground base stations, considered about the uncertainty of spatial positioning of emergency internet of things (eIoT) nodes, a robust optimization method for air-based relay of eIoT based on unmanned aerial vehicle (UAV) was proposed.Firstly, the system modeling of this kind of eIoT was carried out.Secondly, according to the fact that the non-convex and nonlinear model has a great correlation with the positioning accuracy of the ground-based eIoT equipment and the tiny disturbance of the positioning information can lead to the invalid solution of the model, the system model was relaxed and the uncertainty description of the location data of the eIoT equipment was introduced, Then the robust equivalent model of the low altitude UAV relay communication power optimization problem was obtained.Thirdly, the model solving algorithm was given.Finally, the effectiveness and robustness of the proposed method were verified from the deployment of UAV and communication energy consumption.At the same time, the factors effecting the effectiveness of the proposed method were analyzed.

    Research on water quality data classification based on weighted Naive Bayes
    Zhihao FANG, Zhengquan LI, Mingwei ZHANG
    2022, 6(1):  113-122.  doi:10.11959/j.issn.2096-3750.2022.00255
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    In order to better implement the water environmental management policies, water quality evaluation is the basic step, that is to reasonably divide it into specific water quality category according to multiple water quality parameters in a certain water area.Aimed at this problem, an improved Naive Bayes classification method was proposed, which endowed different attributes with different weights, weakened the assumption of Naive Bayes conditional independence, and made the classification result closer to the actual category.Firstly, referred to the data released by the national surface water quality automatic monitoring station, 500 water quality data were selected as samples, and an evaluation system with four indicators was established, including dissolved oxygen, permanganate index, ammonia nitrogen and total phosphorus.And then, the improved Naive Bayes classification method was used to learn and evaluate the samples, and its classification performance by the five fold cross validation method was verified.The results show that the accuracy, precision, recall and F1 value of the improved Naive Bayes classification method reach 96.0%, 95.9%, 93.8% and 94.8% respectively, with higher performance index of water quality data classification compared with other Naive Bayes classification method, which can provide some reference for the problem of water quality data classification encountered in actual engineering.

    Service and Application
    Study of international standard ISO/IEC 30144: 2020 applied in intelligent substation auxiliary monitoring
    Mingjuan WU, Shuyi CHEN, Haitao LIU
    2022, 6(1):  123-132.  doi:10.11959/j.issn.2096-3750.2022.00254
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    Internet of things and wireless sensor network technology has been gradually applied in substation monitoring, as one of the important means of substation automation.The international standard ISO/IEC 30144: 2020 put forward the system architecture, communication architecture and system requirements for wireless sensor network supporting substation.In order to promote the standardized IoT-based smart substation application, taking the standard as a reference, the background and main contents of the international standard were expound, and examples of sensor node types, network communication interfaces and sensor network monitoring platform supporting the substation in the smart substation were given, so as to provide an instantiation method for the application and implementation of the international standard, which is conducive to the realization of standardized, refined and unmanned substation supervision.


Copyright Information
Quarterly,started in 2017
Cpmpetent Unit:Ministry of Industry and Information Technology of the People's Republic of China
Sponsor:Posts & Telecom Press Co.,Ltd.
Editor:Editor Board of Chinese Journal on Internet of Things
Editor-in-Chief:YIN Hao
Executive Editor-in-Chief:ZHU Hongbo
Deputy Editor-in-Chief:LIU Hualu
Director:WU Nada
Address:F8,You Dian Publisher Building,N.11,Chengshousi Road,Fengtai District,Beijing 100078,PR China
Tel:010-81055476
010-81055691
E-mail:wlwxb@bjxintong.com.cn
ISSN 2096-3750
CN 10-1491/TP
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