A Review of Artificial Intelligence Applications in Contemporary Computer Network Technologies

Rapid advancement in science and technology has seen computer network technology being upgraded constantly, and computer technology, in particular, has been applied more and more extensively, which has brought convenience to people’s lives. The number of people using the internet around the globe has also increased significantly, exerting a profound influence on artificial intelligence. Further, the constant upgrading and development of artificial intelligence has led to the continuous innovation and improvement of computer technology. Countries around the world have also registered an increase in investment, paying more attention to artificial intelligence. Through an analysis of the current development situation and the existing applications of artificial intelligence, this paper explicates the role of artificial intelligence in the face of the unceasing expansion of computer network technology.

Internet of Cultural Things: Current Research, Challenges and Opportunities

Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural services,cultural resources,and cultural platforms,bringing individuals with richer humanistic experience,increasing economic benefits for the cultural sector,and promoting the development of cultural heritage protection and education.At present,IoCT has received widespread attention in both industry and academia.To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications,this survey provides a comprehensive overview of the IoCT components and key technologies.A comparison study of representative IoCT systems is presented according to their applicability.A general platform architecture of IoCT is proposed to link cultural objects with the internet and human.Finally,open issues for research challenges and future opportunities of IoCT are also studied in this paper.

A Review of Road Accidents Detection through Wireless Technology—5G, MIMO and Internet of Things

Road transport is been used for moving people and all kinds of goods throughout the world. However, it is one mode of transportation that is prone to accidents and it faces a plethora of never-ending challenges, such as the frequent loss of lives and valuables when accident occurs. The best course of action to handle these issues is to set up an autonomous incident detection system using wireless communication, 5G technologies and the Internet of Things. IoT is a seamless technology that increases the connectivity between humans and machines. It is web-based, and improves communication between vehicle to vehicle, vehicle to infrastructures, transfer of data and information to predict incident occurrences through various networks and frameworks such as eCall, OneM2M and integration of mobile broadband. Additionally, internet of things is being adopted for public safety;for instance, it can speed up first responders’ response times to situations by displaying the best routes to a scene of an accident. The rapid development of 5G is happening in parallel with developments of internet of things (IoT), artificial intelligence (AI), and smart platforms for novel applications such as mission-critical communications. 5G is a new generation technology that operates on the Ultra High Spectrum Band UHSB. It is an innovation that uses the pedestrians-vehicle-road-cloud, and the communication between vehicle locations and temperature of high-quality connection. It is essential for intelligent transport systems because it allows for information sharing, prediction of incidences as safety is the primary concern of road transport. This review examines accident detection through 5G technology, integrated mobile broadband, and multiple inputs multiple outputs (MIMO) wireless system. Finally, we conclude by examining recent technology, challenges, present and future research trends.

A survey on communication protocols and performance evaluations for Internet of Things

The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.

An improved pulse coupled neural networks model for semantic IoT

In recent years,the Internet of Things(IoT)has gradually developed applications such as collecting sensory data and building intelligent services,which has led to an explosion in mobile data traffic.Meanwhile,with the rapid development of artificial intelligence,semantic communication has attracted great attention as a new communication paradigm.However,for IoT devices,however,processing image information efficiently in real time is an essential task for the rapid transmission of semantic information.With the increase of model parameters in deep learning methods,the model inference time in sensor devices continues to increase.In contrast,the Pulse Coupled Neural Network(PCNN)has fewer parameters,making it more suitable for processing real-time scene tasks such as image segmentation,which lays the foundation for real-time,effective,and accurate image transmission.However,the parameters of PCNN are determined by trial and error,which limits its application.To overcome this limitation,an Improved Pulse Coupled Neural Networks(IPCNN)model is proposed in this work.The IPCNN constructs the connection between the static properties of the input image and the dynamic properties of the neurons,and all its parameters are set adaptively,which avoids the inconvenience of manual setting in traditional methods and improves the adaptability of parameters to different types of images.Experimental segmentation results demonstrate the validity and efficiency of the proposed self-adaptive parameter setting method of IPCNN on the gray images and natural images from the Matlab and Berkeley Segmentation Datasets.The IPCNN method achieves a better segmentation result without training,providing a new solution for the real-time transmission of image semantic information.

A Workable Solution for Reducing the Large Number of Vehicle and Pedestrian Accidents Occurring on a Yellow Light

Traffic intersections are incredibly dangerous for drivers and pedestrians. Statistics from both Canada and the U.S. show a high number of fatalities and serious injuries related to crashes at intersections. In Canada, during 2019, the National Collision Database shows that 28% of traffic fatalities and 42% of serious injuries occurred at intersections. Likewise, the U.S. National Highway Traffic Administration (NHTSA) found that about 40% of the estimated 5,811,000 accidents in the U.S. during the year studied were intersection-related crashes. In fact, a major survey by the car insurance industry found that nearly 85% of drivers could not identify the correct action to take when approaching a yellow traffic light at an intersection. One major reason for these accidents is the “yellow light dilemma,” the ambiguous situation where a driver should stop or proceed forward when unexpectedly faced with a yellow light. This situation is even further exacerbated by the tendency of aggressive drivers to inappropriately speed up on the yellow just to get through the traffic light. A survey of Canadian drivers conducted by the Traffic Injury Research Foundation found that 9% of drivers admitted to speeding up to get through a traffic light. Another reason for these accidents is the increased danger of making a left-hand turn on yellow. According to the National Highway Traffic Safety Association (NHTSA), left turns occur in approximately 22.2% of collisions—as opposed to just 1.2% for right turns. Moreover, a study by CNN found left turns are three times as likely to kill pedestrians than right turns. The reason left turns are so much more likely to cause an accident is because they take a driver against traffic and in the path of oncoming cars. Additionally, most of these left turns occur at the driver’s discretion—as opposed to the distressingly brief left-hand arrow at busy intersections. Drive Safe Now proposes a workable solution for reducing the number of accidents occurring during a yellow light at intersections. We believe this fairly simple solution will save lives, prevent injuries, reduce damage to public and private property, and decrease insurance costs.

Mi-IoT智能互联设备在实验室日常管理中的应用

随着物联网和智能家居技术的蓬勃发展,实验室作为科研创新的重要场所,其智能化水平对于提高科研效率、优化实验环境至关重要。米家作为智能家居领域的知名品牌,其智能设备在实验室中的应用潜力巨大。以米家智能设备为例,探讨其在实验室中的应用管理,旨在提高实验室的智能化水平,优化实验环境,提升测试效率。首先,概述了智能设备的基本概念;然后,详细分析了米家智能设备在实验室中的具体应用;接着,探讨了智能设备的集成与管理平台;最后,对应用效果进行了展望。

BIM-IoT技术在轨道交通工程智能化施工中的应用研究

建筑信息模型(BIM)和物联网(IoT)是建筑行业智能化转型升级的关键技术,通过在施工现场部署传感器和设备,BIM-IoT技术实现了对施工过程中包括实时监测材料运输、设备使用情况和施工进度等实时监测和数据采集。该技术还支持对施工人员的实时管理和安全监控,如人员考勤记录和视频监控系统的应用。基于IoT技术,通过数据分析和算法,实现资源的准确预测和合理分配,提高施工效率和质量。最后本文总结了BIM-IoT在实际应用过程中的重难点,为同类型工程提供参考。

基于NB-IoT的用电信息采集系统设计与研究

随着工业物联网(IoT)的兴起,电力行业纷纷采纳IoT技术对终端电表进行升级。基于窄带物联网(NB-IoT)的IoT通信技术可实现对电能表的信息采集。从NB-IoT通信技术出发,介绍了国内外的发展水平、开展进度和组网技术,依据对用电信息智能采集的需求分析了系统总体架构,并且着重讨论了电能表数据采集功能的开发和扩展。通过合理设计终端电表的软件与硬件部分,实现了终端电表的高效通信功能。创新性地采用嵌入式用户身份识别模块(eSIM)卡进行通信,更方便、快捷地对电能资源进行资产统一管理。研究结果表明,借助NB-IoT网络通信实现了终端电表的观察到达时间差定位,满足了对终端电表位置信息的查询需求和用电信息采集需求。该设计实现的强链接、高覆盖、低成本的智能终端电表网络,对电力行业的场联网技术研究具有实际的指导意义和应用价值。

Portable and Efficient Implementation of CRYSTALS-Kyber Based on WebAssembly

With the rapid development of quantum computers capable of realizing Shor’s algorithm,existing public key-based algorithms face a significant security risk.Crystals-Kyber has been selected as the only key encapsulation mechanism(KEM)algorithm in the National Institute of Standards and Technology(NIST)Post-Quantum Cryptography(PQC)competition.In this study,we present a portable and efficient implementation of a Crystals-Kyber post-quantum KEM based on WebAssembly(Wasm),a recently released portable execution framework for high-performance web applications.Until now,most Kyber implementations have been developed with native programming languages such as C and Assembly.Although there are a few previous Kyber implementations based on JavaScript for portability,their performance is significantly lower than that of implementations based on native programming languages.Therefore,it is necessary to develop a portable and efficient Kyber implementation to secure web applications in the quantum computing era.Our Kyber software is based on JavaScript and Wasm to provide portability and efficiency while ensuring quantum security.Namely,the overall software is written in JavaScript,and the performance core parts(secure hash algorithm-3-based operations and polynomial multiplication)are written in Wasm.Furthermore,we parallelize the number theoretic transform(NTT)-based polynomial multiplication using single instruction multiple data(SIMD)functionality,which is available in Wasm.The three steps in the NTT-based polynomial multiplication have been parallelized with Wasm SIMD intrinsic functions.Our software outperforms the latest reference implementation of Kyber developed in JavaScript by×4.02(resp.×4.32 and×4.1),×3.42(resp.×3.52 and×3.44),and×3.41(resp.×3.44 and×3.38)in terms of key generation,encapsulation,and decapsulation on Google Chrome(resp.Firefox,and Microsoft Edge).As far as we know,this is the first software implementation of Kyber with Wasm technology in the web environment.

基于AIOT家居装饰型人工智能2.1音响系统研制

产品基于AIOT技术,面向智能家居应用领域,由人工智能语音音源系统、2.1音响系统、沙发背景墙创意装饰系统、航天主题装饰等组成;产品利用人工智能语音芯片作为2.1音响系统信号源,选用I2S数字音频总线技术,设计增加智能语音芯片AUX音频输出功能,与个性化定制的音响系统相连,形成智能音响系统,并将智能音响系统与沙发背景墙创意装饰工艺品相融合,重组智能家居生态,研制成新一代装饰型智能2.1音响系统。

构建节点信誉度的跨域移动节点安全认证方法

为增强物联网架构的安全性,降低数据传输风险,提出一种新的跨域移动节点安全认证方法。分析物联网节点的物理特征与信任特征,利用网络模块、信誉模块和服务模块搭建信任体系;通过信任初始化、信任更新等过程建立信任模型,计算不同节点之间的信誉程度,以信誉值为安全认证的依据;构建具有应用层、合约层、激励层等结构的区块链架构,引入加密算法,经过不同域服务器之间的相互认证,解析区块链证书是否有效,若有效则认为认证成功;反之,认证失败。实验结果表明,无论网络状态如何,所提方法下节点之间的通信成功率均较高,并且能减少计算开销,提高认证效率,有效加强了物联网信息传输的安全性。

物流企业全面预算管理在物联网技术发展中的应用研究

随着全球经济的快速发展和市场竞争的日益激烈,物流行业作为现代经济的重要支柱产业之一,承担着连接生产、流通和消费等各个环节的关键责任。在市场环境瞬息万变和客户需求日益多样化的背景下,传统的物流管理模式已难以满足当前日益复杂的市场需求和管理挑战,物流企业急需采用新技术来提升管理水平、降低成本、提高效率,以适应快速变化和竞争激烈的市场环境。文章旨在深入探讨物联网技术在物流全面预算管理中的应用现状和发展趋势,分析其对物流企业管理模式和运营效率的影响,以期为物流行业的可持续发展提供借鉴和参考。

基于项目式教学的物联网课程思政建设

面向物联网技术应用背景,以课程思政育人为引领,探讨了基于建构主义教育理论的项目式教学框架。在课程教学实践中,注重学生工程应用和创新能力培养,通过融入思政元素和引入工程应用案例,提升学生综合素养。在教学过程中,通过小组项目式合作和自主知识框架构建,培养学生创新、合作和独立思考能力。教学成果表明,本课程融合思政与技术教育有效提升了学生社会责任感和创新能力,为培养新工科背景下的复合型人才提供了有益的探索和实践路径。

智慧校园中物联网技术的应用研究

文章分析了智慧校园中物联网(Internet of Things,IoT)技术的应用场景和需求,介绍了智慧校园物联网技术系统架构及物联网的关键技术,并从提高校园服务水平、管理水平、教育教学支持水平等方面,探讨了物联网技术在智慧校园中的应用,以期为智慧校园建设提供有益的参考。

Hadoop平台下粒子滤波结合改进ABC算法的IoT大数据特征选择方法

针对现有物联网大数据特征选择算法计算效率低下、可扩展性不高的问题,提出一种基于改进人工蜂群(ABC)选择特征的系统架构,该架构包含四层体系,可以高效地聚合有效数据,剔除不需要的数据。整个系统是基于Hadoop平台、MapReduce以及改进ABC算法的。改进ABC算法用于选择特征,而MapReduce则由并行算法支持,该算法可高效处理大数据集。该系统使用MapReduce工具实现,并利用粒子滤波来消除噪声。将提出的算法与同类方法进行比较,并通过使用十个不同的数据集对效率、准确性和吞吐量进行评估。结果表明,相比其他几种较新的算法,提出的算法在选择特征时更具可扩展性和高效性。

NB-IoT技术特性及应用

传统的物联网通信技术3G、WI-FI等,虽能满足一般的通信需求,但其功耗高,成本高等劣势成为限制物联网技术发展的因素。与此同时,NB-IoT技术的优势逐渐显现,可以满足物联网的不同需求,成为相关开发人员进行产品研发的首要选择。NB-IoT全称为基于蜂窝的窄带物联网,是近几年新兴的一种物联网通信技术,同时也成为了万物互联网的一个重要分支。该技术相比于4G技术、WI-FI技术、GPRS技术等,具有低功耗、低成本、广覆盖、海量连接等技术特点,并可直接部署于GSM网络,UMTS网络或LTE网络。为了更全面地了解NB-IoT技术,对NB-IoT技术的基本架构以及关键技术进行阐述,并结合其他物联网通信技术进行对比分析,重点剖析其在农业应用以及智能交通领域的典型案例,并探讨了该技术在未来发展过程中所面临的挑战。

智慧物联网新技术在智慧仓建设中的应用研究

随着物联网和人工智能技术的不断发展,智慧物联网新技术在智慧仓储建设中的应用越来越广泛。智慧仓储作为物流行业的重要组成部分,对提高物流效率和服务质量具有重要意义。智慧物联网新技术的应用,可以为智慧仓储建设提供更加智能化、高效化的解决方案,进一步提高仓储管理的效率和准确性。文章旨在探讨智慧物联网新技术在智慧仓储建设中的应用,以期为相关领域的研究和实践提供一定的参考。

关于NB-IoT物联网覆盖增强技术的分析

我国科学技术不断地发展进步,在很大程度上推动了覆盖增强技术的发展进程。文章主要立足于NB-IoT物联网覆盖增强技术,展开了深入的研究与分析,以此期望为我国今后在对于NB-IoT物联网覆盖增强技术研究问题上,提供一些参考性的建议。

NB-IoT低速率窄带物联网通信技术现状及发展趋势

NB-IoT作为现阶段我国物联网结构体系中的重要分支,凭借自身在蜂窝网络结构技术以及运行成本等方面的优势与商业价值,逐渐成为物流网发展的的主流。本文以NB-IoT低速率窄宽带物联网技术为研究重点,深入分析发展现状及方向,为其在实践中的有效应用提供必要的参考。