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Energy-aware multipath routing in WSN using improved invasive weed elephant herd optimization 基于改进入侵杂草象群优化的WSN能量感知多路径路由
Pub Date : 2022-02-04 DOI: 10.1108/ijpcc-09-2021-0229
Hingmire Vishal Sharad, Santosh R. Desai, Kanse Yuvraj Krishnrao
PurposeIn a wireless sensor network (WSN), the sensor nodes are distributed in the network, and in general, they are linked through wireless intermediate to assemble physical data. The nodes drop their energy after a specific duration because they are battery-powered, which also reduces network lifetime. In addition, the routing process and cluster head (CH) selection process is the most significant one in WSN. Enhancing network lifetime through balancing path reliability is more challenging in WSN. This paper aims to devise a multihop routing technique with developed IIWEHO technique.Design/methodology/approachIn this method, WSN nodes are simulated originally, and it is fed to the clustering process. Meanwhile, the CH is selected with low energy-based adaptive clustering model with hierarchy (LEACH) model. After CH selection, multipath routing is performed by developed improved invasive weed-based elephant herd optimization (IIWEHO) algorithm. In addition, the multipath routing is selected based on certain fitness functions like delay, energy, link quality and distance. However, the developed IIWEHO technique is the combination of IIWO method and EHO algorithm.FindingsThe performance of developed optimization method is estimated with different metrics, like distance, energy, delay and throughput and achieved improved performance for the proposed method.Originality/valueThis paper presents an effectual multihop routing method, named IIWEHO technique in WSN. The developed IIWEHO algorithm is newly devised by incorporating EHO and IIWO approaches. The fitness measures, which include intra- and inter-distance, delay, link quality, delay and consumption of energy, are considered in this model. The proposed model simulates the WSN nodes, and CH selection is done by the LEACH protocol. The suitable CH is chosen for transmitting data through base station from the source to destination. Here, the routing system is devised by a developed optimization technique. The selection of multipath routing is carried out using the developed IIWEHO technique. The developed optimization approach selects the multipath depending on various multi-objective functions.
在无线传感器网络(WSN)中,传感器节点分布在网络中,通常通过无线中间连接起来,以组装物理数据。节点在一段特定的时间后能量下降,因为它们是电池供电的,这也缩短了网络的寿命。其中路由过程和簇头选择过程是WSN中最重要的两个过程。在无线传感器网络中,通过平衡路径可靠性来提高网络生存期是一个比较具有挑战性的问题。本文的目的是利用已开发的IIWEHO技术设计一种多跳路由技术。设计/方法/方法在该方法中,对WSN节点进行原始模拟,并将其输入到聚类过程中。同时,采用低能量自适应分层聚类模型(LEACH)选择CH。选择CH后,采用改进的基于入侵杂草的象群优化(IIWEHO)算法进行多路径路由。此外,根据时延、能量、链路质量和距离等适应度函数选择多径路由。然而,所开发的IIWEHO技术是IIWO方法和EHO算法的结合。结果采用距离、能量、延迟和吞吐量等指标对优化方法的性能进行了评价,改进了优化方法的性能。提出了一种有效的多跳路由方法,即无线传感器网络中的IIWEHO技术。本文提出的IIWEHO算法是将EHO和IIWO方法结合而成的新算法。该模型考虑了距离内和距离间、时延、链路质量、时延和能量消耗等适应度度量。该模型模拟WSN节点,并通过LEACH协议进行CH选择。选择合适的信道通过基站将数据从源传输到目的。在这里,路由系统是由一种先进的优化技术设计。采用开发的IIWEHO技术进行多径路由选择。所提出的优化方法根据不同的多目标函数选择多路径。
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引用次数: 0
FHSA: fractional harmony search algorithm for polyphase code design in radar signal processing 雷达信号处理中多相码设计的分数阶和谐搜索算法
Pub Date : 2022-01-27 DOI: 10.1108/ijpcc-05-2021-0120
Sirasani Srinivasa Rao, V. SubbaRamaiah
PurposeThe purpose of this research is to design and develop a technique for polyphase code design for the radar system.Design/methodology/approachThe proposed fractional harmony search algorithm (FHSA) performs the polyphase code design. The FHSA binds the properties of the harmony search algorithm and the fractional theory. An optimal fitness function based on the coherence and the autocorrelation is derived through the proposed FHSA. The performance metrics such as power, autocorrelation and cross-correlation measure the efficiency of the algorithm.FindingsThe performance metrics such as power, autocorrelation and cross-correlation is used to measure the efficiency of the algorithm. The simulation results show that the proposed optimal phase code design with FHSA outperforms the existing models with 1.420859, 4.09E−07, 3.69E−18 and 0.000581 W for the fitness, autocorrelation, cross-correlation and power, respectively.Originality/valueThe proposed FHSA for the design and development of the polyphase code design is developed for the RADAR is done to reduce the effect of the Doppler shift.
目的设计和开发一种雷达系统多相码设计技术。设计/方法/方法提出的分数阶和谐搜索算法(FHSA)进行多相代码设计。FHSA结合了和谐搜索算法和分数理论的特性。通过所提出的FHSA,导出了基于相干性和自相关性的最优适应度函数。功率、自相关和互相关等性能指标衡量了算法的效率。结果采用功率、自相关和互相关等性能指标来衡量算法的效率。仿真结果表明,基于FHSA的最优相位码设计在适应度、自相关、互相关和功率方面均优于现有模型,分别为1.420859 W、4.09E−07 W、3.69E−18 W和0.000581 W。原创性/价值本文提出的多相码设计和开发的FHSA是为了减少多普勒频移的影响而开发的。
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引用次数: 0
Automatic diseases detection and classification of EEG signal with pervasive computing using machine learning 基于机器学习的普适计算脑电信号疾病自动检测与分类
Pub Date : 2022-01-26 DOI: 10.1108/ijpcc-09-2021-0216
U. Rajashekhar, Neelappa, M. HarishH.
PurposeThe natural control, feedback, stimuli and protection of these subsequent principles founded this project. Via properly conducted experiments, a multilayer computer rehabilitation system was created that integrated natural interaction assisted by electroencephalogram (EEG), which enabled the movements in the virtual environment and real wheelchair. For blind wheelchair operator patients, this paper involved of expounding the proper methodology. For educating the value of life and independence of blind wheelchair users, outcomes have proven that virtual reality (VR) with EEG signals has that potential.Design/methodology/approachIndividuals face numerous challenges with many disorders, particularly when multiple dysfunctions are diagnosed and especially for visually effected wheelchair users. This scenario, in reality, creates in a degree of incapacity on the part of the wheelchair user in terms of performing simple activities. Based on their specific medical needs, confined patients are treated in a modified method. Independent navigation is secured for individuals with vision and motor disabilities. There is a necessity for communication which justifies the use of VR in this navigation situation. For the effective integration of locomotion besides, it must be under natural guidance. EEG, which uses random brain impulses, has made significant progress in the field of health. The custom of an automated audio announcement system modified to have the help of VR and EEG for the training of locomotion and individualized interaction of wheelchair users with visual disability is demonstrated in this study through an experiment. Enabling the patients who were otherwise deemed incapacitated to participate in social activities, as the aim was to have efficient connections.FindingsTo protect their life straightaway and to report all these disputes, the military system should have high speed, more precise portable prototype device for nursing the soldier health, recognition of solider location and report about health sharing system to the concerned system. Field programmable gate array (FPGA)-based soldier’s health observing and position gratitude system is proposed in this paper. Reliant on heart rate which is centered on EEG signals, the soldier’s health is observed on systematic bases. By emerging Verilog hardware description language (HDL) programming language and executing on Artix-7 development FPGA board of part name XC7ACSG100t the whole work is approved in a Vivado Design Suite. Classification of different abnormalities and cloud storage of EEG along with the type of abnormalities, artifact elimination, abnormalities identification based on feature extraction, exist in the segment of suggested architecture. Irregularity circumstances are noticed through developed prototype system and alert the physically challenged (PHC) individual via an audio announcement. An actual method for eradicating motion artifacts from EEG signals that have
这些后续原则的自然控制、反馈、刺激和保护建立了这个项目。通过适当的实验,建立了一个结合自然交互和脑电图辅助的多层计算机康复系统,实现了虚拟环境和真实轮椅的运动。针对盲人轮椅操作患者,本文阐述了正确的方法。在教育盲人轮椅使用者的生命价值和独立性方面,研究结果证明,带有脑电图信号的虚拟现实(VR)具有这种潜力。设计/方法/方法个人面临着许多障碍的挑战,特别是当多种功能障碍被诊断出来时,尤其是对视力受损的轮椅使用者。实际上,这种情况在一定程度上造成了轮椅使用者在进行简单活动方面的丧失能力。根据病人的特殊医疗需要,用一种改良的方法治疗禁闭病人。有视力和运动障碍的人可以独立导航。有必要进行交流,这证明在这种导航情况下使用VR是合理的。此外,运动的有效整合必须在自然的引导下进行。脑电图利用随机脑脉冲,在健康领域取得了重大进展。本研究通过实验验证了一种经过VR和EEG技术改造的自动音频广播系统对视觉障碍轮椅使用者运动和个性化互动的训练。使那些被认为是无行为能力的病人能够参与社会活动,因为目的是建立有效的联系。为了保护士兵的生命安全,及时报告这些纠纷,军事系统应该有高速、更精确的便携式士兵健康护理原型装置,识别士兵的位置,并将健康共享系统报告给有关系统。提出了一种基于现场可编程门阵列(FPGA)的士兵健康观测与位置感激系统。依靠以脑电图信号为中心的心率,可以系统地观察士兵的健康状况。通过新兴的Verilog硬件描述语言(HDL)编程语言,在部件名称为XC7ACSG100t的Artix-7开发FPGA板上执行,整个工作在Vivado Design Suite中完成。在建议架构的分段中存在不同异常的分类和脑电图的云存储以及异常类型、伪影消除、基于特征提取的异常识别。通过开发的原型系统可以注意到不正常的情况,并通过音频通知提醒身体障碍(PHC)个人。建立了一种消除PHC患者大脑异常脑电图信号中运动伪影的实际方法,所建立的系统是一种可以传递脑信号变化强度差异的便携式设备。首先提取脑电信号,去除不需要的伪信号,然后通过离散小波变换挖掘结构,这是完成伪信号删除的两个阶段。当使用隐马尔可夫模型(HMM)和高斯混合模型(GMM)结合提取特征时,可以使用称为多速率支持向量机分类器的机器学习算法来注意和识别信号中的异常。这些结果信号在存储设备中受到保护并传送给控制器,用于对盲人所采取的行动进行有能力的声明。假装每天的运动时间表可以让假装的脑电图信号被捕捉到。针对计划系统的验证,该数据库可与大量记录的脑电图信号一起使用和延续。定量分析表明,投影策略在恢复原始脑电信号的theta、delta、alpha和beta复核方面表现较好,且改变较少,脑电信号信噪比较高。投影法采用Verilog HDL和MATLAB软件进行结果的生成和授权,提高了结果的准确性。由于所取得的结果表明,信噪比提高32%,均方误差(MSE)提高14%,异常识别提高65%,因此在FPGA上对标准脑电信号数据集的设计进行了有效的验证和验证。该系统在异常识别方面具有速度快、精度高的特点,可用于军事应用。提出了一种基于fpga的士兵健康观察与位置感激系统。
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引用次数: 2
Design and implementation of energy-aware cross-layer routing protocol for wearable body area network 可穿戴体域网络能量感知跨层路由协议的设计与实现
Pub Date : 2022-01-13 DOI: 10.1108/ijpcc-02-2021-0055
M. Vadlamudi, Asdaque Hussain
PurposeA wireless body area network (WBAN) plays a crucial role in the health-care domain. With the emergence of technologies like the internet of things, there is increased usage of WBAN for providing quality health services. With wearable devices and sensors associated with human body, patient’s vital signs are captured and sent to doctor. The WBAN has number of sensor nodes that are resource constrained. The communications among the nodes are very crucial as human health information is exchanged. The purpose of this paper aims to have Quality of Service (QoS) with energy aware and control overhead aware. Maximizing network lifetime is also essential for the improved quality in services. There are many existing studies on QoS communications in WBAN.Design/methodology/approachIn this paper, with the aim of energy-efficient WBAN for QoS, a cross-layer routing protocol is designed and implemented. A cross-layer routing protocol that is ad hoc on-demand distance vector (AODV)-based, energy and control overhead-aware (AODV-ECOA) is designed and implemented for energy-efficient routing in WBAN. The cross-layer design that involves multiple layers of open systems interconnection reference model, which will improve energy efficiency and thus QoS.FindingsImplementation is simulated using the network simulator tool, i.e. NS-2. The proposed cross-layer routing protocol AODV-ECOA shows least bandwidth requirement by control packets, leading to less control overhead, highest packet delivery ratio and energy efficiency. The experimental results revealed that AODV-ECOA shows better performance over existing protocols such as AODV and POLITIC.Originality/valueAn efficient control overhead reduction algorithm is proposed for reducing energy consumption further and improves performance of WBAN communications to realize desired QoS.
目的无线体域网络(WBAN)在医疗保健领域发挥着至关重要的作用。随着物联网等技术的出现,无线宽带网络越来越多地用于提供高质量的医疗服务。通过与人体相关的可穿戴设备和传感器,捕捉患者的生命体征并发送给医生。WBAN中存在大量资源受限的传感器节点。节点之间的通信对于人类健康信息的交换至关重要。本文的目的是实现具有能量感知和控制开销感知的服务质量(QoS)。最大化网络生命周期对于提高服务质量也是必不可少的。目前已有很多关于WBAN中QoS通信的研究。设计/方法/方法本文以高效节能的无线局域网为目标,设计并实现了一种跨层路由协议。设计并实现了一种基于自组织按需距离矢量(AODV)、能量和控制开销感知(AODV- ecoa)的跨层路由协议,以实现无线宽带网络中的节能路由。跨层设计涉及多层开放系统互连参考模型,这将提高能源效率,从而提高QoS。使用网络模拟器工具(即NS-2)对查找实现进行模拟。所提出的跨层路由协议AODV-ECOA对控制数据包的带宽需求最小,从而实现了控制开销少、数据包分发率高和能效高的目标。实验结果表明,AODV- ecoa比现有的AODV协议和policy协议具有更好的性能。为了进一步降低WBAN通信的能耗,提高WBAN通信的性能,实现期望的QoS,提出了一种有效的控制开销降低算法。
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引用次数: 2
Efficient techniques of fractional-N PLL for pervasive wireless applications 用于普及无线应用的高效分数n锁相环技术
Pub Date : 2022-01-05 DOI: 10.1108/ijpcc-07-2021-0159
M. Azeem, U. R. Nelakuditi
PurposeThe purpose of this paper to ensure the rapid developments in the radio frequency wireless technology, the synthesis of frequencies for pervasive wireless applications is crucial by implementing the design of low voltage and low power Fractional-N phase locked loop (PLL) for controlling medical devices to monitor remotely patients.Design/methodology/approachThe developments urge a technique reliable to phase noise in designing fractional-N PLL with a new eight transistor phase frequency detector and a good linearized charge pump (CP) for speed of operation with minimum mismatches.FindingsIn applications for portable wireless devices, by proposing a new phase-frequency detector with the removal of dead, blind zones and a modified CP to minimize the mismatch of currents.Originality/valueThe results are simulated in 45 nm complementary metal oxide semiconductor generic process design kit (GPDK) technology in cadence virtuoso. The phase noise of the proposed Fractiona-N phase locked loop has–93.18, –101.4 and –117 dBc/Hz at 10 kHz, 100 kHz and 1 MHz frequency offsets, respectively, and consumes 3.3 mW from a 0.45 V supply.
为了保证射频无线技术的快速发展,实现低电压、低功率分数n锁相环(PLL)控制医疗设备远程监测患者的设计,频率合成是普及无线应用的关键。设计/方法/方法在设计分数n锁相环时,需要一种可靠的相位噪声检测技术,该技术采用新的八晶体管相位频率检测器和良好的线性化电荷泵(CP),以实现最小失配的操作速度。在便携式无线设备的应用中,提出了一种新的相位频率检测器,该检测器消除了死区、盲区和改进的CP,以最大限度地减少电流的不匹配。结果在cadence virtuoso中的45 nm互补金属氧化物半导体通用工艺设计套件(GPDK)技术中进行了模拟。在10 kHz、100 kHz和1 MHz频率偏置时,所提出的分数阶n锁相环的相位噪声分别为- 93.18、-101.4和-117 dBc/Hz,并在0.45 V电源下消耗3.3 mW。
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引用次数: 0
An optimized deep learning-based trust mechanism In VANET for selfish node detection 一种优化的基于深度学习的VANET自利节点检测信任机制
Pub Date : 2021-12-31 DOI: 10.1108/ijpcc-09-2021-0239
N. Jyothi, Rekha Patil
PurposeThis study aims to develop a trust mechanism in a Vehicular ad hoc Network (VANET) based on an optimized deep learning for selfish node detection.Design/methodology/approachThe authors built a deep learning-based optimized trust mechanism that removes malicious content generated by selfish VANET nodes. This deep learning-based optimized trust framework is the combination of the Deep Belief Network-based Red Fox Optimization algorithm. A novel deep learning-based optimized model is developed to identify the type of vehicle in the non-line of sight (nLoS) condition. This authentication scheme satisfies both the security and privacy goals of the VANET environment. The message authenticity and integrity are verified using the vehicle location to determine the trust level. The location is verified via distance and time. It identifies whether the sender is in its actual location based on the time and distance.FindingsA deep learning-based optimized Trust model is used to detect the obstacles that are present in both the line of sight and nLoS conditions to reduce the accident rate. While compared to the previous methods, the experimental results outperform better prediction results in terms of accuracy, precision, recall, computational cost and communication overhead.Practical implicationsThe experiments are conducted using the Network Simulator Version 2 simulator and evaluated using different performance metrics including computational cost, accuracy, precision, recall and communication overhead with simple attack and opinion tampering attack. However, the proposed method provided better prediction results in terms of computational cost, accuracy, precision, recall, and communication overhead than other existing methods, such as K-nearest neighbor and Artificial Neural Network. Hence, the proposed method highly against the simple attack and opinion tampering attacks.Originality/valueThis paper proposed a deep learning-based optimized Trust framework for trust prediction in VANET. A deep learning-based optimized Trust model is used to evaluate both event message senders and event message integrity and accuracy.
本研究旨在开发一种基于优化深度学习的车辆自组织网络(VANET)信任机制,用于自私节点检测。设计/方法/方法作者构建了一个基于深度学习的优化信任机制,该机制可以消除自私VANET节点产生的恶意内容。该基于深度学习的优化信任框架结合了基于深度信念网络的红狐优化算法。提出了一种基于深度学习的非视线状态下车辆类型识别优化模型。这种身份验证方案同时满足VANET环境的安全和隐私目标。使用车辆位置验证消息的真实性和完整性,以确定信任级别。位置通过距离和时间来验证。它根据时间和距离来识别发送者是否在其实际位置。使用基于深度学习的优化信任模型来检测视线和非视线条件下存在的障碍物,以降低事故率。实验结果在准确率、精密度、召回率、计算成本和通信开销等方面均优于以往的预测结果。实验使用Network Simulator Version 2模拟器进行,并使用不同的性能指标进行评估,包括简单攻击和意见篡改攻击的计算成本、准确性、精度、召回率和通信开销。然而,该方法在计算成本、准确度、精密度、召回率和通信开销等方面均优于k近邻和人工神经网络等现有方法。因此,该方法具有很强的抗简单攻击和意见篡改攻击的能力。本文提出了一种基于深度学习的优化信任框架,用于VANET中的信任预测。基于深度学习的优化信任模型用于评估事件消息发送方和事件消息的完整性和准确性。
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引用次数: 7
OPC UA TSN: a next-generation network for Industry 4.0 and IIoT OPC UA TSN:面向工业4.0和工业物联网的下一代网络
Pub Date : 2021-12-27 DOI: 10.1108/ijpcc-07-2021-0160
Hristo Trifonov, D. Heffernan
PurposeThe purpose of this paper is to describe how emerging open standards are replacing traditional industrial networks. Current industrial Ethernet networks are not interoperable; thus, limiting the potential capabilities for the Industrial Internet of Things (IIoT). There is no forthcoming new generation fieldbus standard to integrate into the IIoT and Industry 4.0 revolution. The open platform communications unified architecture (OPC UA) time-sensitive networking (TSN) is a potential vendor-independent successor technology for the factory network. The OPC UA is a data exchange standard for industrial communication, and TSN is an Institute of Electrical and Electronics Engineers standard for Ethernet that supports real-time behaviour. The merging of these open standard solutions can facilitate cross-vendor interoperability for Industry 4.0 and IIoT products.Design/methodology/approachA brief review of the history of the fieldbus standards is presented, which highlights the shortcomings for current industrial systems in meeting converged traffic solutions. An experimental system for the OPC UA TSN is described to demonstrate an approach to developing a three-layer factory network system with an emphasis on the field layer.FindingsFrom the multitude of existing industrial network schemes, there is a convergence pathway in solutions based on TSN Ethernet and OPC UA. At the field level, basic timing measurements in this paper show that the OPC UA TSN can meet the basic critical timing requirements for a fieldbus network.Originality/valueThis paper uniquely focuses on the specific fieldbus standards elements of industrial networks evolution and traces the developments from the early history to the current developing integration in IIoT context.
本文的目的是描述新兴的开放标准如何取代传统的工业网络。目前的工业以太网不具备互操作性;从而限制了工业物联网(IIoT)的潜在功能。没有即将到来的新一代现场总线标准来整合工业物联网和工业4.0革命。开放平台通信统一架构(OPC UA)时敏网络(TSN)是一种潜在的独立于厂商的工厂网络后继技术。OPC UA是工业通信的数据交换标准,TSN是电气和电子工程师协会支持实时行为的以太网标准。这些开放标准解决方案的合并可以促进工业4.0和工业物联网产品的跨供应商互操作性。设计/方法/方法简要回顾了现场总线标准的历史,其中突出了当前工业系统在满足融合流量解决方案方面的缺点。本文介绍了OPC UA TSN的实验系统,以现场层为重点,演示了开发三层工厂网络系统的方法。从现有的众多工业网络方案来看,基于TSN以太网和OPC UA的解决方案存在收敛路径。在现场级,本文的基本时序测量表明,OPC UA TSN可以满足现场总线网络的基本关键时序要求。原创性/价值本文独特地关注工业网络演变的特定现场总线标准元素,并追溯从早期历史到当前发展中的工业物联网背景下的集成的发展。
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引用次数: 2
Safety driven intelligent autonomous vehicle for smart cities using IoT 使用物联网的智慧城市安全驱动的智能自动驾驶汽车
Pub Date : 2021-12-07 DOI: 10.1108/ijpcc-10-2020-0182
K. Balachander, C. Venkatesan, R. Kumar
PurposeAutonomous vehicles rely on IoT-based technologies to take numerous decisions in real-time situations. However, added information from the sensor readings will burden the system and cause the sensors to produce inaccurate readings. To overcome these issues, this paper aims to focus on communication between sensors and autonomous vehicles for better decision-making in real-time. The system has unique features to detect the upcoming and ongoing vehicles automatically without intervention of humans in the system. It also predicts the type of vehicle and intimates the driver.Design/methodology/approachThe system is designed using the ATmega 328 P and ESP 8266 chip. Information from ultrasonic and infrared sensors are analyzed and updated in the cloud server. The user can access all these real-time data at any point of time. The stored information in cloud servers is used for integrating artificial intelligence into the system.FindingsThe real-time sensor information is used to predict the surrounding environment and the system responds to the user according to the situation.Practical implicationsThe system is implemented on embedded platform with IoT technology. The sensor information is updated to the cloud using the Blynk application for the user in real time.Originality/valueThe system is proposed for smart cities with IoT technology where the user and the system are aware of the surrounding environment. The system is mainly concerned with the accuracy of sensors and the distance between the vehicles in real-time environment.
自动驾驶汽车依靠基于物联网的技术在实时情况下做出大量决策。然而,来自传感器读数的附加信息将增加系统的负担,并导致传感器产生不准确的读数。为了克服这些问题,本文旨在关注传感器与自动驾驶汽车之间的通信,以便更好地实时决策。该系统具有独特的功能,可以自动检测即将到来和正在行驶的车辆,而无需人工干预。它还可以预测车辆的类型,并与驾驶员亲密接触。系统采用atmega328p和ESP 8266芯片进行设计。来自超声波和红外传感器的信息在云服务器上进行分析和更新。用户可以在任何时间点访问所有这些实时数据。存储在云服务器中的信息用于将人工智能集成到系统中。实时传感器信息用于预测周围环境,系统根据情况对用户做出响应。本系统采用物联网技术在嵌入式平台上实现。传感器信息使用Blynk应用程序为用户实时更新到云端。该系统是为具有物联网技术的智能城市提出的,在这些城市中,用户和系统都了解周围的环境。该系统主要关注传感器的精度和实时环境下车辆之间的距离。
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引用次数: 25
Shifted Rayleigh filter: a novel estimation filtering algorithm for pervasive underwater passive target tracking for computation in 3D by bearing and elevation measurements 移位瑞利滤波:一种新的基于方位和仰角测量的三维普适水下被动目标跟踪估计滤波算法
Pub Date : 2021-11-23 DOI: 10.1108/ijpcc-06-2021-0138
M. Lakshmi, S. Rao, K. Subrahmanyam
PurposeMarine exploration is becoming an important element of pervasive computing underwater target tracking. Many pervasive techniques are found in current literature, but only scant research has been conducted on their effectiveness in target tracking.Design/methodology/approachThis research paper, introduces a Shifted Rayleigh Filter (SHRF) for three-dimensional (3 D) underwater target tracking. A comparison is drawn between the SHRF and previously proven method Unscented Kalman Filter (UKF).FindingsSHRF is especially suitable for long-range scenarios to track a target with less solution convergence compared to UKF. In this analysis, the problem of determining the target location and speed from noise corrupted measurements of bearing, elevation by a single moving target is considered. SHRF is generated and its performance is evaluated for the target motion analysis approach.Originality/valueThe proposed filter performs better than UKF, especially for long-range scenarios. Experimental results from Monte Carlo are provided using MATLAB and the enhancements achieved by the SHRF techniques are evident.
目的海洋探测正成为普适计算水下目标跟踪的重要组成部分。目前文献中发现了许多普遍存在的技术,但对其在目标跟踪中的有效性的研究却很少。本文介绍了一种用于水下三维目标跟踪的移位瑞利滤波器(SHRF)。比较了SHRF和先前证明的无气味卡尔曼滤波(UKF)方法。研究发现,与UKF相比,shrf特别适用于远程场景,用于跟踪解决方案收敛性较低的目标。在分析中,考虑了从单个运动目标的方位、仰角测量噪声中确定目标位置和速度的问题。针对目标运动分析方法,生成了SHRF并对其性能进行了评价。原创性/价值建议的过滤器比UKF执行得更好,特别是对于长期场景。用MATLAB给出了蒙特卡罗的实验结果,结果表明SHRF技术的增强效果是明显的。
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引用次数: 3
Design of low power SRAM- based ubiquitous sensor for wireless body area networks 基于SRAM的无线体域网络低功耗泛在传感器设计
Pub Date : 2021-11-18 DOI: 10.1108/ijpcc-05-2021-0107
Kumari Neeraj, M. M. Basha, Srinivasulu Gundala
PurposeSmart ubiquitous sensors have been deployed in wireless body area networks to improve digital health-care services. As the requirement for computing power has drastically increased in recent years, the design of low power static RAM-based ubiquitous sensors is highly required for wireless body area networks. However, SRAM cells are increasingly susceptible to soft errors due to short supply voltage. The main purpose of this paper is to design a low power SRAM- based ubiquitous sensor for healthcare applications.Design/methodology/approachIn this work, bias temperature instabilities are identified as significant issues in SRAM design. A level shifter circuit is proposed to get rid of soft errors and bias temperature instability problems.FindingsBias Temperature Instabilities are focused on in recent SRAM design for minimizing degradation. When compared to the existing SRAM design, the proposed FinFET-based SRAM obtains better results in terms of latency, power and static noise margin. Body area networks in biomedical applications demand low power ubiquitous sensors to improve battery life. The proposed low power SRAM-based ubiquitous sensors are found to be suitable for portable health-care devices.Originality/valueIn wireless body area networks, the design of low power SRAM-based ubiquitous sensors are highly essential. This design is power efficient and it overcomes the effect of bias temperature instability.
智能无处不在的传感器已部署在无线体域网络中,以改善数字医疗保健服务。近年来,随着对计算能力要求的急剧提高,无线体域网络对基于静态ram的低功耗泛在传感器的设计提出了很高的要求。然而,SRAM单元越来越容易受到软误差,由于供电电压不足。本文的主要目的是为医疗保健应用设计一种基于SRAM的低功耗泛在传感器。设计/方法/方法在这项工作中,偏置温度不稳定性被认为是SRAM设计中的重要问题。为了消除软误差和偏置温度不稳定问题,提出了一种电平移位电路。在最近的SRAM设计中,为了最大限度地减少退化,关注了偏置温度不稳定性。与现有的SRAM设计相比,本文提出的基于finfet的SRAM在延迟、功耗和静态噪声裕度方面取得了更好的结果。生物医学应用中的身体区域网络需要低功耗无处不在的传感器来提高电池寿命。所提出的基于sram的低功耗无处不在传感器适用于便携式医疗保健设备。在无线体域网络中,基于sram的低功耗无处不在传感器的设计至关重要。该设计既节能又克服了偏置温度不稳定性的影响。
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引用次数: 3
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Int. J. Pervasive Comput. Commun.
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