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2022-03-22
摘要翻译:
致力于空气质量监测的毛细管无线传感器网络提供了关于危险空气状况的重要信息。在采用环境产生的能源作为基本能源时,主要的挑战是毛细管网络的实现,而不是按规定的时间更换电池,这导致设备管理的功能困境和高昂的成本。本文提出了一个无电池、自调节、多参数的空气质量监测平台,该平台能够长期收集环境能量。此外,本文还介绍了传感器截面的研究及其结果。一个定制的校准过程,以检查传感器的灵敏度和电力回收部分的各种能源的基本组合,可以在一种“设置和忘记”的情况下,有效地改善室内和室外应用中的空气质量标准跟踪。
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英文标题:
《Development of Highly Efficient Multi-invariable Wireless Sensor System
  Design for Energy Harvesting》
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作者:
Usman Asghar, Farid Touati, Damiano Crescini, Alessio Galli, Adel Ben
  Mnaouer
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最新提交年份:
2018
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分类信息:

一级分类:Electrical Engineering and Systems Science        电气工程与系统科学
二级分类:Signal Processing        信号处理
分类描述:Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用,包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、(生物)医学、图像、视频和多模态自然和人为信号,包括通信信号和数据。感兴趣的主题包括:统计信号处理、谱估计和系统辨识;滤波器设计;自适应滤波/随机学习;(压缩)采样、传感和变换域方法,包括快速算法;用于机器学习的信号处理和用于信号处理应用的机器学习;网络与图形信号处理;信号处理中的凸和非凸优化方法;雷达、声纳和传感器阵列波束形成和测向;通信信号处理;低功耗、多核、片上系统信号处理;信息物理系统的传感、通信、分析和优化,如电网和物联网。
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一级分类:Computer Science        计算机科学
二级分类:Computers and Society        计算机与社会
分类描述:Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
涵盖计算机对社会的影响、计算机伦理、信息技术和公共政策、计算机的法律方面、计算机和教育。大致包括ACM学科类K.0、K.2、K.3、K.4、K.5和K.7中的材料。
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一级分类:Computer Science        计算机科学
二级分类:Networking and Internet Architecture        网络和因特网体系结构
分类描述:Covers all aspects of computer communication networks, including network architecture and design, network protocols, and internetwork standards (like TCP/IP). Also includes topics, such as web caching, that are directly relevant to Internet architecture and performance. Roughly includes all of ACM Subject Class C.2 except C.2.4, which is more likely to have Distributed, Parallel, and Cluster Computing as the primary subject area.
涵盖计算机通信网络的所有方面,包括网络体系结构和设计、网络协议和网络间标准(如TCP/IP)。还包括与Internet体系结构和性能直接相关的主题,如web缓存。大致包括除C.2.4以外的所有ACM主题类C.2,后者更有可能将分布式、并行和集群计算作为主要主题领域。
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英文摘要:
  Capillary wireless sensor networks devoted to air quality monitoring have provided vital information on dangerous air conditions. In adopting the environmentally generated energy as the fundamental energy source the main challenge is the implementation of capillary networks rather than replacing the batteries on a set period of times that leads to functional dilemma of devices management and high costs. In this paper we present a battery-less, self-governing, multi-parametric sensing platform for air quality monitoring that harvests environment energy for long run. Furthermore study on sensor section with their results have also been described in the paper. A customized process of calibration to check the sensors' sensitivity and a basic portfolio of variant energy sources over the power recovery section could productively improve air quality standards tracing in indoor and outdoor application, in a kind of 'set and forget' scenario.
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PDF链接:
https://arxiv.org/pdf/1802.05755
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