物联网:智慧城市与健康管理的基石

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"物联网_智慧城市,eHealth CRC(2018).pdf" 物联网(IoT)作为一项重大的技术革新,已经渗透到生活的各个领域,特别是在智能城市建设和医疗保健方面。它开启了一种新的趋势,致力于通过构建无处不在的服务池来提供个性化的用户体验。物联网的这种变革性方法的识别激发了本书的编写,目的是展示这些领域的最新研究成果。 物联网的研究不仅限于特定领域,而是由传感器、网络、云计算、边缘计算、大数据、机器学习智能、安全和隐私等多领域研究的交叉合作驱动的。这使得本书的领域具有很强的跨学科性质,来自全球15多个国家的研究人员分享了他们在物联网领域的前沿研究。所有21章都展示了作者们在物联网领域的最佳研究成果,对于该领域具有至关重要的意义。 智能城市是物联网推动的关键发展领域之一。从智能交通到公民数据的有效管理以及公路安全措施,物联网已经彻底改变了城市建设的各个方面。本书采用双重方法,既讨论了物联网的核心概念,又探讨了构建智能城市和医疗保健应用的相关案例研究。我们希望这本书能成为所有物联网研究人员的理想伴侣。关于eHealth的章节展示了在开发全面智能健康护理模型方面的有趣研究。 随着物联网的发展,设备产生的数据量急剧增加。然而,这赋予了系统更大的能力,因为分析的数据越多,对用户行为的理解就越深入。书中的一些章节也讨论了物联网中的数据方面。 本书分为四个部分: 1. 物联网简介:定义与基础框架 这部分介绍了物联网的基本定义和构建块,为理解物联网的概念和技术提供了基础。 2. 物联网框架:架构视角 这一部分深入探讨了物联网的架构设计,包括如何将不同组件集成在一起,以实现无缝通信和数据处理。 3. 物联网的跨学科方面 这里涵盖了物联网与其他领域的交叉,如大数据分析、机器学习、安全性与隐私保护,展示了这些领域如何相互影响并推动物联网的进步。 4. 物联网和泛在计算的未来研究、范围及案例研究 最后部分展望了物联网的未来研究方向,包括潜在的应用场景和案例,以及泛在计算的发展。 总体而言,这本书为读者提供了物联网的全面视图,涵盖了从基本原理到实际应用的广泛内容,以及对未来的展望。无论是学者、研究人员还是从业者,都能从中受益,深化对物联网及其在智能城市和eHealth等领域影响的理解。
2018-01-14 上传
Internet of Things (IoT) is the third wave of Internet and is supposed to have a potential to connect about 28 billion items by 2020, ranging from bracelets to cars. The term “IoT,” which was rst proposed by Kevin Ashton, a British technologist, in 1999, has the potential to impact everything from new product opportunities to shop oor optimization to fac- tory worker ef ciency gains that will power top-line and bottom-line gains. It is believed that IoT will improve energy ef ciency, remote monitoring, and control of physical assets and productivity through applications as diverse as home security to condition monitor- ing on the factory oor. Now IoT has been used in markets in the eld of health care, home appliances and buildings, retail markets, energy and manufacturing companies, mobility and transportation, logistics companies, and by media. Equipments are becoming more digitized and more connected, establishing networks between machines, humans, and the Internet, leading to the creation of new ecosystems that enable higher productivity, better energy ef ciency, and higher pro tability. Sensors help to recognize the state of things, by which they gain the advantage of anticipating human needs based on the information collected per context. These intelligent devices not only gather information from their environment but are also capable of taking deci- sions without human intervention. IoT technology is being used in our day-to-day life for unlocking the door without a key; in card recognizers, automatic locks, vehicle detecting systems, toll payment system; and for tracking animals, access control, payment systems, contactless smart cards, anti-theft devices, steering column reader, etc. The IoT building blocks will come from those that are web-enabled devices, providing common platforms on which they can communicate, and develop new applications to capture new users. In this background, this book is an attempt to present updated information on the recent trends on the issues involved, highlighting the challenges involved, and source the solutions for some of these challenges. The book comprises 14 chapters. The chapterwise description of contents in the volume is as follows. For seamless visual tracking of passengers traveling in a vehicle, the visual light trans- mission (VLT) and visual light re ectance (VRT) values of the glass windows used in the vehicle should be at a particular value. All vehicle manufacturers follow certain standards. But the vehicle owner/user generally buys window-tinting lms from the gray market and pastes the same on the glass windows, which in turn hamper the visibility, thereby preventing the law enforcement authorities from having a clear view of those traveling in the vehicle. In Chapter 1, a proposal for the automatic detection of tint level for vehi- cles is presented. The system has been designed using ordinary cameras that work in the visible region of the electromagnetic spectrum. The system is capable of identifying a vehicle’s registered number using algorithms developed for this purpose. Various ltering techniques are applied to nd the level of tint from the captured camera images. Using three different techniques, namely, color segmentation, contour detection, and histogram analysis, the tint level of windshield/window region is estimated. Thus, the IoT system recognizes the numbers on the number plate and can fetch the contact details of the owner from the database. It also communicates the same information to the owner with details on and extent of tint level violation along with documentary evidence.