Recent Techniques for Harvesting Energy from the Human Body

The human body contains a near-infinite supply of energy in chemical, thermal, and mechanical forms. However, the majority of implantable and wearable devices are still operated by batteries, whose insufficient capacity and large size limit their lifespan and increase the risk of hazardous material leakage. Such energy can be used to exceed the battery power limits of implantable and wearable devices. Moreover, novel materials and fabrication methods can be used to create various medical therapies and life-enhancing technologies. This review paper focuses on energy-harvesting technologies used in medical and health applications, primarily power collectors from the human body. Current approaches to energy harvesting from the bodies of living subjects for self-powered electronics are summarized. Using the human body as an energy source encompasses numerous topics: thermoelectric generators, power harvesting by kinetic energy, cardiovascular energy harvesting, and blood pressure. The review considers various perspectives on future research, which can provide a new forum for advancing new technologies for the diagnosis, treatment, and prevention of diseases by integrating different energy harvesters with advanced electronics.     

A novel fog-computing-assisted architecture of E-healthcare system for pregnant women

Recently, there is a tremendous rise and adoption of smart wearable devices in smart healthcare applications. Moreover, the advancement in sensors and communication technology empowers to detect and analyse physiological data of an individual from the wearable device. At present, the smart wearable device based on internet of things is assisting the pregnancy woman to continuously monitor their health status for avoiding the severity. The physiological data analysis of wearable device is processed with the assistance of fog computing due to limited computational and energy capability in the wearable device. Additionally, fog computing overcomes the excess latency that is created by cloud computing during physiological data analysis. In this article, a smart health monitoring IoT and fog-assisted framework are proposed for obtaining and processing the temperature, blood pressure, ECG, and pulse oximeter parameters of the pregnant woman. Based on real time series data, the rule-based algorithm logged in the wearable device with fog computing to analyse the critical health conditions of pregnant women. The proposed wearable device is validated and tested on 80 pregnant women in real time, and wearable device is delivering the 98.75% accuracy in providing health recommendations.

     

面向IoT终端设备的RISC-V微控制器设计与分析

随着通信、芯片等技术的不断发展,以及现在提出的万物互联的概念,物联网将迎来一个大的发展;其中 IoT 终端设备的研究是重中之重.应用于 IoT的终端设备不仅需要在几 mW的功率范围内工作,而且需要灵活的计算能力.这就要求应用于 IoT 终端设备的处理器能实现更高的能效比.本文设计了一款基于 RISC-V 指令集的微控制器,首先详细介绍了该RISC-V 微控制器的微结构、存储子系统和RISC-V 指令集架构;最后在VCS 验证环境中验证了该微控制器的逻辑功能.     

可穿戴医疗设备的安全方法研究

针对可穿戴医疗设备应用中所存在的隐私保护和安全问题,在分析了已有生物密钥和量子密钥的优缺点的基础上,给出了将两者结合并用于可穿戴医疗设备安全保护中的思路;针对可穿戴医疗设备组成的异构网络的数据安全传输问题,在分析已有的密钥预分配方案的基础上,提出将其应用于可穿戴医疗设备构成的动态、异构网络中,为解决可穿戴医疗设备数据安全传输提供理论和技术基础。     

Solution-processed ZnO energy harvester devices based on flexible substrates

Microsystem Technologies - The smart healthcare devices connected to the internet of things (IoT) for medical services can acquire and process physiological data of risk patients, real-time...     

非易失处理器安全备份机制研究

非易失处理器NVP可以在自供能环境下快速恢复,非常适合物联网等应用环境。备份(Checkpointing)是NVP的核心保障技术。然而,现有的备份策略假设NVP处于理想的工作环境,只考虑了能量输入不稳等因素,没有考虑外界的恶意攻击对NVP安全带来的影响,比如,外界篡改备份过程中寄存器的内容,使系统崩溃;篡改备份过程中写到非易失存储中的内容,使数据不可信等,阻碍了NVP在可穿戴医疗设备等安全攸关领域中的应用。梳理了最新的带维持态的NVP在备份过程中存在的安全威胁,并提出了相应的应对机制。     

Performance evaluation of green data centre management supporting sustainable growth of the internet of things

Network management is increasingly being customised for green objectives due to roll out of mission-critical applications across the internet of things and execution, in a number of cases, on battery-constrained devices. In addition, the volume of operations across the internet of things is attracting climate change concerns. While operational efficiency of wireless devices and in data centres (which support operation of the internet of things) should not be achieved at the expense of Quality of Service, optimisation opportunities should be exploited and inefficient resource use minimised. Green networking approaches however, are not yet standardised, and there is scope for novel middleware architectures. In this paper, we explore operational efficiency from the perspective of activities in data centres which support the internet of things. This includes evaluation of the effectiveness of mechanisms integrated into the e-CAB framework, an algorithm proposed by the authors to manage next generation data centres with green objectives. A selection of its policy mechanisms have been implemented in the NS-2 Network Simulator to evaluate performance; configuration decisions are described in this paper and presented alongside experimental results which demonstrate optimisations achieved. Focus lies, in particular, on rate adaptation of its context discovery protocol which is responsible for capturing real-time network state. Performance results reveal a small overhead when applying network management and validate improved efficiency through adaption in response to environment dynamics.     

An acceleration vector variance based method for energy expenditure estimation in real-life environment with a smartphone/smartwatch integration

By combining embedded passive sensing technologies from both smartphone and smartwatch, it is possible to obtain a high quality detection of sedentary activities (sitting, reclining posture…), movements (walking…) and periods of more intense body movements (running…). Our research encompasses the definition of an energy-saving function for the total energy expenditure (TEE) estimation using accelerometry data. This topic is clearly at the crossroad of both computer science and medical research. The present contribution proposes an intelligent wearable system, which combines the use of two complementary devices: smartphone and smartwatch to collect accelerometry data. Together they can precisely discriminate real-world human sedentary and active behaviors and their duration and estimate energy expenditure in real time and in free-living conditions. The results of the study are expected to help subjects to handle their daily-living physical activity notably for being compliant with the physical activity international guidelines (150 min of moderate intensity activity/week). It is also expected that the physical activity feedbacks using these popular devices can prove the effectiveness of such wearable objects to promote individually-adapted healthy behavioral changes. The performance of the proposed function was evaluated by comparing the energy expenditure given by the smartphone and smartwatch with that produced by Armband^®. The mean error of TEE between the proposed function and Armband^® was less than 4% for an average 6 h period of daily-living activities. The main theoretical contribution is the definition of a new predictive mathematical function of energy expenditure, which competes with the non-public function used in dedicated costly devices such as Armband^®. In addition, this work demonstrates the potential of wearable technologies.     

Review on mobility aware MAC protocol using Mobile internet of things

Multimedia Tools and Applications - Modern boom and understanding of our growing needs, applications based on the Mobile Internet of Things (MIoT) are becoming important for future internet...     

A survey on semanticized and personalized health recommender systems

Health 3.0 is a health-related extension of the Web 3.0 concept. It is based on the semantic Web which provides for semantically organizing electronic health records of individuals. Health 3.0 is rapidly gaining ground as a new research topic in many academic and industrial disciplines. Due to the recent rapid spread of wearable sensors and smart devices with access to social media, migrating health services from the traditional centre-based health system to personal health care is inevitable. In this current era of greater personalization, treating patients' health problems according to their profile and medical data gathered is possible using the latest information technologies. Consequently, personalized health recommender systems have gained importance. Empowering the utility of advanced Web technology in personalized health systems is still challenging due to pressing issues, such as lack of low cost and accurate smart medical sensors and wearable devices, existing investment in legacy Web system architecture in health sector, heterogeneity of medical data gathered by myriad health care institutions and isolated health services, and interoperability issues as well as multi-dimensionality of medical data. By tracing recent developments, this paper offers a systematic review through recent research on semantic Web-enabled personalized health systems, namely, semanticized personalized health recommender systems with the key enabling technologies, major applications, and successful case studies. Critical questions derived from the research studies were discussed, and main directions of open issues were identified leading to recommendations for future study in the field of personalized health recommender systems.     

Secure video summarization framework for personalized wireless capsule endoscopy

Wireless capsule endoscopy (WCE) has several benefits over traditional endoscopy such as its portability and ease of usage, particularly for remote internet of things (IoT)-assisted healthcare services. During the WCE procedure, a significant amount of redundant video data is generated, the transmission of which to healthcare centers and gastroenterologists securely for analysis is challenging as well as wastage of several resources including energy, memory, computation, and bandwidth. In addition to this, it is inherently difficult and time consuming for gastroenterologists to analyze this huge volume of gastrointestinal video data for desired contents. To surmount these issues, we propose a secure video summarization framework for outdoor patients going through WCE procedure. In the proposed system, keyframes are extracted using a light-weighted video summarization scheme, making it more suitable for WCE. Next, a cryptosystem is presented for security of extracted keyframes based on 2D Zaslavsky chaotic map. Experimental results validate the performance of the proposed cryptosystem in terms of robustness and high-level security compared to other recent image encryption schemes during dissemination of important keyframes to healthcare centers and gastroenterologists for personalized WCE.     

从互联网角度分析物联网

从互联网角度对物联网进行了深入浅出的分析。物联网是在计算机互联网的基础上,利用RFID、无线数据通信等技术,构造一个覆盖世界上万事万物的"Internet of things"。在这个网络中,物品(商品)能够彼此进行"交流",而无需人的过多干预。其实质就是综合利用各种技术,通过互联网实现物品(商品)的自动识别和信息的互联与共享的目的。不论是物联网的概念内涵,还是使用的相关的技术,物联网都没有脱离互联网,二者的基础是一致的。     

An Improved Steganographic Scheme Using the Contour Principle to Ensure the Privacy of Medical Data on Digital Images

With the improvement of current online communication schemes, it is now possible to successfully distribute and transport secured digital Content via the communication channel at a faster transmission rate. Traditional steganography and cryptography concepts are used to achieve the goal of concealing secret Content on a media and encrypting it before transmission. Both of the techniques mentioned above aid in the confidentiality of feature content. The proposed approach concerns secret content embodiment in selected pixels on digital image layers such as Red, Green, and Blue. The private Content originated from a medical client and was forwarded to a medical practitioner on the server end through the internet. The K-Means clustering principle uses the contouring approach to frame the pixel clusters on the image layers. The content embodiment procedure is performed on the selected pixel groups of all layers of the image using the Least Significant Bit (LSB) substitution technique to build the secret Content embedded image known as the stego image, which is subsequently transmitted across the internet medium to the server end. The experimental results are computed using the inputs from “Open-Access Medical Image Repositories (aylward.org)” and demonstrate the scheme’s impudence as the Content concealing procedure progresses.     

基于体域网的穿戴式全景射控系统

基于超宽带体域网以及多视点视频编码技术,设计了一个面向穿戴式应用的全景视频监控系统,其中着重研究了全景视频采集、编码与传输的关键技术.在穿戴式全景监控系统中,体域网节点的处理能力、电池能量及通信带宽等资源均相当有限,而该系统对于全景视频的重构质量又提出了较高的要求.因此,针对全景视频的采集、编码与传输,根据H.264/...     

Implementation of 4kUHD HEVC-content transmission

The Internet of things (IoT) has received a great deal of attention in recent years, and is still being approached with a wide range of views. At the same time, video data now accounts for over half of the internet traffic. With the current availability of beyond high definition, it is worth understanding the performance effects, especially for real-time applications. High Efficiency Video Coding (HEVC) aims to provide reduction in bandwidth utilisation while maintaining perceived video quality in comparison with its predecessor codecs. Its adoption aims to provide for areas such as television broadcast, multimedia streaming/storage, and mobile communications with significant improvements. Although there have been attempts at HEVC streaming, the literature/implementations offered do not take into consideration changes in the HEVC specifications. Beyond this point, it seems little research exists on real-time HEVC coded content live streaming. Our contribution fills this current gap in enabling compliant and real-time networked HEVC visual applications. This is done implementing a technique for real-time HEVC encapsulation in MPEG-2 Transmission Stream (MPEG-2 TS) and HTTP Live Streaming (HLS), thereby removing the need for multi-platform clients to receive and decode HEVC streams. It is taken further by evaluating the transmission of 4k UHDTV HEVC-coded content in a typical wireless environment using both computers and mobile devices, while considering well-known factors such as obstruction, interference and other unseen factors that affect the network performance and video quality. Our results suggest that 4kUHD can be streamed at 13.5 Mb/s, and can be delivered to multiple devices without loss in perceived quality.

     

基于ARM的视频数据采集传输系统的设计与实现

对基于ARM的视频数据采集传输系统进行研究及设计,通过ARM新一代嵌入式开发平台,与现在流行的互联网及无线传输技术相结合,实现视频数据的采集和远程数据的传输。设计中采用嵌入式Linux系统通过USB摄像头进行视频数据的采集,解决图像的格式转换和MJPEG编码压缩的数据处理,以及通过软件的设计实现MJPEG格式文件到流媒体输出等问题,最终实现视频数据采集和传输。本系统有以下几个方面的应用:家庭环境的实时监测、家居的智能化控制、高危车间厂房无线监控与控制、中长距离的家庭视频通讯、企业实时视频监控等。     

IEEE 802.15.4实时通信调度算法研究

IEEE 802.15.4是低功耗无线通信媒体接入控制协议,目前已广泛应用于医疗健康、工业控制和楼宇自动化等物联网领域。为满足不同应用需求,研究者提出了多种适用于IEEE 802.15.4协议的实时通信算法。根据带宽利用率、延时约束和能效性等特征,对这些实时通信调度算法进行分类、比较和性能分析,以助于在实际应用中合理部署。另外,对未来的研究工作进行了展望。     

Advanced internet of things for personalised healthcare systems: A survey

As a new revolution of the Internet, Internet of Things (IoT) is rapidly gaining ground as a new research topic in many academic and industrial disciplines, especially in healthcare. Remarkably, due to the rapid proliferation of wearable devices and smartphone, the Internet of Things enabled technology is evolving healthcare from conventional hub based system to more personalised healthcare systems (PHS). However, empowering the utility of advanced IoT technology in PHS is still significantly challenging in the area considering many issues, like shortage of cost-effective and accurate smart medical sensors, unstandardised IoT system architectures, heterogeneity of connected wearable devices, multi-dimensionality of data generated and high demand for interoperability. In an effect to understand advance of IoT technologies in PHS, this paper will give a systematic review on advanced IoT enabled PHS. It will review the current research of IoT enabled PHS, and key enabling technologies, major IoT enabled applications and successful case studies in healthcare, and finally point out future research trends and challenges.     

一种监护控制系统及室内定位方法

利用物联网、可穿戴便携设备等新技术开发一款可对住院患者进行精准定位并能够实时自动采集患者生命体征的监护控制系统。系统有效改变了医院传统护理模式,提升了护理质量。通过建立监护控制系统,实现了患者生命体征数据自动采集;通过利用UWB超宽带技术,采用基于锚的TDOA定位模式开发高精度室内定位模块,实现对住院患者精确定位。应用该系统,护理人员可以对病人活动状态进行实时监控、患者病情及时处理,对心脑血管疾病患者临床诊疗过程具有重要意义。系统有效改变医院传统护理模式,降低了医疗差错,提高了医护人员工作效率和医疗服务质量。     

Lightweight and Secure Mutual Authentication Scheme for IoT Devices Using CoAP Protocol

Internet of things enables every real world objects to be seamlessly integrated with traditional internet. Heterogeneous objects of real world are enhanced with capability to communicate, computing capabilities and standards to interoperate with existing network and these entities are resource constrained and vulnerable to various security attacks. Huge number of research works are being carried out to analyze various possible attacks and to propose standards for securing communication between devices in internet of things (IoT). In this article, a robust and lightweight authentication scheme for mutual authentication between client and server using constrained application protocol is proposed. Internet of things enables devices with different characteristics and capabilities to be integrated with internet. These heterogeneous devices should interoperate with each other to accumulate, process and transmit data for facilitating smart services. The growth of IoT applications leads to the rapid growth of IoT devices incorporated to the global network and network traffic over the traditional network. This scheme greatly reduces the authentication overhead between the devices by reducing the packet size of messages, number of messages transmitted and processing overhead on communicating devices. Efficiency of this authentication scheme against attacks such as DoS (denial of service), replay attacks and attacks to exhaust the resources are also examined. Message transmission time reduced upto 50% of using proposed techniques.