Household flow detection using FEAT (flow estimating accelerometer-thermometer) device

The use of IoT devices in water end use disaggregation verification is an emerging field which offers benefits over conventional approaches, in terms of cost, accuracy and scalability. Having reliably disaggregated water appliance consumption data will enable smart water meter data to be used in household water conservation approaches and for understanding water consumption behaviours. The FEAT device provides a low cost, easily applied and scalable solution that is demonstrated to work even for very low flow conditions of 0.03 l/s. The FEAT device is a combination of a battery, Wi-fi board and MPU6050 sensors providing multi-modal accelerometer and thermometer data. The study places 7 of these FEAT devices onto hot and cold water pipes leading to a shower, which is operated 4 times in a high flow situation, 0.13 l/s, and 4 times in a low flow situation, 0.03 l/s. The data is then analysed and compared with a flow logger to determine if the FEAT device can detect when a domestic appliance is using water. There are limiting cases where the level of noise or external interference limits distorts the data, obscuring the distinguishable peaks in the data due to the similarity of the values. By using high and low pass filtering methods it was possible to enhance the peaks but there are still situations where peaks cannot be detected: for example, if a rigid pipe is not able to vibrate easily or if a hot water boiler is not triggered due to the low flow rate. However, the results show it should be possible to overcome these limiting cases, as it is much less likely for both the vibration and temperature data to be adversely affected by noise or external influences simultaneously, therefore decreasing the effect of noise and external influences. In conclusion, this research paper demonstrates that FEAT devices are a low cost, easily applied and scalable solution for detecting flow. By using high and low pass filtering, placing sensors on freely moving pipes and through the use of multi-modal verification, the FEAT device is shown to work on both metal and plastic pipes even in the lowest flow situations of 0.03 l/s. Therefore the FEAT device is a suitable solution for appliance identification in disaggregation verification datasets.     

物联网技术应用实践及其体系结构

物联网技术以其在众多领域的应用而受到了人们的广泛关注。在介绍物联网技术的基本概念及其发展现状的基础上,分别给出了物联网技术在医疗卫生事业、环境监控保护、农业和畜牧管理等领域的成功应用案例。最后通过总结应用方案,分析了物联网体系结构和相关技术,指出了电信运营商在物联网体系中的作用与价值。     

Animating Architecture: Coupling High-Definition Sensing with High-Definition Actuation

Ruairi Glynn , lecturer on interactive architecture at the Bartlett School ofArchitecture, University College London (UCL), puts the pressing question: ‘What does a world of hyper-connective, high-definition sensing offer architectural design?’ Despite the pervasiveness of ubiquitous computing – the Internet of Things (IoT) – and students' ability to speculate, build and test responsive lifesize installations, could practice itself be in danger of getting left behind?     

Research of authentication techniques for the Internet of things

Identity authentication technology is a key technology in the Internet of things (IoT)security field which ensures the authenticity of the identity information of users and device nodes connected to the IoT.Due to the low cost,low power consumption,small storage of IoT devices and heterogeneity of IoT network,the identity authentication mechanisms in traditional computer networks are often not applicable.Firstly,the development process of IoT was introduced,the security risks of IoT and the challenges faced by the authentication work were analyzed.Then the emphasis was put on comparison of the advantages and disadvantages among five typical authentication protocols.Moreover,the authentication technologies in several practical scenarios of RFID,smart grid,Internet of vehicles,and smart home were summarized and analyzed.Finally,the future research direction was discussed.     

一种数据流处理环境下的节点副本放置方法

物联网环境下的许多应用表现为传感数据的连续流式处理,且系统往往通过节点的副本技术保障可用性。但是,运行时副本的备份和放置存在内存和带宽等资源开销,产生处理的延迟。该文给出一种方法,根据运行时的资源消耗以贪心方式放置节点的副本,折中了系统的可用性和开销。实际系统的仿真实验表明,在相同的条件下,该方法相比传统的随机放置,能为系统提供更稳定的可用性。     

物联网平台安全接入方案研究

物联网发展过程中,面临的一个重要问题是感知数据如何从感知设备安全地传输到物联网平台的问题。文章针对三种物联网平台部署模式,提出三种物联网平台的安全接入方案,并分别对三种方案的安全性进行讨论。     

基于直接数字频率合成的远距离散射通信方法

远距离(LoRa)散射通信(BC)不仅成本低、功耗低,而且通信距离远。但现存散射方案的系统组成复杂,且无法应用于实际工程。为此该文提出一种新的LoRa散射通信方法,采用直接数字频率合成(DDS)技术产生频率线性变化的方波作为LoRa散射调制信号,并据此首次展示了基于MCU的LoRa散射通信系统原型样机。实验结果表明,该方法能够在相距208 m的基站和接收端之间的任意位置实现低功耗LoRa散射通信,且兼容现有的商用LoRa射频芯片组。此外,该方法还适用于专用集成电路(ASIC)设计,可使LoRa散射IC有更高的鲁棒性、更低的成本和功耗。     

基于区块链的分布式物联网信任管理方法研究

随着物联网(Internet of things, IoT)技术的发展,在不同的物联网之间逐渐形成了大规模、异构化、动态化的分布式物联网环境.分布式物联网内的设备间与物联网管理机构间存在着广泛的合作需求,为此需要在其中建立信任机制以促进合作.然而,现有的信任机制研究大部分脱离于物联网环境,没有考虑物联网设备计算与存储能力有限且差异较大这一特点,造成抽象信任机制研究无法直接应用于物联网中;另一方面,现有的物联网信任问题研究都依赖于额外的可信第三方或域间信任假设,这在实际中是难以实现的.为了解决上述问题,借助区块链与风险理论,提出一种适用于分布式物联网的信任管理方法.具体地,将信任量化为对期望信用与风险的考察,并借助区块链实现信任数据的有效共享与安全性.实验与分析表明:该方案能够有效量化信任,保护数据不被篡改,且能够以较低的存储开销维护系统的正常运行.     

HSMA：面向物联网异构数据的模式分层匹配算法

随着物联网技术的快速发展,万物互联已经成为必然趋势.物联网技术涉及智能家居、智慧交通等多个领域,使得人们能够随时随地地连接任何人或者设备.然而目前大多数物联网异构数据是孤立的存储,阻碍了万物互联的步伐.数据模式匹配被广泛应用于数据互联并且能够较好地解决以上问题.由于海量物联网数据的异构性以及高增长性,目前的模式匹配方式人工参与度高,与实际应用的契合度低,难以解决物联网新环境下的模式自动匹配问题.提出了一种面向物联网异构数据的模式分层匹配算法,构建3层映射匹配：特征分类匹配、关系特征聚类匹配和混合元素匹配.该算法通过逐层匹配,不断缩小匹配空间,从而提高了匹配质量,减少了元素间匹配次数和人工参与度,较好地实现了自动模式匹配.运用大量数据样本来检验算法的效率和性能,结果证明该算法可行有效.     

面向物联网数据安全共享的属性基加密方案

物联网的发展一直面临着严峻的安全威胁和挑战,而物联网数据的安全共享及细粒度访问控制是其急需应对的安全问题之一.针对该问题,提出一种面向物联网数据安全共享的访问结构隐藏的属性基加密方案.该方案在保证数据隐私的情况下,能够实现密文数据的细粒度访问控制.首先提出一种将身份加密方案(identity-based encryption, IBE)转换为支持多值属性与门的密文策略属性基加密方案(ciphertext-policy attribute-based encryption, CP-ABE)的通用转换方法,并且转换后的CP-ABE能够继承IBE的特征.然后基于该转换方法将Wee提出的接收者匿名IBE方案转换为访问结构隐藏的CP-ABE方案,实现了密文、用户私钥、公钥和主私钥长度恒定,且解密只需一个双线对运算.而后将该CP-ABE方案应用于物联网中的智慧医疗应用场景,并给出应用的系统模型及步骤.最后,理论分析与实验结果表明所提方案在实现访问结构隐藏时,在计算效率、存储负担及安全性方面具有优势,在实际应用于物联网环境时更加高效和安全.