Secure localization with attack detection in wireless sensor networks

Rapid technological advances have enabled the development of low-cost sensor networks for various monitoring tasks, where it is important to estimate the positions of a number of regular sensor nodes whose locations cannot be known apriori. We address the problem of localizing the regular nodes with range-based location references obtained from certain anchor nodes referred to as beacons, particularly in an adverse environment where some of the beacons may be compromised. We propose an innovative modular solution featuring two lightweight modules that are for dedicated functionalities, respectively, but can also be closely integrated. First, we harness simple geometric triangular rules and an efficient voting technique to enable the attack detection module, which identifies and filters out malicious location references. We then develop a secure localization module that computes and clusters certain reference points, and the position of the concerned regular node is estimated with the centroid of the most valuable reference points identified. Extensive simulations show that our attack detection module can detect compromised beacons effectively, and the secure localization module can subsequently provide a dependable localization service in terms of bounded estimation error. The integrated system turns out to be tolerant of malicious attacks even in highly challenging scenarios.     

Through-Walls Communication for Medical Emergency Services

The authors present a model for bringing the coordination power of workflow management systems to outdoor wearable augmented reality (AR) systems. They portray how mobile equipment may be integrated with adaptive, context-aware work environments. A scenario of a medical emergency task is described to illustrate the functionality of this form of collaboration system. Appropriate information stickers are introduced to support data collection in medical emergency scenarios in a sophisticated form through a hands-free user interface for medical personnel. They propose the use of new user interface technology, including multimedia, AR information stickers, and the allocation of patient medical records to identified locations of the human body. A key feature is the access to relevant information for users in the mobile environment as well as for those in the advanced control room. An additional advantage is the automatic recording of on-site data, which helps to build the medical record of a patient without interfering with the work of the emergency team.     

L2P2: A location-label based approach for privacy preserving in LBS

The developments in positioning and mobile communication technology have made the location-based service (LBS) applications more and more popular. For privacy reasons and due to lack of trust in the LBS providers, k-anonymity and l-diversity techniques have been widely used to preserve privacy of users in distributed LBS architectures in Internet of Things (IoT). However, in reality, there are scenarios where the locations of users are identical or similar/near each other in IoT. In such scenarios the k locations selected by k-anonymity technique are the same and location privacy can be easily compromised or leaked. To address the issue of privacy preservation, in this paper, we introduce the location labels to distinguish locations of mobile users to sensitive and ordinary locations. We design a location-label based (LLB) algorithm for protecting location privacy of users while minimizing the response time for LBS requests. We also evaluate the performance and validate the correctness of the proposed algorithm through extensive simulations.     

采用EKF与PF的室内融合定位技术

在室内定位的复杂环境中,WiFi指纹法的定位性能易受信号波动的影响,行人航位推算方法(Pedestrian Dead Reckoning,PDR)的定位误差会随时间逐渐累积,为了解决这两个方面的问题,提出了一种采用扩展卡尔曼滤波(Extended Kalman Filter,EKF)与粒子滤波(Particle Filter,PF)的融合定位技术,该技术通过融合WiFi指纹法和优化后的行人航位推算方法来提高定位精度。在WiFi指纹法模块,该技术采用传统的加权k近邻法进行定位。在行人航位推算模块,该技术融合多种传感器进行航向估计,改进传统的非线性模型进行步长估计,使优化后的行人航位推算方法更适用于复杂环境中的实际应用。最后,结合粒子滤波和室内地图信息,该技术能够校正估计位置并进一步提高定位精度。通过实验表明,本文提出的融合校正方法能够有效提高定位精度。     

Using and determining location in a context-sensitive tour guide

In a study that provided unique insights into the challenges associated with developing location-based applications, the Lancaster Guide project used members of the general public to test a network-centric electronic tourist guide. We discuss two main topics. The first is our choice of positioning technology - beacons that broadcast using an IEEE 802.11 wireless network combined with user input. The second topic concerns techniques for generating custom tours for electronic city-guide systems. Guide generates these custom tours by taking into account multiple contextual triggers and user preferences. In practice, producing good tours and, indeed, assessing the quality of a tour are difficult tasks. While our analysis of techniques for producing custom tours is somewhat specific to the city-guide domain we believe that the majority of our work is relevant to location-based systems in general     

Interactive 3D content insertion in images for multimedia applications

This article addresses the problem of creating interactive mixed reality applications where virtual objects interact in images of real world scenarios. This is relevant to create games and architectural or space planning applications that interact with visual elements in the images such as walls, floors and empty spaces. These scenarios are intended to be captured by the users with regular cameras or using previously taken photographs. Introducing virtual objects in photographs presents several challenges, such as pose estimation and the creation of a visually correct interaction between virtual objects and the boundaries of the scene. The two main research questions addressed in this article include, the study of the feasibility of creating interactive augmented reality (AR) applications where virtual objects interact in a real world scenario using the image detected high-level features and, also, verifying if untrained users are capable and motivated enough to perform AR initialization steps. The proposed system detects the scene automatically from an image with additional features obtained using basic annotations from the user. This operation is significantly simple to accommodate the needs of non-expert users. The system analyzes one or more photos captured by the user and detects high-level features such as vanishing points, floor and scene orientation. Using these features it will be possible to create mixed and augmented reality applications where the user interactively introduces virtual objects that blend with the picture in real time and respond to the physical environment. To validate the solution several system tests are described and compared using available external image datasets.     

Exploiting real world knowledge in ubiquitous applications

Electronic tourist guide systems typically recommend locations and sometimes provide navigation information. However, previously such systems were rather naive about what constituted information close to and thus relevant for the user. In this paper we show how to exploit knowledge about features in the real world to compute whether an information resource concerns something that the user can probably see. At run-time, we can take a set of foci, that is 2D polygons to which data is attached, and then filter away those foci that are invisible because they are occluded by nearby buildings. This is performed with the awareness of the inconsistencies and lack of accuracy in both mapping technology and GPS positioning in urban spaces. We have also developed tools to upload geotagged photos and mark foci polygons on a map. Using visibility-filtered information, less cluttered maps can be provided, and the user experience enhanced through removal of irrelevant information.     

A review of source term estimation methods for atmospheric dispersion events using static or mobile sensors

Understanding atmospheric transport and dispersal events has an important role in a range of scenarios. Of particular importance is aiding in emergency response after an intentional or accidental chemical, biological or radiological (CBR) release. In the event of a CBR release, it is desirable to know the current and future spatial extent of the contaminant as well as its location in order to aid decision makers in emergency response. Many dispersion phenomena may be opaque or clear, thus monitoring them using visual methods will be difficult or impossible. In these scenarios, relevant concentration sensors are required to detect the substance where they can form a static network on the ground or be placed upon mobile platforms. This paper presents a review of techniques used to gain information about atmospheric dispersion events using static or mobile sensors. The review is concluded with a discussion on the current limitations of the state of the art and recommendations for future research.     

全源矿井定位:一种智能煤矿位置服务新范式

矿山动目标定位系统为煤矿智能化建设提供基于位置的服务。而传统的矿井定位系统中定位信标与定位标签之间大多采用单一或组合通信技术,结构不灵活,覆盖范围受限,鲁棒性不高,定位精度有限;使用单一或组合测距技术,无法根据使用场景的不同自适应选择最优测距技术;位置求解算法固定,无法根据使用场景的不同和信号变化自适应选择最优求解算法。提出了全源矿井定位新范式,可根据定位环境和目标承载平台的变化,从所有可用定位信号测量设备中动态选择满足当前需求的最优设备组合,自适应地从可用的测距算法、位置解算算法、结果优化算法中选择最优的算法组合,计算出目标节点的最优位置。给出了全源矿井定位系统架构,探讨了矿井中可用的定位信号测量设备和可用于定位的测量属性值类型,对比了单一矿井定位与全源矿井定位在定位服务器方面的功能差异。研究了全源矿井定位中的3项关键技术:统一定位框架技术,旨在解决全源定位的模块化、组合式、可扩充需求;全源定位信息融合技术,对测量属性值进行有机组织,达到提高定位精度的目的;通信定位一体化技术,通过无线通信网络本身所具有的定位能力,简化全源矿井定位系统的设计并提高定位精度。提出了基于“端-边-云”的全源矿井定位系统实施架构,以便与煤矿智能化的主流建设模式相适应,大幅降低实施难度和系统成本。     

基于WT-UKF 的PDR/GPS 组合定位算法

针对行人航迹推算(PDR) 与全球定位系统(GPS) 组合定位问题, 提出一种基于小波变换(WT) 的无迹卡尔曼滤波(UKF) 改进算法, 对PDR 和GPS 定位结果进行数据融合. 建立PDR/GPS 组合定位系统数学模型, 采用小波变换对运动加速度信号噪声特性进行在线估计, 以更新UKF 的协方差矩阵. 所提出的WT-UKF 滤波算法弥补了传统UKF 算法因人为假定信号噪声为高斯白噪声而影响滤波效果和精度的缺陷. 实验结果表明, 使用WT-UKF 滤波算法对PDR/GPS 进行数据融合时稳定性更强, 精度更高.     

磁信标的三维磁场计算及优化设计

磁信标定位技术在现代定位领域中显示出越来越重要的作用,为确定磁信标的最佳设计结构,用Comsol Mutiphysics软件对不同结构的磁信标产生的三维磁场进行了有限元分析,讨论了磁信标的材料、结构、形状等参数不同时磁场强度的性能并对其进行优化设计。在此基础上分别研究了单、正交、阵列永磁体磁信标及单、正交螺线管磁信标的场强特性,使用MATLAB软件对不同结构磁信标的场强大小及稳定性进行了仿真模拟,得出对永磁体磁信标来说,正交组合磁信标产生的磁场稳定性更好,对螺线管来说,加磁芯的正交螺线管磁场强度稳定性较好,适用于高精度磁信标定位系统。不同阵列磁信标的最佳基线长度不同,产生的磁场强度约为组合磁信标的倍数,但随着距离的增加磁场变化率较大造成场强分布不稳定,适用于误差容错较高的磁信标定位系统。     

融合RSSI测距定位的室内PDR算法

在室内定位系统中,针对RSSI测距定位系统接收到的信号会因环境的不确定性出现不可预测的随机变化和行人航迹推算(PDR)定位系统漂移误差长时间的累积效果,提出融合RSSI测距定位的室内行人航迹推算算法,以扩展卡尔曼滤波器实现两者定位信息的融合,获得系统的最优定位结果。仿真结果表明,该融合定位算法的平均定位误差约为0.83205 m,范围维持在0.51948 m～1.13529 m内,并在定位稳定性方面表现出良好的性能,验证了该方法的合理性和有效性。     

A NFC-based pervasive solution for city touristic surfing

Context-aware and pervasive computing applications have increased their number during the last decade, thanks to the development of new communication and mobile technologies. These applications cover a wide spectrum of problems, sectors, scenarios, and environments that aim to build smart environments supporting many kinds of human interactions. Tourism is an important economic sector for many cities and countries and therefore a research area where the development of ubiquitous applications is having a great interest. In this paper, we propose a solution oriented to help the user to find the location of interest points within the city and navigate through them. In this work, we propose the use of mobile phones with the near-field communication technology incorporated and Smart Posters disseminated along the city. Indoor and outdoor locations and navigation are allowed, “where is it?”, “what is it?”, “where am I?”, “what is there around me?” and the remaining hits of locations and navigation paradigms are supported by an easy, cheap, and context-awareness system without the need of hard tasks to the user related to system installation or tailoring.     

Optimal positioning of read/write heads in mirrored disks

This work is concerned with finding the expected-travel-distance-minimizing anticipatory positions of disk arms in mirrored disk systems. In such systems, data is duplicated across two or more disk drives. A ‘read’ request may choose to read from any copy, and thus do so from the disk whose arm is closest to the request location. Since a ‘write’ must update all copies, the response time for such a request will depend on the distance of the arm which is furthest away from the request's location. Some problems of optimally positioning emergency service units on a line and of positioning idle elevators can be viewed mathematically as a special case of the mirrored disks scenario in which there are ‘read’ requests only. We show that, for any request location distribution, if there are more write than read requests then both arms should be located as if read requests did not exist — both at the median of the distribution. For situations where most requests are of ‘read’ type, we derive necessary conditions for optimal locations.     

面向无线传感器网络节点定位的移动锚节点路径规划

节点定位是无线传感器网络技术研究的一个基本问题,大多数无线传感器网络的应用和中间件技术都需要节点的位置信息.目前比较实用的定位方法是利用一些移动锚节点(如安装有GPS)根据有效的规划路径移动,通过发送包含其自身坐标的信息来定位其他节点,该方法不过多地增加无线传感器网络成本,还可以获得较高的定位精度.在该方法中,移动锚节点的路径规划问题是需要解决的基本问题.主要研究移动锚节点的路径规划问题,把图论引入到无线传感器网络节点定位系统.把无线传感器网络看成一个连通的节点无向图,路径规划问题转化为图的生成树及遍历问题,提出了宽度优先和回溯式贪婪算法.仿真实验和真实系统实验结果表明,该方法能够很好地适应无线传感器网络节点随机分布的节点定位,可以取得较高的定位精度.     

一种基于蓝牙信标的室内定位系统

针对室内定位与导航服务的应用需求,使用蓝牙信标节点,构建了一种米级室内定位系统.设计了一种基于CC2540F256的蓝牙4.0信标节点,采用优化均匀部署方法完成信标的布设,在此基础上配置信标BLE协议栈进行位置标识;在安卓平台下搭建定位终端,利用三角质心定位方法实现位置估计.该系统在传统RSSI定位方法的基础上,加入阶段去噪与平滑滤波过程,用于提高测距准确度和稳定性.在实验室楼道测试环境下,平均定位精度可达1.5m,具有布设方便、功耗低和绿色环保的特点.     

A mobile system for sedentary behaviors classification based on accelerometer and location data

BackgroundSedentary behaviors are associated to the development of noncommunicable diseases (NCD) such as cardiovascular diseases (CVD), type 2 diabetes, and cancer. Accelerometers and inclinometers have been used to estimate sedentary behaviors, however a major limitation is that these devices do not provide enough contextual information in order to recognize the specific sedentary behavior performed, e.g., sitting or lying watching TV, using the PC, sitting at work, driving, etc.ObjectivePropose and evaluate the precision of a mobile system for objectively measuring six sedentary behaviors using accelerometer and location data.ResultsThe system is implemented as an Android Mobile App, which identifies individual’s sedentary behaviors based on accelerometer data taken from the smartphone or a smartwatch, and symbolic location data obtained from Bluetooth Low Energy (BLE) beacons. The system infers sedentary behaviors by means of a supervised Machine Learning Classifier. The precision of the classification of five of the six studied sedentary behaviors exceeded 95% using accelerometer data from a smartwatch attached to the wrist and 98% using accelerometer data from a smartphone put into the pocket. Statistically significant improvement in the average precision of the classification due to the use of BLE beacons was found by comparing the precision of the classification using accelerometer data only, and BLE beacons localization technology.ConclusionsThe proposed system provides contextual information of specific sedentary behaviors by inferring with very high precision the physical location where the sedentary event occurs. Moreover, it was found that, when accelerometers are put in the user’s pocket, instead of the wrist and, when symbolic location is inferred using BLE beacons; the precision in the classification is improved. In practice, the proposed system has the potential to contribute to the understanding of the context and determinants of sedentary behaviors, necessary for the implementation and monitoring of personalized noncommunicable diseases prevention programs, for instance, sending sedentary behavior alerts, or providing personalized recommendations on physical activity. The system could be used at work to promote active breaks and healthy habits.     

Probabilistic location-dependent queries at different location granularities

Approaches for the processing of location-dependent queries usually assume that the location data are expressed precisely, usually using GPS locations. However, this is unrealistic because positioning methods do not have a perfect accuracy (e.g., the positioning approach used in cellular networks handles only the cell where mobile users are located). Besides, users may need to express queries based on concepts of locations other than traditional GPS locations, which we call location granules.In this paper, we focus on location granule-based query processing (i.e., processing of queries with location granules) in situations where the location data available is imprecise, which we have called probabilistic location-dependent queries. For that purpose, we exploit the concept of uncertainty location granule, which represents the location uncertainty of an object. In particular, we tackle the problem of processing probabilistic inside (range) constraints. We analyze in detail how those constraints can be processed, taking into account both the existence of location uncertainty affecting the relevant objects and the location granularity specified. An extensive experimental evaluation shows the feasibility of the proposed probabilistic query processing approach and analyzes the advantages of using index structures to speed up the query processing.     

改进的井下人员定位PDR算法研究

传统的行人航位推算(PDR)算法用于井下人员定位时,因步频检测、步长估计和航向估计阶段的姿态累计误差导致定位误差逐渐增大,而常用的零速校正、航向漂移消除、步态信号优化等误差修正方法无法改变PDR算法的固有缺陷,定位精度有待提高。提出采用改进的峰值检测法实现PDR算法中步频检测,基于深度循环神经网络(RNN)实现步长估计。将改进的PDR算法用于井下人员定位:首先采用手机加速度传感器、陀螺仪、磁力计获取行人运动数据;然后采用改进的峰值检测法获取固定时间间隔内的平均步频,与时间间隔、加速度及加速度方差作为特征输入训练后的深度RNN模型进行步长估计;最后结合估计的航向角预测人员当前位置。试验结果表明,改进的井下人员定位PDR算法对测试集数据的预测相对误差为5.9%,对实际测试路线的定位相对误差为1.6%~3.9%,小于传统PDR算法定位误差,有效提高了井下人员定位精度。     

CoSTUR: 面向用户评级的空间文本竞争选址

随着GPS定位技术和移动互联网的发展, 各类LBS (location-based service)应用积累了大量带有位置和文本标记的空间文本数据, 这些数据广泛应用于市场营销、城市规划等设施选址决策中. 空间文本选址的目标是从候选位置集合中挖掘最佳地点新建设施, 以期影响最多空间文本对象, 如用户或车辆等, 其中空间距离越接近且文本越相似则影响力越大. 现有方案未考虑现实普遍存在的同行竞争, 也忽略了用户对设施的评价因素. 为更合理地在同行竞争环境结合用户评级进行选址决策, 本文提出新的空间文本竞争选址问题CoSTUR. 通过引入权衡影响的确定性和数量的阈值, 解决传统模型中对象只能被单一设施影响的局限, 建模了用户可能同时受多个设施影响的真实情况. 借鉴经典的竞争均分模型, 实现了不同评级设施间竞争量化. 为降低大规模数据导致的高昂计算代价, 构建了新型空间文本索引结构TaR-tree, 并结合阈值设计基于影响范围的两个剪枝策略, 实现基于分支定界思想的空间连接和范围查询两种方案. 在真实和合成数据集上的实验结果显示, 相比基线算法计算效率能够提升近一个量级, 说明提出方法的有效性.