A soft computing based location-aware access control for smart buildings

The evolution of wireless communications and pervasive computing is transforming current physical spaces into real smart environments. These emerging scenarios are expected to be composed by a potentially huge amount of heterogeneous smart objects which can be remotely accessed by users via their mobile devices anytime, anywhere. In this paper, we propose a distributed location-aware access control mechanism and its application in the smart building context. Our approach is based on an access control engine embedded into smart objects, which are responsible to make authorization decisions by considering both user location data and access credentials. User location data are estimated using a novel indoor localization system based on magnetic field data sent by user through her personal phone. This localization system implements a combination of soft computing techniques over the data collected by smartphones. Therefore, our location-aware access control mechanism does not require any intermediate entity, providing the benefits of a decentralized approach for smart environments. From the results obtained, we can consider our proposal as a promising approach to tackle the challenging security requirements of typical pervasive environments.     

基于普适计算环境的三维空间RSSI位置感知研究

文中对室内定位应用中可能的几种技术进行了分析与对比,指出了各自的缺陷与不足。通过分析指出无线传感器网络自身的特点较其他几种技术更好地适应了普适计算环境对于位置感知服务的需求。采用无线传感器节点,把基于RSSI技术的测距方法作为研究位置感知的主要途径,提出了可行的三维空间位置感知模型及其相应的误差修正方案,并进行了充分的实验验证,证明该模型可以定位出目标较为准确的位置,其中所提出的误差修正方案很好地校正了目标点的实际位置。     

Head Up Games: combining the best of both worlds by merging traditional and digital play

Current pervasive games are mostly location-aware applications, played on handheld computing devices. Considering pervasive games for children, it is argued that the interaction paradigm existing games support limits essential aspects of outdoor play like spontaneous social interaction, physical movement, and rich face-to-face communication. We present a new genre of pervasive games conceived to address this problem, that we call “Head Up Games” (HUGs) to underline that they liberate players from facing down to attend to screen-based interactions. The article discusses characteristics of HUG and relates them to existing genres of pervasive games. We present lessons learned during the design and evaluation of three HUG and chart future challenges.     

保密社交意愿探测

研究保密意愿探测问题：Alice和Bob可以协同测试他们是否可以在某个理想区域共事,但不泄漏彼此的隐私信息.近年来,大部分的移动智能设备在出厂时都预装了位置感知设备,从而为开发者设计各种各样的提供位置识别与服务的应用软件提供了广阔的空间.然而很多情况下,用户间不愿意泄露自己的位置信息（或者活动范围）,仅通过一比特的信息探知（或知晓）各参与方是否愿意在某个（便于彼此的）区域内共同做某件事情.保密意愿探测协议可以实现这样的功能,并且能够保证各参与方位置信息不会泄露.首先,设计了一个新的基于高阶剩余类判定性难解问题的云外包同态加密方案;然后,基于该方案构造了一个保密意愿探测协议,并在ideal/real模型下证明了协议的安全性.     

User needs for location-aware mobile services

Mobile contexts of use vary a lot, and may even be continuously changing during use. The context is much more than location, but its other elements are still difficult to identify or measure. Location information is becoming an integral part of different mobile devices. Current mobile services can be enhanced with location-aware features, thus providing the user with a smooth transition towards context-aware services. Potential application fields can be found in areas such as travel information, shopping, entertainment, event information and different mobile professions. This paper studies location-aware mobile services from the user's point of view. The paper draws conclusions about key issues related to user needs, based on user interviews, laboratory and field evaluations with users, and expert evaluations of location-aware services. The user needs are presented under five main themes: topical and comprehensive contents, smooth user interaction, personal and user-generated contents, seamless service entities and privacy issues.     

Location awareness through trajectory prediction

Location-aware computing is a type of ubiquitous computing that uses user’s location information as an essential parameter for providing services and application-related optimization. Location management plays an important role in location-aware computing because the provision of services requires convenient access to dynamic location and location-dependent information. Many existing location management strategies are passive since they rely on system capability to periodically record current location information. In contrast, active strategies predict user movement through trajectories and locations. Trajectory prediction provides richer location and context information and facilitates the means for adapting to future locations. In this paper, we present two models for trajectory prediction, namely probability-based model and learning-based model. We analyze these two models and conduct experiments to test their performances in location-aware systems.     

一个普适计算环境中的定位隐私保护模型*

随着普适计算技术的发展,在普适环境中的应用服务也日益增多。这些服务通常都是基于用户位置的服务,然而,用户的定位信息中往往直接或间接地包含着用户的隐私内容。针对如何在获取个性化定制服务的同时保护用户的定位隐私这一问题展开讨论,提出了一种定位信息采集和假名使用的策略,并基于该策略建立了一个普适计算环境中的定位隐私保护模型。     

P3 systems: putting the place back into social networks

The availability of technologies enables a new class of location-aware information systems that link people-to-people-to-geographical-places (P3 systems). P3 systems can strengthen the relationship between social networks and physical places. They can also help individuals leverage location information to make new social ties and coordinate interactions that reinforce existing ties. Using the P3 systems framework, we describe the design space for location-aware community systems and important socio-technical challenges and opportunities.     

Accident aware localization mechanism for wireless sensor networks

Accurate location information is important for event reporting, coverage estimation, and location-aware routing in a Wireless Sensor Network (WSN). Recently, a number of range-free localization schemes have been proposed to provide each static sensor with location information, which is represented by a rectangular region. However, most WSN applications are applied in outdoor environments where the sensors’ location regions could be incorrect due to sudden accidents. This paper proposes an Active Location Correction Protocol, called ALCP, for detecting and correcting the occurrence of location error based on the bounding box technology. Performance study reveals that applying the ALCP to improve the location accuracies can enhance the performance of the well-known GPSR routing in terms of routing length, sensing coverage, and packet arrival rate.     

A location model for smart environments

This paper presents a location model for location-aware and user-aware services in smart environments. It can be dynamically organized like a tree based on geographical containment, such as that in a user–room–floor–building hierarchy and each node in the tree can be constructed as an executable software component. The model is unique in existing approaches because it enables location-aware services to be managed without any database servers, it can be managed by multiple computers, and it can provide a unified view of the locations of not only physical entities and spaces, including users and objects, but also computing devices and services. A prototype implementation of this approach was constructed on a Java-based mobile agent system. This paper presents the rationale, design, implementation, and applications of the prototype system.     

普适计算及其定位感知系统

普适计算的目的是为了使计算机更好地为人类服务，提高人们的生活质量。普适计算中的定位感知系统是普适计算研究中的核心部分之一，如何确定室内用户的动态位置信息，如何主动向用户提供各种所需的信息，这些都是其研究话题。给出了一种自行设计的普适计算室内定位感知系统的最小功能模型。     

An adaptive location prediction model based on fuzzy control

We focus on the proactivity feature of mobile applications. We propose a short-memory adaptive location predictor that realizes mobility prediction in the absence of extensive historical mobility information. Our predictor is based on a local linear regression model, while its adaptation capability is achieved through a fuzzy controller. Such fuzzy controller capitalizes on an appropriate size of historical mobility information in order to minimize the location prediction error and provide fast adaptation to any detected movement change. Our prediction experiments, performed with real GPS data, show the predictability and adaptability of the proposed location predictor.     

Privacy-Conscious Location-Based Queries in Mobile Environments

In location-based services, users with location-aware mobile devices are able to make queries about their surroundings anywhere and at any time. While this ubiquitous computing paradigm brings great convenience for information access, it also raises concerns over potential intrusion into user location privacy. To protect location privacy, one typical approach is to cloak user locations into spatial regions based on user-specified privacy requirements, and to transform location-based queries into region-based queries. In this paper, we identify and address three new issues concerning this location cloaking approach. First, we study the representation of cloaking regions and show that a circular region generally leads to a small result size for region-based queries. Second, we develop a mobility-aware location cloaking technique to resist trace analysis attacks. Two cloaking algorithms, namely MaxAccu_Cloak and MinComm_Cloak, are designed based on different performance objectives. Finally, we develop an efficient polynomial algorithm for evaluating circular-region-based kNN queries. Two query processing modes, namely bulk and progressive, are presented to return query results either all at once or in an incremental manner. Experimental results show that our proposed mobility-aware cloaking algorithms significantly improve the quality of location cloaking in terms of an entropy measure without compromising much on query latency or communication cost. Moreover, the progressive query processing mode achieves a shorter response time than the bulk mode by parallelizing the query evaluation and result transmission.     

位置感知计算的概论、关键问题和技术探讨

自从Mark Weiser在1991年提出普适计算的思想以来,计算模式经历主机计算、桌面计算的阶段后正朝普适计算方向蓬勃发展.上下文感知是普适计算的最重要的特征,同时也是主要的研究领域.自从二十世纪70年代美国军方推出军民两用的室外定位系统GPS,以及1989年Roy Want等开发出支持大规模使用、价格低廉的室内位置传感系统Active Badge以来,位置感知由于其高鲁棒性和确定性、技术的可获得性而成为当前上下文感知计算的一个真正的研究热点.本文从普适计算和智能空间的特征和要求出发,阐述了位置感知计算的主要概念、思想,并根据当前最新的研究状况,解释了位置感知计算面临的主要问题和相应的技术方法,最后叙述了作为本课题组研究的试验系统--智能教室的技术路线.     

A comprehensive approach to model and use context for adapting applications in pervasive environments

With an increasing diversity of pervasive computing devices integrated in our surroundings and an increasing mobility of users, it will be important for computer systems and applications to be context-aware. Lots of works have already been done in this direction on how to capture context data and how to carry it to the application. Among the remaining challenges are to create the intelligence to analyze the context information and deduce the meaning out of it, and to integrate it into adaptable applications. Our work focuses on these challenges by defining generic context storage and processing model and by studying its impact on the application core. We propose a reusable context ontology model that is based on two levels: a generic level and a domain specific level. We propose a generic adaptation framework to guarantee adaptation of applications to the context in a pervasive computing environment. We also introduce a comprehensive adaptation approach that involves content adaptation and presentation adaptation inline with the adaptation of the core services of applications. Our case study shows that the context model and the application adaptation strategies provide promising service architecture.     

基于无线局域网的室内临近位置检测代理实现

传统基于网络的位置服务系统主要是为远程用户提供查询移动对象位置的信息服务。而现有基于移动终端的位置感知服务不能满足位置上下文应用的要求．为了达到系统自动自发的上下文交互目的。需要在应用中定义一个位置检测代理来捕获移动设备的位置变化事件．生成有效的上下文信息．本文使用简单贝叶斯分类算法实现了基于无线局域网的临近位置检测代理．在室内环境中进行实验表明。该方法可根据实际需要调整位置检测的范围与准确度。具有可行性与灵活性．     

LACO: A location-aware cooperative query system for securely personalized services

Location-aware computing technology becomes promising for pervasive personalization services which run anytime, anywhere, and on any device. These services should be based on contextual queries that are provided in a fast and flexible manner. To do so, cooperative query answering may be useful to support query relaxation and to provide both approximate matches as well as exact matches. To facilitate query relaxation, a knowledge representation framework has been widely adopted which accommodates semantic relationships or distance metrics to represent similarities among data values. However, research shows few legacy cooperative query mechanisms that consider location-awareness. Hence, the purpose of this paper is to propose a securely personalized location-aware cooperative query that supports conceptual distance metric among data values, while considering privacy concerns around user context awareness. To show the feasibility of the methodology proposed in this paper, we have implemented a prototype system, LACO, in the area of site search in an actual large-scale shopping mall.     

Location-Aware Tools for Improving Public Transit Usability

Real-time arrival information, immediately available on mobile devices, can significantly enhance the usability of public transit systems. The OneBusAway system provides just such information to more than 7,000 Seattle-area bus riders per day. The authors describe a new location-aware native iPhone application for OneBusAway that provides bus stop and arrival information tailored to the user's location. Results from survey and user-study evaluations demonstrate quicker access to data using the location-aware tool. In addition, data for OneBusAway users as a whole show strikingly positive changes in rider satisfaction, the number of transit trips per week, reduced wait time at bus stops, and increased walking. The positive results also hold for the location-aware version users, suggesting the possibility of even further gains.     

Toward location-aware Web: extraction method,applications and evaluation

Location-based services (LBS) belong to one of the most popular types of services today. However, a recurring issue is that most of the content in LBS has to be created from scratch and needs to be explicitly tagged to locations, which makes existing Web content not directly usable for LBS. In this paper, we aim at making Web sites location-aware and feed this information to LBS. Our approach toward location-aware Web is threefold: First, we present a location extraction method: SALT. It receives Web sites as input and equips them with location tags. Compared to other approaches, SALT is capable of extracting locations with a precision up to the street level. Performance evaluations further show high applicability for practice. Second, we present three applications for SALT: Webnear.me, Local Browsing and Local Facebook. Webnear.me offers location-aware Web surfing through a mobile Web site and a smartphone app. Local Browsing adds the feature to browse by nearby tags, extracted from Web sites delivered by SALT. Local Facebook extends location tagging to social networks, allowing to run SALT on one’s own and one’s friends’ timeline. Finally, we evaluate SALT for technology acceptance of Webnear.me through a formative user study. Through real user data, collected during a 3 months pilot field deployment of Webnear.me, we assess whether SALT is a proper instance of “location of a Web site”.