Guide robot intelligent navigation in urban environments

This paper presents an intelligent robotic system to guide visually impaired people in urban environments. The robot is equipped with two laser range finders, global positioning system (GPS), camera, and compass sensors. All the sensors data are processed by a single laptop computer. We have implemented different navigation algorithms enabling the robot to move autonomously in different urban environments. In pedestrian walkways, we utilize the distance to the edge (left, right, or both) to determine the robot steering command. In difference from pedestrian walkways, in open squares where there is no edge information, artificial neural networks map the GPS and compass sensor data to robot steering command guiding the visually impaired to the goal location. The neural controller is designed such as to be employed even in environments different from those in which they have been evolved. Another important advantage is that a single neural network controls the robot to reach multiple goal locations inside the open square. The proposed algorithms are verified experimentally in a navigation task inside the University of Toyama Campus, where the robot moves from the initial to goal location.     

Trip planning queries with location privacy in spatial databases

Privacy has become a major concern for the users of location-based services (LBSs) and researchers have focused on protecting user privacy for different location-based queries. In this paper, we propose techniques to protect location privacy of users for trip planning (TP) queries, a novel type of query in spatial databases. A TP query enables a user to plan a trip with the minimum travel distance, where the trip starts from a source location, goes through a sequence of points of interest (POIs) (e.g., restaurant, shopping center), and ends at a destination location. Due to privacy concerns, users may not wish to disclose their exact locations to the location-based service provider (LSP). In this paper, we present the first comprehensive solution for processing TP queries without disclosing a user’s actual source and destination locations to the LSP. Our system protects the user’s privacy by sending either a false location or a cloaked location of the user to the LSP but provides exact results of the TP queries. We develop a novel technique to refine the search space as an elliptical region using geometric properties, which is the key idea behind the efficiency of our algorithms. To further reduce the processing overhead while computing a trip from a large POI database, we present an approximation algorithm for privacy preserving TP queries. Extensive experiments show that the proposed algorithms evaluate TP queries in real time with the desired level of location privacy.     

Using check-in features to partition locations for individual users in location based social network

With location-based social network (LBSN) flourishing, location check-in records offer us sufficient information resource to do relative mining. Among locations visited by a user, those attracting relatively more visits from that user can serve as a support for further mining and improvement for location-based services. Therefore, great significance lies in the partition for visited locations based on a user’s visiting frequency. The aim of our paper is to partition locations for individual users by utilizing classification in machine learning, categorizing the location for a user once he or she makes initial check-in there. After feature extraction for each initial check-in record, we evaluate the contribution of three feature categories. The results show the contribution of different feature categories varies in classification, where social features appear to offer the least contribution. At last, we do a final test on the whole sample, comparing the results with two baselines based on majority voting respectively. The results largely outperform the baselines in general, demonstrating the effectiveness of classification.     

一种基于道路网络的移动目标数据库模型

移动目标数据库(moving object database)有别于一般数据库技术的重要特征之一就是不仅可以对移动目标在数据库记录的时刻进行位置查询,而且可以对不同记录时刻之间以及未来时刻的位置进行查询,其研究的首要问题是建立移动目标运动及位置更新模型.目前有大量依靠其他辅助设备(如GSM网络)定位的盲终端设备(如移动电话,PDA等),存在着MOD管理的潜在需求,需要对它们建立合适的运动及位置更新模型,来为移动用户提供基于位置的服务.针对这类无自定位能力的移动目标,利用它们通常运动在城市的道路网络上这一特点,提出了基于道路网络的移动目标历史和未来速度计算模型,在此基础上提出了基于道路网络的非等时位置更新模型.与传统的速度计算模型相比,基于道路网络的移动目标历史和未来速度计算模型在考虑移动目标定位误差时可以降低移动目标位置预测的误差;与等时位置更新模型相比,基于道路网络的非等时位置更新模型在平均预测误差相近的情况下,可以减少移动目标和定位设施之间的通信量.     

Examining the impact of the precision of address geocoding on estimated density of crime locations

This study examines the impact of the precision of address geocoding on the estimated density of crime locations in a large urban area of Japan. The data consist of two separate sets of the same Penal Code offenses known to the police that occurred during a nine-month period of April 1, 2001 through December 31, 2001 in the central 23 wards of Tokyo. These two data sets are derived from older and newer recording system of the Tokyo Metropolitan Police Department (TMPD), which revised its crime reporting system in that year so that more precise location information than the previous years could be recorded. Each of these data sets was address-geocoded onto a large-scale digital map, using our hierarchical address-geocoding schema, and was examined how such differences in the precision of address information and the resulting differences in address-geocoded incidence locations affect the patterns in kernel density maps.An analysis using 11,096 pairs of incidences of residential burglary (each pair consists of the same incidents geocoded using older and newer address information, respectively) indicates that the kernel density estimation with a cell size of 25×25 m and a bandwidth of 500 m may work quite well in absorbing the poorer precision of geocoded locations based on data from older recording system, whereas in several areas where older recording system resulted in very poor precision level, the inaccuracy of incident locations may produce artifactitious and potentially misleading patterns in kernel density maps.     

基于位置服务中的连续查询隐私保护研究

近年来,伴随着移动计算技术和无限设备的蓬勃发展,位置服务中的隐私保护研究受到了学术界的广泛关注,提出了很多匿名算法以保护移动用户的隐私信息.但是现有方法均针对snapshot查询,不能适用于连续查询.如果将现有的静态匿名算法直接应用于连续查询,将会产生隐私泄露、匿名服务器工作代价大等问题.针对这些问题,提出了δp-隐私模型和δq-质量模型来均衡隐私保护与服务质量的矛盾,并基于此提出了一种贪心匿名算法.该算法不仅适用于snapshot查询,也适用于连续查询.实验结果证明了算法的有效性.     

Recommendation of location-based services based on composite measures of trust degree

As more and more users use the mobile terminals of high computing power, the location-based services (LBS) recommendations for mobile users have become an important and interesting topic. Mobile users are eager to get their interested and reliable services quickly. A considerable number of research works have been dedicated to service recommendation based on users’ preferences and locations. In this paper, we study the credibility of recommended services, and propose a set of composite measures on how to provide more reliable services. We further propose the trustworthy Skyline of LBS recommendation in terms of the trust degree based on the newly introduced composite measures to achieve more credibility to provide recommendation services. Experimental results show that our method can recommend desired and trusted services to users.     

Remote service discovery and binding architecture for soft real-time QoS in indoor location-based service

Indoor location-based service (LBS) is generally distinguished from web services that have no physical location and user context. In particular, various resources have dynamic and frequent mobility in indoor environments. In addition, an indoor LBS includes numerous service lookups being requested concurrently and frequently from several locations, even through a network infrastructure requiring high scalability in indoor environments. The traditional centralized LBS approach needs to maintain a geographical map of the entire building or complex in its central server, which can cause low scalability and traffic congestion. This paper presents a self-organizing and fully distributed indoor LBS platform with regional cooperation among devices. A service lookup algorithm based on the proposed distributed architecture searches for the shortest physical path to the nearest service resource. A continuous service binding mechanism guarantees a probabilistic real-time QoS regardless of dynamic and frequent mobility in a soft real-time system such as an indoor LBS. Performance evaluation of the proposed algorithm and platform is compared to the traditional centralized architecture in the experimental evaluation of scalability and real test bed environments.     

路网环境下的语义多样性位置隐私保护方法

针对位置服务中基于K-匿名方法构造的匿名集因未考虑语义信息导致语义推断攻击问题,提出了一种路网环境下的语义多样性位置隐私保护方法。该方法根据不同语义位置用户访问数量,利用欧氏距离选择具有相似特性的语义位置类型,构建最优语义位置类型集合。根据路段上属于该类型集的语义位置所占比例,选择最优路段构建匿名集,使得匿名集不仅满足语义多样性,而且增加了用户语义位置的不确定性。实验结果表明,与LSBASC算法相比,该方法在平均匿名时间上提高了27%,SDA算法的执行效率更好。在相对空间粒度上减小了21%,隐私泄露程度上降低了3%,SDA算法以更小的匿名空间提供更高的服务质量和隐私保护程度,能有效地保护用户语义位置隐私。     

基于ResNet的音频场景声替换造假的检测算法

针对造假成本低、不易察觉的音频场景声替换的造假样本检测问题，提出了基于ResNet的造假样本检测算法。该算法首先提取音频的常数Q频谱系数（CQCC）特征，之后由残差网络（ResNet）结构学习输入的特征，结合网络的多层的残差块以及特征归一化，最后输出分类结果。在TIMIT和Voicebank数据库上，所提算法的检测准确率最高可达100%，错误接收率最低仅为1.37%。在现实场景下检测由多种不同录音设备录制的带有设备本底噪声以及原始场景声音频，该算法的检测准确率最高可达99.27%。实验结果表明，在合适的模型下利用音频的CQCC特征来检测音频的场景替换痕迹是有效的。     

Location determination of mobile devices for an indoor WLAN application using a neural network

Due to the popularity of location-based services, determining the location of a device at all times has become a subject of great interests. Although many GPS-based applications have been developed and successfully deployed in various fields, their applicabilities are hindered by the obstruction of the objects in the environment. Essentially, as satellite signals cannot penetrate the walls of buildings, the coverage of GPS systems is limited to outdoor environments. To fully exploit the benefit of location-based services, approaches that determine the location of a device in indoor environments need to be established. This study presents a novel location determination mechanism that uses an indoor WLAN and back-propagation neural network (BPN). A museum is taken as the context of the example indoor environment. Location determination is achieved using the combined strengths of 802.11b wireless access signals. With a significant number of access points (APs) installed in the museum, hand-held devices can sense the strengths of the signals from all APs to which the devices can connect. Using a back-propagation network, device locations can be estimated with sufficient accuracy. A novel adaptive algorithm is implemented for enhancing the accuracy of the estimation.

位置隐私保护技术综述

随着如智能手机和平板电脑等移动设备的普及,基于位置的服务(LBS)变得越来越流行,人们通过网络进行查询的同时,将自己的位置信息暴露给了LBS提供商。如何保护用户的位置信息不被潜在地泄露给LBS提供商,对一个LBS系统来说是至关重要的。目前关于LBS的隐私保护的研究已经取得了一定的成果,为了更深入地解决位置隐私保护技术中还没有解决的诸多问题,展开对相关课题的深入研究,从非k-匿名位置隐私技术、k-匿名位置隐私技术、P2P架构下的k-匿名技术和连续查询轨迹匿名技术四个方面对相关文献进行了综述,分别介绍了相关的算法。最后,总结了位置隐私保护技术当前存在的问题及未来的发展方向。     

Capturing the response of players to a location-based game

Location-based games offer opportunities for us to learn more about people’s interactions and feelings towards the environment they are in as well as to understand more about the mental models and locations associated with known environments, e.g. a university campus with its associations of learning. In our study, we wanted to manipulate the activities in a game to take advantage of certain locations in the hope of producing certain emotional reactions. However, it is not enough to simply produce these reactions; one must also have a way of capturing any emotions produced whether these are the ones expected or not. The objective of this paper, therefore, was to trial a new methodology for location-based games that aims at capturing the players’ emotional reactions to the activities in a game whilst in certain locations. In order to test the methodology, we designed a location-based game that can be played on any Bluetooth-enabled mobile phone that has an accelerometer. The game has been designed to interweave with a persons’ normal activity. As a result, there is little distinction between gaming time and non-gaming time.     

Recording and playing back interactive media streams

Recording systems and media servers for networked audio and video streams have become an important part of today's Internet. In contrast to this, only a few recording and playback solutions currently exist for the data streams of interactive media applications (e.g., shared whiteboards and distributed virtual environments). So far these solutions are application-specific: individual algorithms and implementations are required for each application that is to be recorded. In this paper, we are proposing generic algorithms for the recording and playback of interactive media streams. These algorithms are based on a common model for the class of interactive media. They enable full random access to recordings by initializing the replaying applications with the required state information (e.g., the current slide in a recorded presentation). We have implemented these algorithms in the Interactive Media on Demand (IMoD) system. In order to interpret the semantics of an interactive media stream, the system requires that the Real-Time Application-Level Protocol for Distributed Interactive Media (RTP/I) protocol is used for the framing of the transmitted data. Any application using RTP/I can be recorded directly using the system without any modification. Interactive media streams not using RTP/I can be recorded using the generic recording algorithms. However, they require an adaptation of the system so that it is able to extract a minimal set of information from the application-level protocol of these streams. In addition to the generic recording algorithms, we present the architecture and major design considerations of the system and discuss the experiences gained from recording different interactive media applications.     

Birds of a feather locate together? Foursquare checkins and personality homophily

In this paper we consider whether people with similar personality traits have a preference for common locations. Due to the difficulty in tracking and categorising the places that individuals choose to visit, this is largely unexplored. However, the recent popularity of location-based social networks (LBSNs) provides a means to gain new insight into this question through checkins - records that are made by LBSN users of their presence at specific street level locations. A web-based participatory survey was used to collect the personality traits and checkin behaviour of 174 anonymous users, who, through their common check-ins, formed a network with 5373 edges and an approximate edge density of 35%. We assess the degree of overlap in personality traits for users visiting common locations, as detected by user checkins. We find that people with similar high levels of conscientiousness, openness or agreeableness tended to have checked-in locations in common. The findings for extraverts were unexpected in that they did not provide evidence of individuals assorting at the same locations, contrary to predictions. Individuals high in neuroticism were in line with expectations, they did not tend to have locations in common. Unanticipated results concerning disagreeableness are of particular interest and suggest that different venue types and distinctive characteristics may act as attractors for people with particularly selective tendencies. These findings have important implications for decision-making and location.     

数据广播环境下基于数据共享的位置相关skyline查询

数据广播环境下位置相关skyline查询是同时涉及空间位置属性和非空间多维属性的一类新的skyline查询类型,可广泛地应用于地理信息系统、城市规划、智能交通等领域。与传统环境下的位置相关skyline查询相比,数据广播环境下位置skyline查询面临一些新的问题,如广播信道的线性特性、移动设备资源受限性等。针对这些问题,本文提出了基于数据共享的位置相关查询算法,该方法通过共享邻近移动设备缓存的查询结果来改进查询算法的性能。广泛的实验结果显示,在移动设备密度较大的对等网络中,本文提出的算法具有较明显的优势,能显著地提升查询性能。     

Smartphone-based pedestrian tracking in indoor corridor environments

As the use of smartphones spreads rapidly, user localization becomes an important issue for providing diverse location-based services (LBS). While tracking users in outdoor environments is easily done with GPS, the solution for indoor tracking is not trivial. One common technique for indoor user tracking is to employ inertial sensors, but such a system needs to be capable of handling noisy sensors that would normally lead to cumulative locating errors. To reduce such error, additional infrastructure has often been deployed to adjust for these cumulative location errors. As well, previous work has used highly accurate sensors or sensors that are strapped to the body. This paper presents a stand-alone pedestrian tracking system, using only a magnetometer and an accelerometer in a smartphone in indoor corridor environments that are normally laid out in a perpendicular design. Our system provides reasonably accurate pedestrian locations without additional infrastructure or sensors. The experiment results show that the location error is less than approximately 7 m, which is considered adequate for indoor LBS applications.     

Interweaving place and story in a location-based audio drama

This paper presents a qualitative study of an interactive audio drama facilitated by a location-based application. The investigation focuses on an accessible experience, a play in which the audience members simply trigger new scenes of the audio drama as they walk to predefined city areas. The findings draw attention to the role of the mobile technology in facilitating this particular artistic experience. Furthermore, they illustrate the various levels at which creative imagination and open interpretation emerge as audience members seek to make sense of the interrelations between the locative media experienced and elements of the places inhabited during the audio narrative. In concluding the article, designing for loose coupling between mobile media and physical places is suggested as a strategy to enable people’s engagement in meaningful experience through the use of various location-based services.