Location Based Services Acceptance and Adoption Evaluation: An Investigation on Mobile Phone Users’ Response to Awareness and Utilization of LBS Technology in Nairobi Kenya

Location Based Navigation System (LBNS) is a specific Location Based Service (LBS) purely for navigational purpose. These systems resolve position of a user by using GNSS/GPS positioning technologies, to which supplementary information on goods and services are tagged. The navigation services have become popular and can be installed on mobile phones to provide route information, location of points of interest and user’s current location. LBS has continued to face challenges which include “communication” process towards user reference. Location Based Service System conveys suitable information through a mobile device for effective decision making and reaction within a given time span. This research was geared at understanding the state of LBS technology acceptance and adoption by users in Nairobi Kenya. To do this a quantitative study was carried out through a questionnaire, to investigate mobile phone users’ response on awareness and use of LBS technology. Testing the growth of this technology in this region compared to predictions in previous studies using Technology Acceptance Model (TAM), it is evident that many users may be aware of GPS functionality in mobile phones but are certainly yet to fully embrace the technology as they rarely use it. This points to some underlying challenges towards this technology within this part of the World, thereby recommending for deliberate monitoring and evaluation of LBS technology for sustenance growth based on user satisfaction and acceptance for improved usability.

Web-based GIS System for Real-time Field Data Collection Using Personal Mobile Phone

Recently, use of mobile communicational devices in field data collection is increasing such as smart phones and cellular phones due to emergence of embedded Global Position System GPS and Wi-Fi Internet access. Accurate timely and handy field data collection is required for disaster management and emergency quick responses. In this article, we introduce web-based GIS system to collect the field data by personal mobile phone through Post Office Protocol POP3 mail server. The main objective of this work is to demonstrate real-time field data collection method to the students using their mobile phone to collect field data by timely and handy manners, either individual or group survey in local or global scale research.

Effects of Exposure to GSM Mobile Phone Base Station Signals on Salivary Cortisol,Alpha-Amylase,and Immunoglobulin A

Objective The present study aimed to test whether exposure to radiofrequency electromagnetic fields （RF-EMF） emitted by mobile phone base stations may have effects on salivary alpha-amylase, immunoglobulin A （IgA）, and cortisol levels. Methods Fifty seven participants were randomly allocated to one of three different experimental scenarios （22 participants to scenario 1, 26 to scenario 2, and 9 to scenario 3）. Each participant went through five 50-minute exposure sessions. The main RF-EMF source was a GSM-900-MHz antenna located at the outer wall of the building. In scenarios 1 and 2, the first, third, and fifth sessions were ＂low＂ （median power flux density 5.2 μW/m^2） exposure. The second session was ＂high＂ （2126.8 μW/m^2）, and the fourth session was ＂medium＂ （153.6 μW/m^2） in scenario 1, and vice versa in scenario 2. Scenario 3 had four ＂low＂ exposure conditions, followed by a ＂high＂ exposure condition. Biomedical parameters were collected by saliva samples three times a session. Exposure levels were created by shielding curtains. Results In scenario 3 from session 4 to session 5 （from ＂low＂ to ＂high＂ exposure）, an increase of cortisol was detected, while in scenarios 1 and 2, a higher concentration of alpha-amylase related to the baseline was identified as compared to that in scenario 3. IgA concentration was not significantly related to the exposure. Conclusions RF-EMF in considerably lower field densities than ICNIRP-gnidelines may influence certain psychobiological stress markers.

Location correction technique based on mobile communication base station for earthquake population heat map

China has mobile phone penetration rate of over 96.2%.Mobile phone has become the largest Internet terminal for Chinese Internet users.Population geographic distribution in earthquake zones can be got based on mobile phone positioning and map matching.For reducing earthquake black-box stage,we propose a real-time collection,correction and schedule algorithm of population position data by four stream processing environments(Redis,Hbase,Kafka,and Spark Streaming)in this paper.For labeling precisely population geographic distribution on the network map,matching of population geographic coordinates and map coordinates are optimized by sample comparison based on location data of mobile communication base stations and prefecture level cities.The test result shows the proposed system is high efficient and can rapidly respond to any emerging parallel tasks during the earthquake.A high-precision heat map of affected population can be produced and published on-line within 2 min after the devastating earthquake happened.

Analysis of Geographical Distribution of Missing Children Based on the Missing Children Mobile GIS Mutual Assistance System of China

The Missing Children Mobile GIS Mutual Assistance System of China (MCMAS) is a mobile service software based on mobile GIS platform software, and it is committed to providing the most convenient and efficient system of personally mutual tracing services for missing children family and society. Relying on collaborative utilization of location-based service technology, face image intelligent recognition technology, cloud computing technology, public big data sharing technology, and mobile GIS technology, the MCMAS has achieved prominent application effects since it was deployed. At present, the MCMAS is running soundly, and it has received and released the information about 1011 missing children from May 25, 2016 to May 25, 2017. In order to explore the geographical distribution features and the influencing factors of missing children, the data of missing children are used for spatial and visual analysis by the data mining and GIS technologies. At the same time, we have built the spatial thermodynamic diagram of the big data of China missing children. By comparing provinces and cities with a higher proportion of missing children, the results showed that: 1) The high proportion of missing children spatially concentrated in the eastern part of the China. 2) The number of missing children was significantly correlated with the population density and economic status of the city. Furthermore, the paper macro-levelly presents a basic basis for rescuing the missing children from two aspects: regionally spatial characteristics and influencing factors.

Location Based Navigation Service Technology: Development of an Optimization Algorithm for Multivariate Contextual Cartographic Content in Location Based Navigation Service

User response or reaction to navigation applications is influenced by relevance in geographic information, in terms of cartographic context and content delivered within a definite time, providing a direct impact to outcome or consequence based on decision making and hence user reaction. Location Based Navigation Services (LBNS) have continuously advanced in cartographic visualization, making maps interpretation easy and ubiquitous to any user, as compared to pre-historic times when maps were a preserve of a few. Despite rapid growth in LBNS, there exist challenges that may be characterized as technical and non-technical challenges, among them being process of conveying geospatial information to user. LBNS system deliver appropriate information to a user through smartphone (mobile device) for effective decision making and response within a given time span. This research focuses on optimization of cartographic content for contextual information in LBNS to users, based on prevailing circumstances of various components that constitute it. The research looks into Geographic Information Retrieval (GIR), as a technical challenge centered on a non-technical issue of social being of user satisfaction, leading to decision making in LBNS, hence response and outcome. Though advanced technologically, current LBNS on information sourcing depends on user manual web pages navigation and maneuver, this can be painstaking and time consuming that it may cause unnecessary delay in information delivery, resulting to delayed information response time (DIRT). This in turn may lead to unappropriate decision making with erroneous reaction or response being taken, resulting in loss of opportunity, resources, time and even life. Optimization in LBNS is achieved by a mathematical relationship developed between user status, mobile device variables against cartographic content. The relationship is in turn applied in LBNS android application to fulfill optimization solution for user consumption.

基于大数据和无线网络的采摘机器人定位技术研究

分析了5G无线网络定位原理,提出了单基站定位技术和加权质心的5G定位技术,设计了采摘机器人定位系统硬件部分,并基于大数据和无线网络实现了采摘机器人定位系统。试验结果表明:系统具有较好的定位精度,优于单基站定位方法精度,且其定位曲线与北斗定位设备曲线拟合度非常高,稳定性较好。

中国失踪儿童互助Mobile GIS系统的设计与实现

针对目前失踪儿童案件频发且寻回率低这一社会问题,系统致力于为失踪儿童家庭和社会提供最为便捷高效的免费民间互助寻亲服务。依托基于位置的服务技术、人脸图像智能识别技术、云计算技术、公众大数据共享技术、移动互联网等技术的协同研究,从而构建移动GIS平台下的失踪儿童互助系统,实现了在寻找失踪儿童过程中有关公众案件的大数据登记与共享以及基于空间位置的人脸图像云端识别、移动互联网地图时序化标注、案例空间化自动追踪与高效反馈等一系列功能。目前系统运行平稳,已接收并发布了全国千余条寻人图文信息,将为亲属、政府、公众以及执法部门之间架起爱心互助的桥梁。

移动网络基站大数据无监督加密方法仿真

为了保证数据完整性和可靠性,会多次对数据收集和存储,导致同一数据被重复存储,增加了冗余度,使得对基站数据加密变得困难。为了解决上述问题,提出移动网络基站大数据无监督抗破译加密方法,通过建立无监督数据消冗算法,对于相同数据采用变长分块识别方法识别并删除重复数据,对于相似数据利用布隆过滤器算法识别并删除相似数据,降低数据冗余度。结合Logistic映射和Henon映射生成双混沌序列,将所得双混沌序列作为高级加密标准(Advanced Encryption Standard,AES)算法的加密密钥,以此实现移动网络基站大数据无监督抗破译加密。实验结果表明,所提方法加密、解密延时均低于12ms,且吞吐量高。

有限数据条件下智能体仿真模型构建方法

与传统的集计评估模型不同,智能体仿真模型能够捕捉个体之间的行为交互,在交通政策精细化评估中具有优势。但智能体仿真模型对数据要求较高,在实践中面临活动计划生成、参数标定和结果验证等难点。基于MATSim建立了在有限数据条件下面向应用研究的可操作、可复现的智能体仿真模型,并且以上海市拥堵收费评估场景为例详细介绍了模型的建模流程和关键技术。重点介绍基于手机轨迹数据的活动计划生成方法以及模型的参数标定和结果验证细节。结果表明,智能体仿真模型能够满足交通政策评估需求,基准场景的上海市域出行方式划分平均相对误差为8%、快速路交通量平均相对误差为17%。进而从集计和个体两个层面对仿真结果进行分析,展示了智能体仿真模型的应用潜力。

城市轨道交通换乘站位置对乘客换乘路径选择的影响

[目的]城市轨道交通乘客实际出行中存在一些不宜量化的因素(如换乘站在线网中的位置等)。这些因素难以量化折算为城市轨道交通多路径概率选择模型中的出行路径阻抗,需要研究这些因素对乘客路径选择的影响。[方法]根据换乘站在城市轨道交通路径中的位置将换乘站划分为居路径前段、居路径中间、居路径后段三类。基于手机信令获取得到的上海轨道交通线网乘客出行数据,选取其中的典型OD(起讫点)对及符合研究要求的换乘站,将多路径概率选择模型计算得到的选择比例与路径实际选择比例进行对比,分析得到不同换乘站类型对乘客换乘路径选择的影响规律。[结果及结论]与居路径中间换乘站相比,乘客更趋于选择在居路径前段、居路径后段的换乘站进行换乘,其路径实际选择比例较模型计算选择比例约高10%。构建多路径概率选择模型时,不能简单地将换乘因素量化折算为阻抗,应对各换乘因素进行综合考虑。

基于手机信令数据的城市通勤碳排放分析

文中提出了一种在缺少用户个人社会经济属性数据的情况下,基于低频手机信令数据、POI数据、互联网位置数据,以及先验知识的面向宏观碳排放核算的出行方式判别方法,并通过基于实际通勤距离的自下而上碳排放计算方法实现不同通勤出行方式碳排放量化.基于提出的核算方法对上海市31 938人次的通勤碳排放进行了核算分析.结果表明:不同交通方式通勤碳排放量差异显著;存在高碳排放通勤群体,其样本量仅占总样本的11%,但其产生的碳排放占总量的55%.高碳排放通勤是长距离通勤和高碳排放出行方式共同影响的结果.

手机位置数据中“乒乓效应”的时空特征研究

“乒乓效应”是手机位置数据中一种典型的噪声数据,分析其时空分布特征对科学应对噪音数据影响、准确理解分析结果、提高手机位置数据质量具有重要意义。本研究基于速度阈值、重复跳转和频繁大幅度转向3种模式的“乒乓效应”检测方法,采用3个不同研究区(上海、西宁和深圳)的手机位置数据,构建了时间与空间易发指数,对手机数据中的“乒乓效应”进行识别,并从跳转距离特征、空间分布特征、时间分布特征3个方面进行了对比分析。结果表明:空间分布上,“乒乓效应”总体呈现出较高的空间自相关现象,表现为远郊区易发、基站密度高处不易发的特点;在时间分布特征上,呈现出白天易发、夜晚不易发的特点;同时“乒乓效应”的存在会对研究结果产生一定程度的影响。

基于用户信令结合路网拟合轨迹研究

通信技术的快速发展和移动设备普及率的提高,使位置服务(LBS)在各行业中得到了广泛应用。文中提出了一种基于用户信令和路网拟合的方法,在收集用户位置信息及信令数据后,使用基于路网的轨迹拟合算法进行匹配,以获取更精确的位置信息。最后,验证了该方法能有效提高轨迹匹配精度和位置估计准确度,能为智能交通、物流等领域提供有效的数据支持。

基于手机信令的地铁站服务特征影响因素研究

地铁站点的服务特征是评价地铁站点服务效率、引导站点周边城市更新及开发建设的重要依据。本研究采用手机信令数据作为实测数据分析站点的实际服务范围,以杭州市地铁1、2、4号线为例,从服务范围、乘客流量、服务对象三方面对地铁站点服务特征进行较为全面的分析,弥补既往研究在研究方法和数据获取方面所存在的局限性。在此基础上,从宏观、中观、微观三个层面探究地铁站点服务特征的影响因素,研究表明:宏观层面的空间结构和站点区位对站点服务特征的影响最为显著;站点流量、服务形态等特征受周边土地使用的影响也较为明显;当站点区位和周边用地条件相似时,其他交通方式接驳和道路网络结构则会发挥较大作用。

5G通信基站周围电磁辐射水平影响因素研究

随着5G通信基站的大规模建设,5G通信基站的电磁辐射安全成为居民日渐担忧的问题,所以了解各因素对周围电磁辐射水平的影响是环境现场监测的关键之一,该文通过现场监测所得数据进行分析和研究,以期分析结果能为相关监测工作者提供一些帮助和参考。

出行活动模型等研究动态

选取来自国际学术期刊的论文,以概述形式对城市交通理论方法、实证分析等学术研究成果进行总结性介绍,旨在增强城市交通业界和学界对国际学术动向和研究热点的关注,促进学术交流。本期共选取2篇论文:《基于长短期记忆网络和手机信令数据的出行活动模型》一文提出一个新的基于长短期记忆网络的出行活动模型框架,该模型框架能够根据手机信令数据识别的出行详细信息直接分析个人出行行为偏好,减少对社会经济属性和活动类型等信息的需求,同时可以很好地预测与时间相关的信息,并具有最佳的稳定性;《用于自动驾驶卡车编队的聚合零知识证明和区块链授权身份验证》一文提出一种聚合高效的零知识证明方法,用于卡车混合队列环境中基于许可区块链网络进行隐私保护身份验证,其能以毫秒为单位执行身份验证,与单一零知识证明设计相比,聚合高效的零知识身份验证系统具有更高的安全性和更好的性能。

位置大数据的价值提取与协同挖掘方法

随着位置服务和车联网应用的不断普及,由地理数据、车辆轨迹和应用记录等所构成的位置大数据已成为当前用来感知人类社群活动规律、分析地理国情和构建智慧城市的重要战略性资源,是大数据科学研究极其重要的一部分.与传统小样统计不同,大规模位置数据存在明显的混杂性、复杂性和稀疏性,需要对其进行价值提取和协同挖掘,才能获得更为准确的移动行为模式和区域局部特征,从而还原和生成满足关联应用分析的整体数据模型.因此,着重从以下3个方面系统综述了针对位置大数据的分析方法,包括:(1)针对数据混杂性,如何先从局部提取出移动对象的二阶行为模式和区域交通动力学特征;(2)针对数据复杂性,如何从时间和空间尺度上分别对位置复杂网络进行降维分析,从而建立有关社群整体移动性的学习和推测方法;(3)针对数据的稀疏性,如何通过协同过滤、概率图分析等方法构建位置大数据全局模型.最后,从软件工程角度提出了位置大数据分析的整体框架.在这一框架下,位置数据将不仅被用来进行交通问题的分析,还能够提升人们对更为广泛的人类社会经济活动和自然环境的认识,从而体现位置大数据的真正价值.

基于移动定位的行为数据采集与地理应用研究

微观个体行为的研究是人文地理学者解释人文地理现象的重要视角,而个体时空数据的获取是制约行为研究的重要瓶颈之一。随着手机的普及,移动定位服务为个体时空数据的获取提供了新的技术手段。通过与人口普查、交通调查等传统移动性数据获取方法的比较,基于移动定位的时空行为数据所具有特点包括:(1)采集个体位置和移动信息真实;(2)定位精度高、信号覆盖广;(3)可持续实时动态获取移动信息;(4)可减少行为数据编码过程的信息损失,适合大规模采集。详细介绍了基于移动通信网络和手机终端的移动定位技术原理,并通过微观个体行为分析和宏观城市动态空间规划的两个典型案例,实证基于移动定位的时空行为数据在城市规划等领域的可行性和适用性。移动定位方法显示出了巨大的技术优势和应用前景,但一些重要的基础性问题仍没有解决,特别是个人的隐私保护和移动定位的地理尺度问题。现有的研究成果表明,基于移动定位数据的地理应用仍处在试验和探索阶段,新的数据获取协议、数据分析方法、地理时空模式提取方法等研究亟待展开。

基于地面移动通信基站的差分气压测高方法

为了解决现有的卫星定位系统高程定位精度较低的问题,提出利用已发展完备的地面移动通信基站作为气压差分测量基准点的差分气压测高的方法.该方法以用户接收机附近的分布密集的地面移动通信基站为气压校正基准点,并利用移动通信基站的传输链路把相关的测量数据传送给用户,用户接收机便可以用移动通信基站观测点的高程值、气压值以及温度值,结合接收机测点处的气压值和温度值,利用高程与气压值之间的对应关系,得到用户接收机处的绝对高程值.实际试验结果表明:使用本方法后,室内高程定位精度约为1 m,室外的高程定位精度优于1 m.测高分辨率约为0.2 m,可以使GNSS(Global Navigation SatelliteSystem)的三维位置定位精度提高约60%.本方法不仅可以弥补GNSS高程精度差的缺陷,作为高程约束参与测量方程解算还会提高水平测量精度,而且还克服了传统的气压测高精度依赖于气象站,而大多数用户接收机离气象站的距离较远,造成气压测高精度偏低的局限性.所以本方法能辅助增强卫星导航系统,提高三维定位精度,用于室内定位可以解决室内楼层的分辨问题.