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.

Free-walking:Pedestrian inertial navigation based on dual foot-mounted IMU

The inertial navigation system(INS),which is frequently used in emergency rescue operations and other situations,has the benefits of not relying on infrastructure,high positioning frequency,and strong real-time performance.However,the intricate and unpredictable pedestrian motion patterns lead the INS localization error to significantly diverge with time.This paper aims to enhance the accuracy of zero-velocity interval(ZVI)detection and reduce the heading and altitude drift of foot-mounted INS via deep learning and equation constraint of dual feet.Aiming at the observational noise problem of low-cost inertial sensors,we utilize a denoising autoencoder to automatically eliminate the inherent noise.Aiming at the problem that inaccurate detection of the ZVI detection results in obvious displacement error,we propose a sample-level ZVI detection algorithm based on the U-Net neural network,which effectively solves the problem of mislabeling caused by sliding windows.Aiming at the problem that Zero-Velocity Update(ZUPT)cannot suppress heading and altitude error,we propose a bipedal INS method based on the equation constraint and ellipsoid constraint,which uses foot-to-foot distance as a new observation to correct heading and altitude error.We conduct extensive and well-designed experiments to evaluate the performance of the proposed method.The experimental results indicate that the position error of our proposed method did not exceed 0.83% of the total traveled distance.

“互联网+”背景下导学互动与BOPPPS模式在《LBS技术与应用》课程中的教学探索

全球卫星导航定位系统逐步成为一个全球性的新兴高新技术产业,LBS技术将充分发挥全球卫星导航定位系统的相关功能,在此基础上提供丰富的服务。如何开展LBS技术的学习,并将理论落实到实际需要深入探究。本文提出“互联网+”的大背景下将导学互动与BOPPPS模式相结合,可以克服现有《LBS技术与应用》新课程教学面临的问题,对教学质量的提高以及相关专业的建设具有重要的意义,同时对全球卫星导航系统的运用提供新的思路。

A Framework of Web Data Integrated LBS Middleware

In this paper, we propose a flexible locationbased service （LBS） middleware framework to make the development and deployment of new location based applications much easier. Considering the World Wide Web as a huge data source of location relative information, we integrate the common used web data extraction techniques into the middleware framework, exposing a unified web data interface for the upper applications to make them more attractive. Besides, the framework also emphasizes some common LBS issues, including positioning, location modeling, location-dependent query processing, privacy and secure management.

Design and implementation of user information sharing system using location-based services for social network services

Internet takes a role as a place for communication between people beyond a space simply for the acquisition of information.Recently,social network service(SNS)reflecting human’s basic desire for talking and communicating with others is focused on around the world.And location-based service(LBS)is a service that provides various life conveniences like improving productivity through location information,such as GPS and WiFi.This paper suggests an application combining LBS and SNS based on Android OS.By using smart phone which is personal mobile information equipment,it combines location information with user information and SNS so that the service can be developed.It also maximizes sharing and use of information via twit based on locations of friends.This proposed system is aims for users to show online identity more actively and more conveniently.

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.

Factors influencing user adoption of location based service:From the expanded TAM perspective

Purpose:This study intends to examine the factors influencing user adoption of location based service(LBS).Design/methodology/approach:This paper develops the research model for user adoption of LBS with the technology acceptance model(TAM) as the theoretical foundation.Using a questionnaire and sampling method,empirical data was collected from 386 participants.Structured equation modeling was used to test the validity of the proposed model.Findings:The results show that I) perceived ease of use.perceived usefulness and perceived playfulness were direct determinants of behavioral intention,and perceived ease of use has the greatest impact of the three;2) emergency,ubiquity,technology maturity and social trust all have positive and significant impacts on perceived ease of use;3) emergency and social trust significantly influence perceived usefulness positively:4) individualization and social impact significantly affect perceived playfulness positively.Research limitations:Subjects were from China’s mainland,which limits the generalizability of the research findings.The interaction effects of age,gender and user experience were not included.Practical implications:This study offers LBS operators,marketers and application developers insights into the way to attract more users by increasing perceived usefulness,ease of use and playfulness of LBS.Originality/value:Location based service is still a relatively new concept and there were few theoretical and empirical studies that examine user adoption of the serv ice.This study contributes to existing LBS adoption studies by modifying and extending TAM and meanwhile the empirical study will help the research community gain a deeper understanding of the factors affecting user adoption of LBS.

Fusing Spatio-Temporal Contexts into DeepFM for Taxi Pick-Up Area Recommendation

Short-term GPS data based taxi pick-up area recommendation can improve the efficiency and reduce the overheads.But how to alleviate sparsity and further enhance accuracy is still challenging.Addressing at these issues,we propose to fuse spatio-temporal contexts into deep factorization machine(STC_DeepFM)offline for pick-up area recommendation,and within the area to recommend pick-up points online using factorization machine(FM).Firstly,we divide the urban area into several grids with equal size.Spatio-temporal contexts are destilled from pick-up points or points-of-interest(POIs)belonged to the preceding grids.Secondly,the contexts are integrated into deep factorization machine(DeepFM)to mine high-order interaction relationships from grids.And a novel algorithm named STC_DeepFM is presented for offline pick-up area recommendation.Thirdly,we devise the architecture of offline-to-online(O2O)recommendation respectively based on DeepFM and FM model in order to tradeoff the accuracy and efficiency.Some experiments are designed on the DiDi dataset to evaluate step by step the performance of spatio-temporal contexts,different recommendation models,and the O2O architecture.The results show that the proposed STC_DeepFM algorithm exceeds several state-of-the-art methods,and the O2O architecture achieves excellent real-time performance.

定位技术在物联网领域的应用发展分析

首先梳理定位技术的发展,总结并对比分析各类定位技术的原理和特点,然后阐述定位技术在智能交通、物流、医疗等物联网行业领域的应用现状,最后,基于市场发展预测定位技术在物联网中的应用发展前景,并从技术演进角度分析定位技术在物联网环境下发展所面临的挑战。

An Entropy-Based Model for Recommendation of Taxis’Cruising Route

Cruising route recommendation based on trajectory mining can improve taxi-drivers'income and reduce energy consumption.However,existing methods mostly recommend pick-up points for taxis only.Moreover,their performance is not good enough since there lacks a good evaluation model for the pick-up points.Therefore,we propose an entropy-based model for recommendation of taxis'cruising route.Firstly,we select more positional attributes from historical pick-up points in order to obtain accurate spatial-temporal features.Secondly,the information entropy of spatial-temporal features is integrated in the evaluation model.Then it is applied for getting the next pick-up points and further recommending a series of successive points.These points are constructed a cruising route for taxi-drivers.Experimental results show that our method is able to obviously improve the recommendation accuracy of pick-up points,and help taxi-drivers make profitable benefits more than before.

Extracting Campus’Road Network from Walking GPS Trajectories

Road network extraction is vital to both vehicle navigation and road planning.Existing approaches focus on mining urban trunk roads from GPS trajectories of floating cars.However,path extraction,which plays an important role in earthquake relief and village tour,is always ignored.Addressing this issue,we propose a novel approach of extracting campus’road network from walking GPS trajectories.It consists of data preprocessing and road centerline generation.The patrolling GPS trajectories,collected at Hunan University of Science and Technology,were used as the experimental data.The experimental evaluation results show that our approach is able to effectively and accurately extract both campus’trunk roads and paths.The coverage rate is 96.21%while the error rate is 3.26%.

Representation and Organization for Spatial Data in LBS

Aiming at the special demand on SVG_based representation and organization for spatial data in location based services（LBS）, the research is made in this article on the conversion method from multiple formats to SVG format, and a harris_corner detector method is proposed and verified to evaluate the conversion result. Based on the above, an optimized compression arithmetic is proposed, which integrated the characteristic of code simplification and GZIP compression. The test shows that the techniques on conversion and compression are feasible, which means that SVG_based representation is suited for spatial data in LBS and the improved compression arithmetic is prior to the former.

A Differential Privacy Protection Protocol Based on Location Entropy

A Location-Based Service(LBS)refers to geolocation-based services that bring both convenience and vulnerability.With an increase in the scale and value of data,most existing location privacy protection protocols cannot balance privacy and utility.To solve the revealing problems in LBS,we propose a differential privacy protection protocol based on location entropy.First,we design an algorithm of the best-assisted user selection for constructing anonymity sets.Second,we employ smart contracts to evaluate the credibility of participants,which ensures the honesty of participants.Moreover,we provide a comprehensive experiment;the theoretical analysis and experiments show that the proposed protocol effectively resists background knowledge attacks.Generally,our protocol improves data availability.Particularly,it realizes user-controllable privacy protection,which improves privacy protection and strengthens security.

Location,Localization,and Localizability

Location-aware technology spawns numerous unforeseen pervasive applications in a wide range of living, pro- duction, commence, and public services. This article provides an overview of the location, localization, and localizability issues of wireless ad-hoc and sensor networks. Making data geographically meaningful, location information is essential for many applications, and it deeply aids a number of network functions, such as network routing, topology control, coverage, boundary detection, clustering, etc. We investigate a large body of existing localization approaches with focuses on error control and network localizability, the two rising aspects that attract significant research interests in recent years. Error control aims to alleviate the negative impact of noisy ranging measurement and the error accumulation effect during coope- rative localization process. Network localizability provides theoretical analysis on the performance of localization approaches, providing guidance on network configuration and adjustment. We emphasize the basic principles of localization to under- stand the state-of-the-art and to address directions of future research in the new and largely open areas of location-aware technologies.

An efficient method for privacy preserving location queries

Recently, the issue of privacy preserving loca- tion queries has attracted much research. However, there are few works focusing on the tradeoff between location privacy preservation and location query information collection. To tackle this kind of tradeoff, we propose the privacy persevering location query （PLQ）, an efficient privacy pre-serving location query processing framework. This frame- work can enable the location-based query without revealing user location information. The framework can also facilitate location-based service providers to collect some information about the location based query, which is useful in practice. PLQ consists of three key components, namely, the location anonymizer at the client side, the privacy query processor at the server side, and an additional trusted third party connect- ing the client and server. The location anonymizer blurs the user location into a cloaked area based on a map-hierarchy. The map-hierarchy contains accurate regions that are parti- tioned according to real landforms. The privacy query pro- cessor deals with the requested nearest-neighbor （NN） loca- tion based query. A new convex hull of polygon （CHP） algo- rithm is proposed for nearest-neighbor queries using a poly- gon cloaked area. The experimental results show that our al- gorithms can efficiently process location based queries.

A Random Anonymity Framework for Location Privacy

Location k-anonymity techniques typically use anony- mous spatial region to ensure privacy. But these solutions are vul- nerable to multiple queries attacks and inference attacks. Failing to account for the obstacle in geographic space is a severe problem since adversaries will surely regard these constraints. A novel framework is proposed to enhance location-dependent queries, based on the theoretical work of k-anonymity and Voronoi diagrams, allows a user to express service requirement and privacy require- ment by specifying a region and an appropriate value ofk. A trusted anonymity server form a restricted set （k, r, s）, which is composed of a number of discrete points to meet the requirements for location k-anonymity and location /-diversity. The location-based services （LBS） server implements an efficient algorithm for continu- ous-region-query processing. Simulation results demonstrated that the framework is superior to previous works in terms of privacy. Moreover, discreteness and randomness of the anonymous set are conducive to resisting location tracking attacks.

Research on k-anonymity privacy protection scheme based on bilinear pairings

Aimed at enhancing privacy protection of location-based services（ LBS） in mobile Internet environment,an improved privacy scheme of high service quality on the basis of bilinear pairings theory and k-anonymity is proposed. In circular region of Euclidian distance,mobile terminal evenly generates some false locations,from which half optimal false locations are screened out according to position entropy,location and mapping background information. The anonymity obtains the effective guarantee,so as to realize privacy protection. Through security analyses,the scheme is proved not only to be able to realize such security features as privacy,anonymity and nonforgeability,but also able to resist query tracing attack. And the result of simulation shows that this scheme not only has better evenness in selecting false locations,but also improves efficiency in generating and selecting false nodes.

A Crowd-Sourced Data Based Analytical Framework for Urban Planning

Aimed at the challenges faced by the current urban development and urban planning, along with the research opportunities brought by "big data," this paper proposes an analytical framework based on crowd-sourced data for urban planning by reviewing related literature and practice. The framework is mainly oriented towards three major requirements of analysis in urban planning: the physical spaces, the user communities, and the social relationships. This analytical framework can be regarded as a preliminary attempt for future data-intensive applications in urban planning and assessment.