Mobile Mapping Applications Research Articles

Drupal 기반 맵 응용 생성기 (MapAppGen) : 맛집탐방 응용 생성 사례

웹과 스마트폰의 사용이 일상화 되면서 맵 응용에 대한 수요가 웹 및 모바일 환경에서 급증하고 있다. 웹 기반 맵 응용들은 대부분 ArcGIS와 같은 값비싼 개발 환경이나 MapServer와 같은 공개 개발 환경에서 작성되고 있고 모바일 맵 응용들은 Google Maps나 Yahoo Maps와 같은 API 수준에서 작성되고 있다. 그러나 이러한 개발 환경들은 자동화 지원 정도가 미약하여 맵 응용 개발의 많은 부분이 아직 수작업에 의존하고 있다. 우리가 설계하고 구현한 MapAppGen은 신속한 웹 기반 맵 응용의 작성을 지원하기 위해 Drupal CMS(Contents Management System)에 적용 가능한 맵 관련 모듈들을 생성해 줌으로써 맵 응용에 대한 생산성을 향상시켜 준다. MapAppGen으로 생성한 응용은 Drupal이 지원하는 기존의 GMap이나 NodeMap이 생성한 응용에 비해 관심의 대상인 지형/지물과 함께 이 지형/지물과 연관된 모든 정보를 검색해 표시한다. MapAppGen은 Google Maps API를 사용하며 Drupal은 컨텐츠의 생성, 구성, 관리를 지원하는 모듈 기반 시스템이다. 향후, MapAppGen을 확장하여 모바일 맵 응용의 자동 생성도 지원할 예정이다. The demand for map applications in both Web and mobile environments has been rapidly increased with the population of Web and smart phone usage. Web-based map applications are mostly developed on such environments as ArcGIS and MapServer and mobile map applications are developed on such API levels as Google Maps and Yahoo Maps. But many parts of map applications are still constructed by coding because these environments don't support high level of automation. Our MapAppGen that we have designed and implemented enhances the Web-based map application productivity by generating the map related modules that can be applied to the Drupal that is one of popular content management systems(CMS's). Comparing the applications that are constructed by the Drupal-supported GMap or NodeMap, the applications that are constructed by MapAppGen provide information on not only the interested geographical feature but also its related geographical features. MapAppGen uses Google Maps API and Drupal is a module-based system that supports the creation, composition and management of contents. We are now working on automatic generation of mobile map applications with MapAppGen.

Platforms and viability of mobile GIS in real‐time hydrological models

PurposeThe purpose of this paper is to examine the practicality of an application called the mobile geographic information system (GIS). The authors' purpose was to focus specifically on the mobile GIS application in a prototype, mobile‐based model that is utilized for detecting flood warnings and issuing forecasts. At the end of this research project, a usability study was carried out in a test‐lab environment.Design/methodology/approachIn this paper, research is presented regarding the architecture of a structure that has been built on practicality. Readers will learn about a system that is applicable within a vast array of turning‐point situations where rainfall data are communicated to the system in real time.FindingsIt has been revealed that traditional GIS and remote sensing software packages are not as cost‐effective as GIS services that are mobile. Mobile GIS systems have the capability to combine GIS, global positioning system, and remote sensing abilities for retrieving geospatial data sets at costs that are not as pricey as the traditional systems. As time moves on, the need for reliable real‐time data sets is increasing. Additionally, flood management examination provides a valid debate for the combining of mobile GISs within the realm of hydrology. Empirical evidence insinuates and illustrates reliability of GIS and the enhancement in the utilization and creation of devices that are offer mobile capabilities. The usability study revealed that the slope, aspect, watershed, and flow direction functions were not easy to comprehend. It was also discovered during the usability study that the word arrangement, radio button arrangement, and dropdown list caused confusion amongst users. The issue that was deemed as most severe, that was discovered during the usability study, was the blurred comprehension that users experienced regarding the digital elevation model.Research limitations/implicationsBefore the wisest solution can be pinpointed, all of the associated constraints of mobile GIS mapping application need to be identified; however, enough constraints have already been identified to bring to a close that a basic mobile GIS mapping application could created and triumphantly used. There are many platforms to choose from in regards to providing a solution to a feasible incorporation of the mobile GISs into the playing field. It should be decided which browser‐based strategy would serve as the highest of benefit based on characteristics that are important to consumers, such as affordability, ease‐of‐use, user‐friendly coding, and acceptability by users.Originality/valueThis research is highly indicative that mobile GIS would be of great benefit for future studies within the realm of disaster monitoring management. The research presented in this paper can be deemed as original due to the fact that it is a study about the utilization of mobile technologically‐advanced gadgets that provide data analysis for flooding in real time. Moreover, these highly technologically‐advanced devices are cost‐effective compared to those in the past.

Reaching a Compromise between Contextual Constraints and Cartographic Rules: Application to Sustainable Maps

Emerging mobile mapping applications create new constraints for cartographers. These constraints should be considered in addition to the traditional cartographic rules used to design maps. Legend colors could be optimized regarding those constraints. A challenge for optimization concerns the preservation of map semiotic quality. In our research, we propose a quantification of the cartographic quality of a map, regarding a given reference map that considers semantic rules of association, differentiation and order conveyed by map colors. Some mobile devices require less energy to display dark colors than lighter ones. In this paper we consider the energy consumption as the contextual constraint to optimize. Map samples are designed, while taking into account some conventional uses of colors for relevant themes: hydrography, vegetation and the background layer. We discuss how to find the best compromise between a contextual constraint (the energy required to display a map on a screen of a mobile device in our example) and the cartographic consistency on colors regarding the initial semantic relationships in the legend. We answer the question of how much can cartographic rules be altered while still preserving semiotic quality.

An ANN embedded RTS smoother for an INS/GPS integrated Positioning and Orientation System

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. The direct geo-referencing is the determination of time variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning by GPS and inertial navigation using an IMU. They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. KF is considered the optimal estimation tool for teal-time INS/GPS integrated kinematic positioning and orientation determination. In post-mission processing, on the other hand, data from the whole mission can be used to estimate the trajectory. When filtering is used in the first step, an optimal smoothing algorithm can be applied to achieve higher accuracy for mobile mapping applications. An intelligent and hybrid scheme consisting of an ANN and KF is proposed to overcome the limitations of KF and to improve the performance of an INS/GPS integrated system from a previous study. However, the accuracy requirements of general mobile mapping applications cannot be achieved easily even by using an ANN–KF scheme. Therefore, this study proposes an ANN embedded RTS backward smoother to enhance the overall accuracy of POS parameters for a tactical grade INS/GPS integrated system in a post-mission mode. Combing the tactical grade INS/GPS integrated system and intelligent POS scheme proposed in this study, a cheap but reasonably accurate POS can be anticipated.

Intelligent Sensor Positioning and Orientation Through Constructive Neural Network-Embedded INS/GPS Integration Algorithms

Mobile mapping systems have been widely applied for acquiring spatial information in applications such as spatial information systems and 3D city models. Nowadays the most common technologies used for positioning and orientation of a mobile mapping system include a Global Positioning System (GPS) as the major positioning sensor and an Inertial Navigation System (INS) as the major orientation sensor. In the classical approach, the limitations of the Kalman Filter (KF) method and the overall price of multi-sensor systems have limited the popularization of most land-based mobile mapping applications. Although intelligent sensor positioning and orientation schemes consisting of Multi-layer Feed-forward Neural Networks (MFNNs), one of the most famous Artificial Neural Networks (ANNs), and KF/smoothers, have been proposed in order to enhance the performance of low cost Micro Electro Mechanical System (MEMS) INS/GPS integrated systems, the automation of the MFNN applied has not proven as easy as initially expected. Therefore, this study not only addresses the problems of insufficient automation in the conventional methodology that has been applied in MFNN-KF/smoother algorithms for INS/GPS integrated systems proposed in previous studies, but also exploits and analyzes the idea of developing alternative intelligent sensor positioning and orientation schemes that integrate various sensors in more automatic ways. The proposed schemes are implemented using one of the most famous constructive neural networks—the Cascade Correlation Neural Network (CCNNs)—to overcome the limitations of conventional techniques based on KF/smoother algorithms as well as previously developed MFNN-smoother schemes. The CCNNs applied also have the advantage of a more flexible topology compared to MFNNs. Based on the experimental data utilized the preliminary results presented in this article illustrate the effectiveness of the proposed schemes compared to smoother algorithms as well as the MFNN-smoother schemes.

An Artificial Neural Network Embedded Position and Orientation Determination Algorithm for Low Cost MEMS INS/GPS Integrated Sensors

Digital mobile mapping, which integrates digital imaging with direct geo-referencing, has developed rapidly over the past fifteen years. Direct geo-referencing is the determination of the time-variable position and orientation parameters for a mobile digital imager. The most common technologies used for this purpose today are satellite positioning using Global Positioning System (GPS) and Inertial Navigation System (INS) using an Inertial Measurement Unit (IMU). They are usually integrated in such a way that the GPS receiver is the main position sensor, while the IMU is the main orientation sensor. The Kalman Filter (KF) is considered as the optimal estimation tool for real-time INS/GPS integrated kinematic position and orientation determination. An intelligent hybrid scheme consisting of an Artificial Neural Network (ANN) and KF has been proposed to overcome the limitations of KF and to improve the performance of the INS/GPS integrated system in previous studies. However, the accuracy requirements of general mobile mapping applications can’t be achieved easily, even by the use of the ANN-KF scheme. Therefore, this study proposes an intelligent position and orientation determination scheme that embeds ANN with conventional Rauch-Tung-Striebel (RTS) smoother to improve the overall accuracy of a MEMS INS/GPS integrated system in post-mission mode. By combining the Micro Electro Mechanical Systems (MEMS) INS/GPS integrated system and the intelligent ANN-RTS smoother scheme proposed in this study, a cheaper but still reasonably accurate position and orientation determination scheme can be anticipated.

An ANN–RTS smoother scheme for accurate INS/GPS integrated attitude determination

Digital mobile mapping, the method that integrates digital imaging with direct geo-referencing, has developed rapidly over the past 15 years. The Kalman filter (KF) is considered an optimal estimation tool for real-time INS/GPS integrated kinematic positioning and orientation determination. However, the accuracy requirements of general mobile mapping applications cannot be easily achieved even when using the KF scheme. Therefore, this study proposes an intelligent scheme combining ANN and RTS backward smoother to overcome the limitations of KF and to enhance the overall accuracy of attitude determination for tactical grade and MEMS INS/GPS integrated systems.