1,720,963 research outputs found
Indoor Mobility(Full Phases of Indoor Navigation Services)
Get PDFOver the last decade, navigation systems have been widely used as resources for path planning and way finding. Normally, they are tracked and guided by specific positioning technologies. Outdoor navigation services have been developed over the years by GPS (Global Position System), which is a quite common precise and infrastructure-free solution in large environments. However, the available navigation services in indoor spaces do not complete, and no standard has developed to fulfill all indoor navigation requirements. In this thesis I discuss about indoor navigation requirements, like this question “How can a human being find his/her destination in a building he / she does not know?”, etc.
Here I propose an indoor navigation system that contains the functional modules and related techniques. The functional modules are Indoor Mapping, Indoor Positioning, Path Planning, En-route Assistant and Analysis respectively, which support the full phases of indoor navigation services.
Indoor Mapping: A 2D and 3D indoor mapping approach is proposed, which 1) can build an effective 2D SVG map that updates selectively, 2) converts it into a 3D virtual scene automatically at back-end, 3) includes an information management system at back-end, 4) renders and interacts efficiently and effectively on a smart phone, and 5) offers a vivid virtual indoor visualization for virtual navigation services at front-end.
Indoor Positioning: I propose two magnetic field positioning techniques: Robot Simulation-oriented Mobile Localization (RSML) and Computer Vision-oriented Fingerprint Localization (CVFL). 1) RSML focuses on a probabilistic framework that measures the relative and absolute position to simulate a robot movement. I propose an integrated magnetic field positioning approach based on eXtended Particle Filtering (XPF) algorithm, which fuses magnetic fingerprints, Wi-Fi fingerprints, and Pedestrian Dead Reckoning; 2) CVFL focuses on Magnetic Fingerprint Image-rization (MFI). It converts fingerprints to images and classifies them by CNN training.
Indoor Path Planning: Wayfinding is necessary to reach the destination, which includes route planning and path navigation. An optimized ant colony algorithm is developed to avoid the obstacles (walls).
En-route Assistant: En-route Assistant module provides the services in various devices, handed system, wearable system, etc. can be used for an enhanced navigation. In real-time navigation, it provides instructions based on a convenient trip for citizens and safe trip plan for VIPs (Visually Impaired People) and MIPs (Mobility Impaired People).
Indoor Data Analysis: Here, a POI recommended algorithm is proposed based on social relations. It uses social relations to enhance the accuracy of the recommended algorithm from a large number of user behavior data in social network. Indoor Mobility also provides a social relationship mining model to recommend POI by a classification mapping between social relationship and POIs.Over the last decade, navigation systems have been widely used as resources for path planning and way finding. Normally, they are tracked and guided by specific positioning technologies. Outdoor navigation services have been developed over the years by GPS (Global Position System), which is a quite common precise and infrastructure-free solution in large environments. However, the available navigation services in indoor spaces do not complete, and no standard has developed to fulfill all indoor navigation requirements. In this thesis I discuss about indoor navigation requirements, like this question “How can a human being find his/her destination in a building he / she does not know?”, etc.
Here I propose an indoor navigation system that contains the functional modules and related techniques. The functional modules are Indoor Mapping, Indoor Positioning, Path Planning, En-route Assistant and Analysis respectively, which support the full phases of indoor navigation services.
Indoor Mapping: A 2D and 3D indoor mapping approach is proposed, which 1) can build an effective 2D SVG map that updates selectively, 2) converts it into a 3D virtual scene automatically at back-end, 3) includes an information management system at back-end, 4) renders and interacts efficiently and effectively on a smart phone, and 5) offers a vivid virtual indoor visualization for virtual navigation services at front-end.
Indoor Positioning: I propose two magnetic field positioning techniques: Robot Simulation-oriented Mobile Localization (RSML) and Computer Vision-oriented Fingerprint Localization (CVFL). 1) RSML focuses on a probabilistic framework that measures the relative and absolute position to simulate a robot movement. I propose an integrated magnetic field positioning approach based on eXtended Particle Filtering (XPF) algorithm, which fuses magnetic fingerprints, Wi-Fi fingerprints, and Pedestrian Dead Reckoning; 2) CVFL focuses on Magnetic Fingerprint Image-rization (MFI). It converts fingerprints to images and classifies them by CNN training.
Indoor Path Planning: Wayfinding is necessary to reach the destination, which includes route planning and path navigation. An optimized ant colony algorithm is developed to avoid the obstacles (walls).
En-route Assistant: En-route Assistant module provides the services in various devices, handed system, wearable system, etc. can be used for an enhanced navigation. In real-time navigation, it provides instructions based on a convenient trip for citizens and safe trip plan for VIPs (Visually Impaired People) and MIPs (Mobility Impaired People).
Indoor Data Analysis: Here, a POI recommended algorithm is proposed based on social relations. It uses social relations to enhance the accuracy of the recommended algorithm from a large number of user behavior data in social network. Indoor Mobility also provides a social relationship mining model to recommend POI by a classification mapping between social relationship and POIs
CITY FEED: A pilot system of citizen-sourcing for city issue management
No full textCrowdsourcing implies user collaboration and engagement, which fosters a renewal of city governance processes. In this article, we address a subset of crowdsourcing, named citizen-sourcing, where citizens interact with authorities collaboratively and actively. Many systems have experimented citizen-sourcing in city governance processes; however, their maturity levels are mixed. In order to focus on the service maturity, we introduce a city service maturity framework that contains five levels of service support and two levels of information integration. As an example, we introduce CITY FEED, which implements citizen-sourcing in city issue management process. In order to support such process, CITY FEED supports all levels of the maturity framework (publishing, transacting, interacting, collaborating, and evaluating) and integrates related information relationally and heterogeneously. In order to integrate heterogeneous information, it implements a threefold feed deduplication mechanism based on the geographic, text semantic, and image similarities of feeds. Currently, CITY FEED is in a pilot stage
XYZ indoor navigation through augmented reality: A research in progress
Get PDFWe present an overall framework of services for indoor navigation, which includes Indoor Mapping, Indoor Positioning, Path Planning, and En-route Assistance. Within such framework we focus on an augmented reality (AR) solution for en-route assistance. AR assists the user walking in a multi-floor building by displaying a directional arrow under a camera view, thus freeing the user from knowing his/her position. Our AR solution relies on geomagnetic positioning and north-oriented space coordinates transformation. Therefore, it can work without infrastructure and without relying on GPS. The AR visual interface and the integration with magnetic positioning is the main novelty of our solution, which has been validated by experiments and shows a good performance
A Pilot Crowdsourced City Governance System: CITY FEED
No full textCrowdsourcing typically implies user collaboration and engagement, to foster participation in city governance process. In order to evaluate the level of crowdsourcing, we introduce a framework on the maturity of municipal services. Also we introduce CITY FEED, that implements crowdsourced city governance process and crowdsourced data integration. CITY FEED has been deployed as a pilot in Pavia, Italy
Delivering Real-Time Information Services on Public Transit: A Framework
No full textPublic transit is described by a wide range of data, which include sensor data, open data, and social network data. Data come in large real-time streams, and are heterogeneous. How to integrate such data in real time? We propose MOBility ANAlyzer (MOBANA), a distributed stream-based framework. MOBANA deals with the integration of heterogeneous information, processing efficiency, and redundancy reduction. As far as integration is concerned, MOBANA integrates data at different layers, and converts them into exchangeable data formats. Specifically, to integrate feed information, MOBANA uses an improved incremental text classifier, based on Kullback Leibler distance. As far as efficiency is concerned, MOBANA is implemented by distributed stream processing engine and distributed messaging system, which enable scalable, efficient, and reliable real-time processing. Specifically, within the transport domain, MOBANA identifies the real-time position of vehicles by an as-needed adjustment of planned position against the real-time position, thus dropping network load. As far as redundancy is concerned, MOBANA filters tweets through a three-fold similarity analysis, which encompasses geo-location, text, and image. In addition, MOBANA is a complete framework, which has been tested as a pilot with real data in the city of Pavia, Italy
Multi-floor indoor navigation with geomagnetic field positioning and ant colony optimization algorithm
Get PDFWe here illustrate a new indoor navigation system, which is independent from power sources, and it can work also in the dark. The system includes two key components, namely positioning and path planning. Positioning is based on geomagnetic elds, and it overcomes the several limits of indoor systems based on WIFI and Bluetooth, etc. Path planning is based on a new and optimized Ant Colony algorithm, called Ant Colony Optimization (ACO), which oers better performances than the classic A* algorithms. The paper illustrates the logic and the architecture of the system,and also presents experimental results
MOBANA: A distributed stream-based information system for public transit
Get PDFAbstract:
Public transit generates a wide range of diverse data, which include static data and high-velocity data streams from sensors. Integrating and processing this big real-time data is a challenge in developing analytical systems for public transit. We here propose MOBANA (MOBility ANAlyzer), a distributed stream-based system, which provides real-time information to a wide range of users for monitoring and analyzing the performance of public transit. To do so, MOBANA integrates the diverse data sources of public transit, and converts them into standard and exchangeable data formats. In order to manage such diverse data, we propose a layered architecture, where each layer handles a specific kind of data. MOBANA is designed to be efficient. e.g., it identifies the real time position of vehicles by adjusting planned position with real-time data as needed, thus dropping network load. MOBANA is implemented by Distributed Stream Processing Engine (DSPE) and Distributed Messaging System (DMS), which pursue scalable, efficient and reliable real-time processing and analytics. MOBANA was deployed as pilot in Pavia, and tested with real data
- …
