Sketch-based Queries in Mobile GIS-Environments

Recent achievements in the field of mobile computing and wireless communication promise data retrieval anywhere and anytime. This development provided the basis to expand GIs technology to handheld devices, such as personal digital assistants (PDAs). Although traditional GIs technology is well suited for desktop workstations, it needs to be adapted in order to satisfy the requirements of users using handheld computing devices. This adaptation is necessary because the usability of traditional GISs depends on characteristics of desktop computers, such as their relatively large user interfaces (e.g., displays, keyboards, pointing devices), considerable computing resources (i.e., CPU, memory, storage, operating systems), and high bandwidth network connectivity. Small devices possess few of these characteristics, hence, requiring new and efficient methods for interaction with spatial databases. We propose a concept that supports sketch-based querying in mobile GIs environments. This concept combines newest techniques for spatial querying and mobile technologies. Such a combination is beneficial for users because it allows them to formulate queries by drawing the desired configuration with a pen on the touch-sensitive PDA screen, and consequently avoids typing complex statements in some SQL-like query language. Client-server architectures in mobile environments are characterized by low and fluctuating bandwidth, and by frequent disconnections. We discuss client-server strategies in mobile environments, suggest an adaptive client-server architecture for geomobile querying, and analyze the performance. It is shown that adaptation to the mobile environment is necessary in order to ensure efficiency of geo-mobile queries

FogGIS: Fog Computing for Geospatial Big Data Analytics

Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining analytics from geospatial data. We built a prototype using Intel Edison, an embedded microprocessor. We validated the FogGIS by doing preliminary analysis. including compression, and overlay analysis. Results showed that Fog computing hold a great promise for analysis of geospatial data. We used several open source compression techniques for reducing the transmission to the cloud.Comment: 6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (09-11 December, 2016) Indian Institute of Technology (Banaras Hindu University) Varanasi, Indi

Wearable learning tools

In life people must learn whenever and wherever they experience something new. Until recently computing technology could not support such a notion, the constraints of size, power and cost kept computers under the classroom table, in the office or in the home. Recent advances in miniaturization have led to a growing field of research in ‘wearable’ computing. This paper looks at how such technologies can enhance computer‐mediated communications, with a focus upon collaborative working for learning. An experimental system, MetaPark, is discussed, which explores communications, data retrieval and recording, and navigation techniques within and across real and virtual environments. In order to realize the MetaPark concept, an underlying network architecture is described that supports the required communication model between static and mobile users. This infrastructure, the MUON framework, is offered as a solution to provide a seamless service that tracks user location, interfaces to contextual awareness agents, and provides transparent network service switching

Towards a Scalable Dynamic Spatial Database System

With the rise of GPS-enabled smartphones and other similar mobile devices, massive amounts of location data are available. However, no scalable solutions for soft real-time spatial queries on large sets of moving objects have yet emerged. In this paper we explore and measure the limits of actual algorithms and implementations regarding different application scenarios. And finally we propose a novel distributed architecture to solve the scalability issues.Comment: (2012

Location Privacy in Spatial Crowdsourcing

Spatial crowdsourcing (SC) is a new platform that engages individuals in collecting and analyzing environmental, social and other spatiotemporal information. With SC, requesters outsource their spatiotemporal tasks to a set of workers, who will perform the tasks by physically traveling to the tasks' locations. This chapter identifies privacy threats toward both workers and requesters during the two main phases of spatial crowdsourcing, tasking and reporting. Tasking is the process of identifying which tasks should be assigned to which workers. This process is handled by a spatial crowdsourcing server (SC-server). The latter phase is reporting, in which workers travel to the tasks' locations, complete the tasks and upload their reports to the SC-server. The challenge is to enable effective and efficient tasking as well as reporting in SC without disclosing the actual locations of workers (at least until they agree to perform a task) and the tasks themselves (at least to workers who are not assigned to those tasks). This chapter aims to provide an overview of the state-of-the-art in protecting users' location privacy in spatial crowdsourcing. We provide a comparative study of a diverse set of solutions in terms of task publishing modes (push vs. pull), problem focuses (tasking and reporting), threats (server, requester and worker), and underlying technical approaches (from pseudonymity, cloaking, and perturbation to exchange-based and encryption-based techniques). The strengths and drawbacks of the techniques are highlighted, leading to a discussion of open problems and future work

Mobile Agents for Mobile Tourists: A User Evaluation of Gulliver's Genie

How mobile computing applications and services may be best designed, implemented and deployed remains the subject of much research. One alternative approach to developing software for mobile users that is receiving increasing attention from the research community is that of one based on intelligent agents. Recent advances in mobile computing technology have made such an approach feasible. We present an overview of the design and implementation of an archetypical mobile computing application, namely that of an electronic tourist guide. This guide is unique in that it comprises a suite of intelligent agents that conform to the strong intentional stance. However, the focus of this paper is primarily concerned with the results of detailed user evaluations conducted on this system. Within the literature, comprehensive evaluations of mobile context-sensitive systems are sparse and therefore, this paper seeks, in part, to address this deficiency

e-Counterfeit: a mobile-server platform for document counterfeit detection

This paper presents a novel application to detect counterfeit identity documents forged by a scan-printing operation. Texture analysis approaches are proposed to extract validation features from security background that is usually printed in documents as IDs or banknotes. The main contribution of this work is the end-to-end mobile-server architecture, which provides a service for non-expert users and therefore can be used in several scenarios. The system also provides a crowdsourcing mode so labeled images can be gathered, generating databases for incremental training of the algorithms.Comment: 6 pages, 5 figure