Information Management in Mobile Environments Using a Location-Aware Intelligent Agent System

2011 ◽  
pp. 1-17
Author(s):  
Amrish Vyas ◽  
Victoria Yoon
Keyword(s):  
Intelligent Agent ◽  
Location Based Services ◽  
Agent System ◽  
Content Dissemination ◽  
New Era ◽  
Location Aware ◽  
Spatio Temporal ◽  
Types Of Information ◽  
Push And Pull ◽  
User Location

Recent rise in the level of comfort and demand to access various types of information using mobile devices can be attributed to the advancements in wireless as well as Internet technologies. This demand leads us to the new era of mobile computing. Location-based services (LBS) are engendering new passion in mobile services utilizing users’ location information. Such spatio-temporal information processing entails the need for a dynamic middleware that accurately identifies changing user location and attaches dependent content in real-time without putting extra burden on users. Our work focuses on creating a distributed infrastructure suitable to support such scalable content dissemination. As a result this chapter offers a conceptual framework, location-aware intelligent agent system (LIA) in integration with publish/subscribe middleware to comprehensively address dynamic content dissemination and related issues. We discuss the operational form of our framework in terms of PUSH and PULL strategies.

Information Management in Mobile Environments Using a Location-Aware Intelligent Agent System

2009 ◽  
pp. 573-588
Author(s):  
Amrish Vyas ◽  
Victoria Yoon
Keyword(s):  
Intelligent Agent ◽  
Location Based Services ◽  
Agent System ◽  
Content Dissemination ◽  
New Era ◽  
Location Aware ◽  
Spatio Temporal ◽  
Types Of Information ◽  
Push And Pull ◽  
User Location

Recent rise in the level of comfort and demand to access various types of information using mobile devices can be attributed to the advancements in wireless as well as Internet technologies. This demand leads us to the new era of mobile computing. Location-based services (LBS) are engendering new passion in mobile services utilizing users’ location information. Such spatio- temporal information processing entails the need for a dynamic middleware that accurately identifies changing user location and attaches dependent content in real-time without putting extra burden on users. Our work focuses on creating a distributed infrastructure suitable to support such scalable content dissemination. As a result this chapter offers a conceptual framework, location-aware intelligent agent system (LIA) in integration with publish/subscribe middleware to comprehensively address dynamic content dissemination and related issues. We discuss the operational form of our framework in terms of PUSH and PULL strategies.

scholarly journals Extracting Stops from Spatio-Temporal Trajectories within Dynamic Contextual Features

2021 ◽  
Vol 13 (2) ◽  
pp. 690
Author(s):  
Tao Wu ◽  
Huiqing Shen ◽  
Jianxin Qin ◽  
Longgang Xiang
Keyword(s):  
Moving Objects ◽  
Major Effect ◽  
Location Based Services ◽  
Trajectory Data ◽  
The Road ◽  
Contextual Features ◽  
Novel Approach ◽  
Gps Trajectories ◽  
Time Distance ◽  
Spatio Temporal

Identifying stops from GPS trajectories is one of the main concerns in the study of moving objects and has a major effect on a wide variety of location-based services and applications. Although the spatial and non-spatial characteristics of trajectories have been widely investigated for the identification of stops, few studies have concentrated on the impacts of the contextual features, which are also connected to the road network and nearby Points of Interest (POIs). In order to obtain more precise stop information from moving objects, this paper proposes and implements a novel approach that represents a spatio-temproal dynamics relationship between stopping behaviors and geospatial elements to detect stops. The relationship between the candidate stops based on the standard time–distance threshold approach and the surrounding environmental elements are integrated in a complex way (the mobility context cube) to extract stop features and precisely derive stops using the classifier classification. The methodology presented is designed to reduce the error rate of detection of stops in the work of trajectory data mining. It turns out that 26 features can contribute to recognizing stop behaviors from trajectory data. Additionally, experiments on a real-world trajectory dataset further demonstrate the effectiveness of the proposed approach in improving the accuracy of identifying stops from trajectories.

scholarly journals A Survey on Spatio-temporal Data Analytics Systems

2022 ◽  
Author(s):  
Md Mahbub Alam ◽  
Luis Torgo ◽  
Albert Bifet
Keyword(s):  
Programming Languages ◽  
Spatial Data ◽  
Data Analytics ◽  
Spatial Databases ◽  
Location Based Services ◽  
Temporal Data ◽  
Wide Range ◽  
Data Volume ◽  
Spatio Temporal ◽  
Gis Software

Due to the surge of spatio-temporal data volume, the popularity of location-based services and applications, and the importance of extracted knowledge from spatio-temporal data to solve a wide range of real-world problems, a plethora of research and development work has been done in the area of spatial and spatio-temporal data analytics in the past decade. The main goal of existing works was to develop algorithms and technologies to capture, store, manage, analyze, and visualize spatial or spatio-temporal data. The researchers have contributed either by adding spatio-temporal support with existing systems, by developing a new system from scratch, or by implementing algorithms for processing spatio-temporal data. The existing ecosystem of spatial and spatio-temporal data analytics systems can be categorized into three groups, (1) spatial databases (SQL and NoSQL), (2) big spatial data processing infrastructures, and (3) programming languages and GIS software. Since existing surveys mostly investigated infrastructures for processing big spatial data, this survey has explored the whole ecosystem of spatial and spatio-temporal analytics. This survey also portrays the importance and future of spatial and spatio-temporal data analytics.

scholarly journals Mapping Urbanization as an Anthropedogenetic Process: A Section through the Times of Urban Soils

2020 ◽  
Vol 5 (2) ◽  
pp. 262-279 ◽  
Author(s):  
Antoine Vialle ◽  
Mario Giampieri
Keyword(s):  
Environmental History ◽  
Urban Areas ◽  
Urban Soils ◽  
Dynamic Vision ◽  
Strategic Role ◽  
Spatio Temporal ◽  
Map Series ◽  
The Times ◽  
Types Of Information ◽  
Ecological Transition

Current trends of spatial planning policies give a strategic role to soils, the multifunctionality of which must be considered as a crucial driver facing cities’ forthcoming social-ecological transition. However, soils within urban areas are insufficiently studied as a long-term record of environmental history and heavy anthropization. This article investigates the extreme qualitative variability of urban soils by presenting a conceptual model and cartographic workflow highlighting soil evolution processes as a value which co-variates with urbanization. Based on a case study in West Lausanne (Switzerland), the layers and map series of an atlas underscore the applicability of different types of information and spatial analysis for documenting the influence of anthrosediments and land cover changes. Combined with empirical profile descriptions, such a consolidated concept map defines a template, in the form of a complex spatio-temporal figure, on which to apply the state factor approach. Instead of using a simple spatial transect or gradient, the increasing anthropic dominance over original landscape conditions is explained using a section through time. An urban anthroposequence consequently retraces contrasting soil development pathways as a coherent bundle of historical trajectories. Such a narrative integrates various facets of land use, including one-off construction techniques and recurring maintenance practices, planning tools, and morphologies, into a specific ‘project for the ground’ which brought forth the mixed mesh of the Swiss Plateau ‘cityterritory.’ Ultimately, the dynamic vision conveyed by these intertwined soil–urbanization coevolution trajectories outlines opportunities for the regeneration of the resource deposit made up of both West Lausanne’s urban fabric and its soils as a palimpsest.

Sign in / Sign up

Export Citation Format

Share Document