Mir Abolfazl Mostafavi

Delete and insert operations in Voronoi/Delaunay methods and applications

This paper presents simple point insertion and deletion operations in Voronoi diagrams and Delaunay triangulations which may be useful for a wide variety of applications, either where interactivity is important, or where local modification of the topology is preferable to global rebuilding. While incremental point insertion has been known for many years, point deletion is relatively unknown. The robustness and efficiency of a new algorithm are described. A variety of potential applications are summarized, and the included computer program may be used as the basis for many new projects.

Probabilistic Sensing Model for Sensor Placement Optimization Based on Line-of-Sight Coverage

This paper proposes a probabilistic sensor model for the optimization of sensor placement. Traditional schemes rely on simple sensor behaviour and environmental factors. The consequences of these oversimplifications are unrealistic simulation of sensor performance and, thus, suboptimal sensor placement. In this paper, we develop a novel probabilistic sensing model for sensors with line-of-sight-based coverage (e.g., cameras) to tackle the sensor placement problem for these sensors. The probabilistic sensing model consists of membership functions for sensing range and sensing angle, which takes into consideration sensing capacity probability as well as critical environmental factors such as terrain topography. We then implement several optimization schemes for sensor placement optimization, including simulated annealing, limited-memory Broyden-Fletcher-Goldfarb-Shanno method, and covariance matrix adaptation evolution strategy.

Voronoi-Based Approaches for Geosensor Networks Coverage Determination and Optimisation: A Survey

Recent advances in sensors technology have led to design and development of variety of geosensor networks and their applications in many disciplines. Such networks consist of a set of sensors laying on different locations and sensing various real world phenomena for environmental monitoring, object surveillance, tracking and controlling applications. A fundamental issue in a geosensor network optimization is estimation of its spatial coverage. The existence of various obstacles in the sensing environment and its complexity result in several holes in the environment. These holes should be detected and minimized in the optimization process. Different approaches have been proposed in the literatures to resolve these problems. A considerable number of current approaches use Voronoi diagram and Delaunay triangulation to identify the holes in the network and deploy an optimal arrangement for the sensors. These structures are more compatible with the spatial distribution of sensors in the environment. This paper presents a survey of the existing solutions for geosensor network optimization that use Voronoi diagram and Delaunay triangulation in their approach.

Towards the global GIS

Abstract This paper outlines the concept of a “global GIS,” and defines various aspects of its development, as well as various options and decisions that must be made. The emphasis is on the advantages and disadvantages of maintaining a global topological structure, and whether topology should be generated “on the fly” in response to a specific query. We first define what we mean by “space” in this context, followed by a description of topological structures and how we may use them in the context of graph traversal problems. We then describe some appropriate data structures. After mentioning some of the real-world problems associated with polygon construction problems, we touch on how graphs may represent change over time. A global topological structure is then proposed which resolves some of the problems mentioned. This is based on incremental graph updating methods. Some unresolved problems associated with using global topological structures are then discussed, especially those associated with queries, such as polygon overlay, that generate a new local topological structure. We conclude with some preliminary rules, and suggest further work.

A GIS based wireless sensor network coverage estimation and optimization: a voronoi approach

Recent advances in sensor technology have resulted in the design and development of more efficient and low cast sensor networks for environmental monitoring, object surveillance, tracking and controlling of moving objects, etc. The deployment of a sensor network in a real environment presents several challenging issues that are often oversimplified in the existing solutions. Different approaches have been proposed in the literatures to solve this problem. Many of these approaches use Voronoi diagram and Delaunay triangulation to identify sensing holes in the network and create an optimal arrangement of the sensors to eliminate the holes. However, most of these methods do not consider the reality of the environment in which the sensor network is deployed. This paper presents a survey of the existing solutions for geosensor network optimization that use Voronoi diagram and Delaunay triangulation and identifies their limitations in a real world application. Next, it proposes a more realistic approach by integrating spatial information in the optimization process based on Voronoi diagram. Finally the results of two cases studies based on the proposed approach in natural area and urban environment are presented and discussed.

A global kinetic spatial data structure for a marine simulation

This paper proposes a new Free-Lagrange method based on the kinetic Voronoi diagram for fluid simulation. The objective here is to combine the advantages of an adoptive mesh structure with the advantages of kinetic mesh maintenance, and demonstrate their value for dynamic simulation. Despite the theoretical advantages of the Free-Lagrange method, its use has been handicapped with the reconstruction of topology after each time step that considerably reduces the efficiency of the method. In addition, the use of fixed time steps causes problems such as overshoots and undetected collisions. In order to demonstrate the ability of the proposed model to solve these problems, the method is applied to a dam-breaking problem and global tides. With the results obtained from these numerical experiments, the validity of the global kinetic data structure is approved. In particular, the method is found to be more efficient than existing methods. In addition, qualitative comparison of physical results with analytical solutions demonstrates the similarity of the results and confirms the physical validity of the proposed method. Further investigations with real-world data and the complete equation of motion are suggested to compare it with other numerical methods.

A dynamic and context-aware semantic mediation service for discovering and fusion of heterogeneous sensor data

Sensors play an increasingly critical role in capturing and distributing observa- tions of phenomena in our environment. The vision of the semantic sensor web is to enable the interoperability of various applications that use sensor data provided by semantically heterogeneous sensor services. However, several challenges still need to be addressed to achieve this vision. More particularly, mechanisms that can support context-aware seman- tic mapping and that can adapt to the dynamic metadata of sensors are required. Semantic mapping for the sensor web is required to support sensor data fusion, sensor data discov- ery and retrieval, and automatic semantic annotation, to name only a few tasks. This pa- per presents a context-awareontology-based semantic mediation service for heterogeneous sensor services. The semantic mediation service is context-aware and dynamic because it takes into account the real-time variability of thematic, spatial, and temporal elements that describe sensor data in different contexts. The semantic mediation service integrates rule- based reasoning to support the resolution of semantic heterogeneities. An application sce- nario is presented showing how the semantic mediation service can improve sensor data interpretation, reuse, and sharing in static and dynamic settings.

Dynamic Evacuation Routing Plan after an Earthquake

AbstractThis study proposes an earthquake evacuation routing plan from local shelters to regional ones for a long-term safe settlement using public vehicles. In a post-earthquake situation, the unpredicted changes in travel demand patterns and accessibility conditions of the transportation network affect the travel time. The contribution of this study is to propose a dynamic evacuation routing approach that can update the routing plan by incorporating time-dependent travel times. The problem is modeled as a vehicle routing problem and a two-stage solution procedure based on the simulated annealing algorithm is developed. The model is applied in part of Tehran’s transportation network. The results confirm that the dynamic evacuation routing approach is able to increase the number of evacuated shelters and decrease both the evacuation time and total travel time of the vehicles. The findings in this study indicate that the application of the proposed model can provide beneficial information for disaster mana...

Mapping between dynamic ontologies in support of geospatial data integration for disaster management

The effective management of disasters requires providing relevant and right information to the concerned decision makers. By its nature, disaster management involves multiple actors and organizations, potentially implying a significant volume of geospatial data coming from heterogeneous and autonomous geospatial data sources. Integration of these data sources is difficult not only because of the semantic heterogeneity of data but also because of the dynamic nature of the reality that is studied. The dynamic aspect of the reality has a direct impact in the conceptualisation of such a reality by adding different event categories to the domain ontology, thus making more complicated to apply existing methods for the mapping and integration of ontologies. In this article, we highlight some problems of heterogeneity that complicate the integration of ontologies composed of objects and events concepts; we also propose a similarity model designed to support mapping of these ontologies.

Toward 3D spatial dynamic field simulation within GIS using kinetic Voronoi diagram and Delaunay tetrahedralization

Geographic information systems (GISs) are widely used for representation, management, and analysis of spatial data in many disciplines. In particular, geoscientists increasingly use these tools for data integration and management purposes in many environmental applications, ranging from water resources management to the study of global warming. Beyond these capabilities, geoscientists need to model and simulate three-dimensional (3D) dynamic fields and readily integrate those results with other relevant spatial information in order to have a better understanding of the environmental problems. However, GISs are very limited for the modeling and simulation of spatial fields, which are mostly 3D and dynamic. These limitations are mainly related to the existing GIS spatial data structures that are static and limited to 2D space. In order to overcome these limitations, we develop and implement a new kinetic 3D spatial data structure based on Delaunay tetrahedralization and a 3D Voronoi diagram to support a 3D dynamic field simulation within GISs. In this article, we describe in detail the different steps from discretization of a 3D continuous field to its numerical integration, based on an event-driven method. For validation of the proposed spatial data structure itself and its potential for the simulation of a dynamic field, two case studies are presented in the article. According to our observations, during the simulation process, the data structure is maintained and the 3D spatial information is managed adequately. Furthermore, the results obtained from both experiments are very satisfactory and are comparable with the results obtained from other existing methods for the simulation of the same dynamic field. To conclude, we discuss the current challenges related to the development of the 3D kinetic data structure itself and its adaptation to 3D dynamic field simulation and suggest some solutions for its improvement.