Vagueness is often present in spatial phenomena. Representing and analysing vague spatial phenomena requires vague objects and operators, whereas current GIS and spatial databases can only handle crisp objects. This paper provides mathematical definitions for vague object types and operators. The object types that we propose are a set of simple types, a set of general types, and vague partitions. The simple types represent identifiable objects of a simple structure, i.e. not divisible into components. They are vague points, vague lines, and vague regions. The general types represent classes of simple type objects. They are vague multipoint, vague multiline, and vague multiregion. General types assure closure under set operators. Simple and general types are defined as fuzzy sets in ℝ² satisfying specific properties that are expressed in terms of topological notions. These properties assure that set membership values change mostly gradually, allowing stepwise jumps. The type vague partition is a collection of vague multiregions that might intersect each other only at their transition boundaries. It allows for a soft classification of space. All types allow for both a finite and an infinite number of transition levels. They include crisp objects as special cases. We consider a standard set of operators on crisp objects and define them for vague objects. We provide definitions for operators returning spatial types. They are regularized fuzzy set operators: union, intersection, and difference; two operators from topology: boundary and frontier; and two operators on vague partitions: overlay and fusion. Other spatial operators, topological predicates and metric operators, are introduced giving their intuition and example definitions. All these operators include crisp operators as special cases. Types and operators provided in this paper form a model for a spatial data system that can handle vague information. The paper is illustrated with an application of vague objects in coastal erosion.

A new category of intelligent sensor network applications emerges where motion is a fundamental characteristic of the system under consideration. In such applications, sensors are attached to vehicles, or people that move around large geographic areas. For instance, in mission critical applications of wireless sensor networks (WSNs), sinks can be associated to first responders. In such scenarios, reliable data dissemination of events is very important, as well as the efficiency in handling the mobility of both sinks and event sources. For this kind of applications, reliability means real-time data delivery with a high data delivery ratio. In this article, we propose a virtual infrastructure and a data dissemination protocol exploiting this infrastructure, which considers dynamic conditions of multiple sinks and sources. The architecture consists of 'highways' in a honeycomb tessellation, which are the three main diagonals of the honeycomb where the data flow is directed and event data is cached. The highways act as rendezvous regions of the events and queries. Our protocol, namely hexagonal cell-based data dissemination (HexDD), is fault-tolerant, meaning it can bypass routing holes created by imperfect conditions of wireless communication in the network. We analytically evaluate the communication cost and hot region traffic cost of HexDD and compare it with other approaches. Additionally, with extensive simulations, we evaluate the performance of HexDD in terms of data delivery ratio, latency, and energy consumption. We also analyze the hot spot zones of HexDD and other virtual infrastructure based protocols. To overcome the hot region problem in HexDD, we propose to resize the hot regions and evaluate the performance of this method. Simulation results show that our study significantly reduces overall energy consumption while maintaining comparably high data delivery ratio and low latency.

The Wireless Sensor Networks (WSNs) design related questions give rise to new complex and difficult theoretical problems and challenges in operations research and optimization areas. As WSNs become increasingly pervasive, a good understanding of these problems in terms of theoretical complexity is of great help in designing appropriate algorithms. In this paper, we examine some of the most fundamental optimization problems related to coverage, topology control, scheduling, routing and mobility in WSNs. Then we focus on their complexity and analyze the differences that exist with the counter part conventional theoretical problems or those already studied in traditional networks. We present as well some of the main methods proposed in the literature and report some open issues regarding these problems.

Many software systems have been created to help the emergency responders in their activities all over the world. These systems are usually dedicated to a specific emergency situation or emergency response sector. Exchange of information between the different systems is difficult or not possible. While much progress is observed in accessing and sharing existing data, management of field (or dynamic) data is often overlooked. A lot of information coming from the field operations is either not archived or is stored in an unstructured way. This makes the analysis of data a difficult and slow process. This paper presents a data model for the management of dynamic data. The data model captures the situational information—incident and its effect—and the operational information—processes activated, people and departments involved. New data types are created for temporal and spatiotemporal information: dynamic counts, e.g. the number of injured or missing people, moving point and moving region, e.g. the position of vehicles or people and the gas plume. The model is derived from the emergency response procedure in the Netherlands. The information needs resulting from this procedure are, in a large part, valid for emergency situations everywhere, therefore the model can be easily adapted for other countries.