Wojciech Chmiel

IOEM - ontology engineering methodology for large systems

The paper presents IOEM, a methodology for ontology development elaborated for the INSIGMA project. Although prepared for a particular use, the methodology is quite general and can be used in a large variety of IT projects requiring ontology components. It is particularly suitable for large and geographically distributed software projects. The methodology is oriented towards applications of ontologies in various phases of a software lifecycle: development and run-time.

Risk assessment for a video surveillance system based on Fuzzy Cognitive Maps

For various IT systems security is considered a key quality factor. In particular, it might be crucial for video surveillance systems, as their goal is to provide continuous protection of critical infrastructure and other facilities. Risk assessment is an important activity in security management; it aims at identifying assets, threats and vulnerabilities, analysis of implemented countermeasures and their effectiveness in mitigating risks. This paper discusses an application of a new risk assessment method, in which risk calculation is based on Fuzzy Cognitive Maps (FCMs) to a complex automated video surveillance system. FCMs are used to capture dependencies between assets and FCM based reasoning is applied to aggregate risks assigned to lower-level assets (e.g. cameras, hardware, software modules, communications, people) to such high level assets as services, maintained data and processes. Lessons learned indicate, that the proposed method is an efficient and low-cost approach, giving instantaneous feedback and enabling reasoning on effectiveness of security system.

A Multicriteria Model for Dynamic Route Planning

In this paper we introduce INSIGMA project and its part related to road transport. We propose methods and parameters for route optimization in dynamic urban environments. An overall motivation for development of proposed dynamic system is discussed with detailed efficiency analysis of placed algorithms. From the end users’ perspective, several practical use cases are identified. The system takes advantages of so-called dynamic maps, which provide information about up-to-date traffic conditions and visualization functionality as well.

OpenCL Implementation of PSO Algorithm for the Quadratic Assignment Problem

This paper presents a Particle Swarm Optimization (PSO) algorithm for the Quadratic Assignment Problem (QAP) implemented on OpenCL platform. Motivations to our work were twofold: firstly we wanted to develop a dedicated algorithm to solve the QAP showing both time and optimization performance, secondly we planned to check, if the capabilities offered by popular GPUs can be exploited to accelerate hard optimization tasks requiring high computational power. We were specifically targeting low-cost popular devices, with limited capabilities. The paper discusses the algorithm and its parallel implementation, as well as reports results of tests.

Ontology Oriented Storage, Retrieval and Interpretation for a Dynamic Map System

This paper presents the Dynamic Map system, one of the key products of the INSIGMA Project. The main focus is on the map and dynamic data storage subsystem, which utilizes a spatial database and is based on ontologies. First, the data models used are described, including the OpenStreetMap-based structure for the static map and the ontology-driven structure for dynamic parameters and events. The approach to generation of database structures from OWL is described in detail, followed by descriptions of the OSM import process, the GPS tracker module, the sensor state analyzer and the event interpreter. Finally, the planned future enhancements are outlined and discussed.

Learning Fuzzy Cognitive Map for Traffic Prediction Using an Evolutionary Algorithm

The motivation for the presented work was the need for solution allowing efficient estimation of traffic parameters in based on sparse measurements covering a small fraction road segments within large urban road network. The solution was intended to be deployed within the Dynamic Map, an important component of the INSIGMA system used for route planning and traffic control. We have chosen to base the estimation model on Fuzzy Cognitive Maps (FCM) formalism and apply an Evolutionary Algorithm to learn the model parameters. The main argument in favor of FCM is their simplicity and the speed of calculations that can be required for real-time updates of traffic parameters. This paper discusses a novel evolutionary algorithm for FCM learning and demonstrates feasibility and efficiency of such approach by giving results of tests performed on road networks of various size.

Bees Algorithm for the Quadratic Assignment Problem on CUDA Platform

With the proliferation of graphics processing units (GPU) supporting general-purpose computing (GPGPU), many computationally demanding applications are being redesigned to exploit the capabilities offered by massively parallel computing platforms. This paper presents a Bees Algorithm (BA) for the Quadratic Assignment Problem (QAP) implemented on the CUDA platform. The motivations for our work were twofold: firstly, we wanted to develop a dedicated algorithm to solve the QAP showing both time and optimization performance, secondly, we planned to check if the capabilities offered by popular GPUs can be exploited to accelerate hard optimization tasks requiring high computational power. The paper describes both sequential and parallel algorithm implementations, as well as reports results of tests.

INSIGMA: an intelligent transportation system for urban mobility enhancement

Intelligent Transportation Systems (ITS) aim to improve safety, mobility and environmental performance of road transport. The INSIGMA project provides a fresh look at the possible innovations in this field, by enhancing the functionality and accuracy of ITS in urban environments. This paper describes the architecture, sensors, processing algorithms, output modules and advantages of the developed system. A comparison of existing ITS systems has been provided as background. Special attention has been given to performance and privacy issues, as the system includes social aspects such as location monitoring.

Contribution of the INSIGMA Project to the Field of Intelligent Transportation Systems

With the growing number of vehicles traveling on public roads, traffic congestion has become a serious problem, resulting in more unpredictable travel times, increased fuel consumption and pollution. Intelligent Transportation Systems (ITS), already being developed by several countries, aim to improve safety, mobility and environmental performance. The goal of the INSIGMA project is to develop a system providing functionality of a typical ITS: real-time traffic monitoring, route planning and traffic control. In this paper we discuss the concepts and solutions developed within the project: dynamic map, sensors – videodetector and GPS tracker – as well as advanced route planning and traffic control algorithms.

Strategic Planning Optimization Using Tabu Search Algorithm

In this paper, we introduce a method for the optimization of strategic tasks using an approximation algorithm. We propose a mathematical model and suboptimal algorithm for solving this problem near optimally. An overall motivation for the development of the proposed algorithm is discussed with a detailed efficiency analysis. From an end users’ perspective the proposed method has practical applications because it can be used in several applied situations.