Development of a Multi-Agent-Based Simulation System for Air Quality Analysis

Abstract

Abstract:The implementation of distributed collaborative intelligence can improve the efficiency of agent-based environmental systems (for environmental networks) in the context of solving emergency situations in real time, such as the critical situation of severe air pollution with an important impact in a given region. In this paper it is presented a distributed multi-agent system for air quality monitoring and analysis (AQDMAS) whose first version was implemented in Zeus, a Java-based toolkit for intelligent agents' development. The study is focused on the possibilities of the computer network distribution of the software agents. The purpose of the system is to verify the air quality standard fulfilment, and if, in case some exceedances occur, to inform the supervisor in order to take a decision. For this version there were designed seven intelligent agents placed in a local computer network in the Petroleum-Gas University of Ploiesti campus in Romania. The results revealed the effectiveness of the proposed monitoring and analyzing technique and the possibility of autonomous built-in simulation of tracking the air quality evolution with distributed resources.

A Data-Driven Condition Monitoring of Product Quality Analysis System Based on RS and AHP

“…An analytical method to evaluate the quality performance of flexible manufacturing systems was approved [4]. A distributed multi-agent system for air quality monitoring and analysis was presented by using the computer network distribution [5]. In this paper, we describe our design on quality analysis system for complex mechanical and electrical products according to practice request.…”

Enhanced Education by Using Intelligent Agents in Multi-Agent Adaptive e-Learning Systems

“…MAS is a collection of autonomous entities called agents, which interact with each other and with their environment in a cooperative or competitive way in order to achieve individual and group goals [6]. According to Wooldridge [7], the major advantages of MAS are: decentralized control, robustness, simple extensibility, expertise and common resources.…”