Development of Autonomous Multi Agent System for Multi-Hazard Risk Assessment

Developing autonomous multi agent systems are to be considered anadvancement of multi agent systems can be applied in both the physical and the logicalworld. Constructions of multi hazard risk assessment using spatial data for disastermanagement have a problem of effective communication because of implicitknowledge. Risk assessment is the determination of quantitative or qualitative value ofrisk related to a concrete situation and a recognized hazard. Multi hazard riskassessment requires commonsense knowledge related with the hazard. This complicatesthe effective communication of data to the user in real-time machine processing insupport of disaster management. The aim of the approach is to identify the influences ofdeveloping autonomous multi agent systems for risk assesmnet in disaster management.The objectives should a) contribute to a better understanding of the transformationprocesses in commonsense knowledge related with a hazard and b) provide effectivecommunication of data to the user in real-time machine processing in support of disastermanagement.In this paper we present a metodology to modeling commonsenseknowledge in Multi hazard risk assessment using Autonomous multi agent system. Thisgives three-phase knowledge modeling approach for modeling commonsenseknowledge in, which enables holistic approach for disaster management. At the initialstage autonomous agents are initialized to convert commonsense knowledge based onmulti hazards into a questionnaire. Removing dependencies among the questions aremodeled using principal component analysis. Classification of the knowledge isprocessed through fuzzy logic agent, which is constructed on the basis of principalcomponents. Further explanations for classified knowledge are derived by agent basedon expert system technology. We have implemented the system using FLEX expertsystem shell, SPSS, XML and VB. This paper describes one such approach usingclassification of human constituents in Ayurvedic medicine. Evaluation of the systemhas shown 77% accuracy.Key words: Autonomous multi agent systems, Multi hazards, risk assessment,commonsense knowledge, Fuzzy logi

Ascertaining the sense of safety in urban neighborhood streets : the case of Kotahena, Sri Lanka

Streets are primary elements through which the character of urban neighborhoods are experienced and expressed. The “sense of safety” in neighborhood streets is paramount to social and psychological wellbeing of its residents and visitors. The intention of this study was to explore environmental and social cues of a neighborhood, which evoke fear of crime, which will help designers to prevent the generation of such negative feelings and promote more safe and comfortable spaces in our cities. This study used interviews, group discussions and observations to identify fear-generating factors with a sample of participants in the multi ethnic neighborhood of Kotahena in Colombo, Sri Lanka. Field data was analyzed through visual documentation and photographic surveys. Moreover, group discussions, interviews and personal observations were used to synergize the study objectives. The findings inform that fear of crime on streets is influenced by both environmental and social cues to varying degrees. Feelings of fear were associated with gender, ethnicity and less familiarity with the place as participants were from an ethnic minority within the community. Literature has emphasized that fear of crime has a connection to actual crime locations. The research findings, however, indicate that fear of crime spots identified by the residents do not have a direct relationship to the actual crime locations

SAS_EN - a swarm of agents for a sustainable environment

The environment consists of heterogeneous entities which are working collaboratively to keep the environment sustainable. The general concept of “environmental sustainability” refers to the necessary balance between human wants and needs and the capacity of the natural systems of the earth. Thus to keep the balance of environment the communication among photosynthesis, co2 emission, environmental conditions, nutrient conditions and nutrient deficiencies of the plant are important. Nevertheless, it has become a major issue in maintaining those conditions within a controlled environment. Therefore, the communication among resource entities that are involved in a certain task of the environment and reaching consensus for protecting and ensuring the sustainability of a given environment is highly important. Thus, this project implements SAS_EN, which collaboratively works for a sustainable environment in a Hydroponics Greenhouse environment. The system has been implemented using agent technology. There are distinct agents dedicated for each task of the environmental sustainability and they collaboratively work to achieve a common goal. Hydroponics, which grows in a controlled environment, has been used for testing and evaluating the solution. The test results have shown its potential in using SAS_EN for solving the distributed problems of the environment