In modern life the road safety has becomes the core issue. One single move of a driver can cause horrifying accident. The main goal of intelligent car system is to make communication with other cars on the road. The system is able to control to speed, direction and the distance between the cars the intelligent car system is able to recognize traffic light and is able to take decision according to it. This paper presents a framework of the intelligent car system. I validate several aspect of our system using simulation.

We proposed an authentication mechanism in the wireless sensor network. Sensor network uses the Kerberos authentication scheme for the authentication of bases station in the network. Kerberos provides a centralized authentication server whose function is to authenticate user by providing him the ticket to grant request to the base station. In this paper we have provided architecture for the authentication of base station in the wireless sensor network based on the Kerberos server authentication scheme.

The design, development and testing of intelligent disaster detection and alerting systems pose a set of non-trivial problems. Not only are such systems difficult to design as they need to accurately predict real-world outcomes using a distributed sensing of various parameters, they also need to generate an optimal number of timely alerts when the actual disaster strikes. In this paper, we propose the SimConnector Emulator, a novel approach for the testing of real-world systems using agent-based simulations as a means of validation. The basic idea is to use agent-based simulations to generate event data to allow the testing of responses of the software system to real-time events. As proof of concept, we have developed a Forest Fire Disaster Detection and Alerting System, which uses Intelligent Decision Support based on an internationally recognized Fire rating index, namely the Fire Weather Index (FWI). Results of extensive testing demonstrate the effectiveness of the SimCon-nector approach for the development and testing of real-time applications, in general and disaster detection/alerting systems, in particular.

In this paper, we present the verification and validation of an agent-based model of forest fires. We use a combination of a Virtual Overlay Multi-Agent System (VOMAS) validation scheme with Fire Weather Index (FWI) to validate the forest fire Simulation. FWI is based on decades of real forest fire data and is now regarded as a standard index for fire probability with wide usage across Canada, New Zealand and Australia. VOMAS approach allows for flexible validation of agent-based simulation models. In the current work, it is used in the form of a simulation of a randomly deployed Wireless Sensor Network for forest monitoring. Here, each virtual "sensor" agent uses FWI to calculate fire probability and compares it with the simulation model. VOMAS verification and validation methodology for agent-based models allows for interactive design of Agent-Based Models involving both the Simulation Specialists as well as the Subject Matter Experts. The presented simulation model also uses weather parameters such as wind speed, rain, snow to calculate Indices such as Fire Weather Index (FWI), Build Up Index (BUI) and Initial Spread Index (ISI) in real time. We also study the effects of fires on the life of simulated VOMAS sensors. Using extensive simulations, we demonstrate the effectiveness and ease of use of VOMAS based Validation.

Fire modeling is used to understand and to predict possible fire behavior without getting burned. Fire models are used in different aspect of fire management. The increase in the number of forest fires in the last few years has forced governments to take precautions. Beside prevention, early intervention is also very important in fire fighting. If the fire fighters know where the fire will be in sometimes it would be easier for them to stop the fire. Therefore a big need for simulating the fire behavior exists. In this paper we present the survey of various forest fire simulations. The main goal is to determine how forest fires develop in different manners under specific conditions.

Fire modeling is used to understand and to predict possible fire behavior without getting burned. Fire models are used in different aspect of fire management. The increase in the number of forest fires in the last few years has forced governments to take precautions. Beside prevention, early intervention is also very important in fire fighting. If the fire fighters know where the fire will be in sometimes it would be easier for them to stop the fire. Therefore a big need for simulating the fire behavior exists. In this paper we present the survey of various forest fire simulations. The main goal is to determine how forest fires develop in different manners under specific conditions.