Organizations and individuals have been facing disasters globally and locally since hundreds of years. Increasing number of natural disasters has demonstrated the paramount importance of the natural hazards subject for the protection of environment and the citizens. Now more than ever, designing an efficient traffic system, moving vast amounts of helping goods quickly and safely across great distances is one of our most pressing needs. Satellite navigation systems are changing the way in which we travel from place to place whether by land, sea or air and whether in remote areas or through congested city streets. Global positioning system (GPS) and its role in advanced transportation projects is inseparable and become a synonym. The management and operations of vehicles and giving real-time information to users that will lead to cost-effective and satisfied service to passengers is possible nowadays using a GPS based vehicle navigation system and communication via remote sensing. This paper describes how the already developed fleet management and remote sensing technologies can be merged together to form an efficient disaster management system

The rise in dependency upon information present on web and social networks has increased the importance of content credibility systems. These sys- tems can help the users to make a right decision related to buying a product, utiliz- ing a service and etc. Application areas including social network blogs of different subjects such as health, food, education, politics and product review/ratings some- times suffer incredible and wrong information flow. The content credibility sys- tems can help users to identify the credible information on these various forums. Recently, researchers have proposed certain mechanisms for these systems, out of which reputation based systems have gained most attention. However, reputa- tion systems are vulnerable to reputation based attacks, like Sybil, Slandering, and Whitewash promoting spread of wrong information. The authors have proposed a defense mechanism against these attacks that is based upon Bayesian Model. The proposed defense mechanism provides protection against these attacks so that fake or wrong information could be prevented. The authors evaluated the proposed mechanism in three different scenarios and presented the results in terms of pre- cision, recall and rate of change in rank. The results reveal almost 88%prevention against these attacks in comparison to the baseline systems.

In open multiagent systems individual components act in an autonomous and uncertain manner, thus making it difficult for the participating agents to interact with one another in a reliable environment. A reputation model can however predict the behavior of the agents and can optimize the issues related with dynamism. In this paper we present a critical analysis of an existing model for open MAS (FIRE) against our proposed swarm intelligence based reputation model. The model not only provides an optimum solution to various issues of reputation but also provides the mechanism of getting information from various sources.