Abstract:
In present times data is a ubiquitous resource, and its analysis to deduce
highly selective and relatively more useful bits of information often holds
great signi cance. However, in most advanced systems, the deduction of
useful insights from a large dataset denotes only part of the required functionality;
because the information derived from the input data needs to be
integrated back into the system to increase the overall e ciency of operations
in terms of feedback-based predictive capabilities or intelligent decision
making.
Preferably, this integration of information in a dynamic environment
needs to be carried out autonomously with minimal human intervention in
order to gain maximum advantage of adopting this approach. For this purpose,
agent-based systems are most suited as they typically o er features
such as adaptability, pro-activeness, negotiation and learning with a certain
degree of autonomy to achieve pre-de ned goals.
Thus, the aim of the research was de ned as the integration of information
derived from real-time inputs in aiding intelligent decisions with a signi cant
degree of autonomy. For this purpose, long term management of nutrition
and health needs in modern day relief camps was chosen as a practical use
case since it is an often over-looked subject compared to immediate disaster
management where a lot of work has been done in developing advanced
systems. Moreover, given the current scope of things where over 40 million
people have been displaced world over as a result of natural disasters, con-
icts or violence (with more than 1.5 million displaced persons registered in
Pakistan alone), the research holds great signi cance.
In order to enhance the stability, cost-e ectiveness and reliability, the
use of cloud services { in particular infrastructure as a service (IaaS), is
highly desirable. Hence, this research endeavor tends to focus on methods
for analysis of real-time sensory data, and the development of an automated
mechanism for integrating the select pieces of information within a cloudbased
system using multi-agents.
