Real-time Big Data Analysis Platform for Meteorological Applications


Summary:


It is becoming very important to understand and predict various meteorological phenomena, such as lightening, tsunami, and rain precipitation. This can help us reduce the damage they cause. For example, every year, lightning strikes kill many people, farm animals, and wild animals, cause thousands of fires, and result in losing billions of dollars in damage to buildings, communication systems, power lines and, electrical systems. In this project, we will provide a platform that performs real time analysis and that supports several meteorological applications. 




Meteo Apps Real-Time Analysis

Project Members

Iman Elghandour

Mina Edward

Mohamed Aboelhassan




Collaborators

Prof. Zen Kawasaki

Dr. Lotfy Samy

Ahmed Moawad



Awards:


 ITAC Graduation Project Fund, 2016.



Publications:


Mohamed Hassaan and Iman Elghandour. A Real-Time Big Data Analysis Framework on a CPU/GPU Heterogeneous Cluster: A Meteorological Application Case Study. In Proc. IEEE/ACM Int. Conf. on Big Data Computing, Applications, and Technologies (BDCAT), Shanghai, China, 2016.