Our goal is to connect our institution with people who have data skills to help our research team identifying problems and developing tools to solve big data-related problems that have a social impact in general and particularly in Saudi Arabia. Currently, we are building an end to end AI-based social media Analytic system for disaster prediction, mitigation, and emergency response. The project aims to develop a cloud-based computing framework that will systematically monitor, collect and integrate disaster and crisis-related data streams from diverse social network channels, and turn them into actionable intelligence in a knowledge-base for intelligent inferencing, crisis handling, and decision making. The key components of the proposed framework are three: First, the collection of multilingual and multimodal data (text, audios, videos, images, and location information or other sensor-data) and their conversion into a unified machine-understandable dynamic knowledge-base. Second, the application of Natural Language Processing (NLP), Data Mining, Machine Learning, and Artificial Intelligence techniques for automatic identification, prediction, and detection of any type of crisis or disaster using the unified knowledge-base from the previous stage. Third, the development of an interactive dashboard visualization to facilitate crisis monitoring and management.
Project name | Summary | Status | Social impact area |
---|---|---|---|
Cloud Enabled Social Media Analytics Framework for Crisis Management | This project aims to develop a cloud-based computing framework that will systematically monitor, collect and integrate disaster and crisis-related data streams from diverse social network channels, and turn them into actionable intelligence in a knowledge-base for intelligent inferencing, crisis handling, and decision making. The key components of the proposed framework are three: First, the collection of multilingual and multimodal data (text, audios, videos, images, and location information or other sensor-data) and their conversion into a unified machine-understandable dynamic knowledge-base. Second, the application of Natural Language Processing (NLP), Data Mining, Machine Learning, and Artificial Intelligence techniques for automatic identification, prediction, and detection of any type of crisis or disaster using the unified knowledge-base from the previous stage. 3) Third, the development of an interactive dashboard visualization to facilitate crisis monitoring and management. | In progress |
Years in operation: 1 to 5 years
Yearly budget: $100K-$500K
Geographical scope: Country
King Faisal University
College of Computer Science and Information Technology
Saudi Arabia, Eastern province 31982
Saudi Arabia
Phone number: None
Email address: