Real-time Event Detection, Prediction, and Visualization for Emergency Response

该项目提出了用于实时识别和预测现实世界事件的新型端到端方法，从而及时应对疾病爆发和自然灾害等紧急情况，以及预防犯罪，安全漏洞等。它将开发新技术，通过结合自适应学习和概率模型来快速检测和预测事件，并解决融合和可扩展性因素，以处理大量异构数据。将开发一个事件监测系统原型，将研究结果与可视化和描述事件的工具结合起来。

This project proposes novel end-to-end methods for real-time recognition and prediction of real-world events, leading to timely response to emergencies such as disease outbreaks and natural disasters, as well as prevention of crime, security breaches and the like. It will develop new techniques to quickly detect and predict events by incorporating adaptive learning and probabilistic models, and address fusion and scalability factors to handle vast collections of heterogeneous data. An event surveillance system prototype will be developed to incorporate the findings of the research with tools to visualise and describe events.