Multi-resolution situation recognition for urban-aware smart assistant

该项目旨在开发一个态势识别框架，以识别和预测不可预见的新情况，如进度变化、事件和城市环境中的中断。该项目将通过捕捉和模拟人类流动性和工作惯例中的不可预测性来解决重大的知识差距。结果将是一个可以在个人、社会群体和城市层面以及多个地点和时间尺度上应用的情况识别框架。这应该为用户提供及时的通知和建议，以恢复他们的活动和例程。预期的好处将是广泛的，并适用于许多领域，从个人智能助手到旅行计划和应急服务。

This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services.