CONRAD - Health Condition Radar: an Intelligent System for Emergency Support

Morales Tirado, Alba; Daga, Enrico and Motta, Enrico (2022). CONRAD - Health Condition Radar: an Intelligent System for Emergency Support. In: SeWeBMeDA-2022: Proceedings of 5th Workshop on Semantic Web solutions for large-scale biomedical data analytics co-event with The ESWC 2022: Extended Semantic Web Conference.



Smart City initiatives have emerged as a technological solution to enhance the use of resources and improve city services. Emergency Management and Support is attracting considerable attention in this context, and several smart solutions have been proposed to support emergency services activities.

On the one hand, Electronic Health Records (EHR) data allows an emergency response system to derive a person’s current health status and consequently use this information to advise emergency bodies about people with ongoing health issues requiring assistance. On the other hand, using such comprehensive and detailed data has its challenges. EHR contain an overwhelming amount of information that emergency services cannot process effectively, for both its size and specificity. Furthermore, an intelligent system automatically analysing this data will require some knowledge for representing and reasoning over the evolution of health events.

This demo paper proposes a software architecture for using EHR to extract information that supports emergency services activities. The architecture uses Semantic Web technologies as tools to derive people’s ongoing health issues, specifically HECON Ontology and the KG for health evolution information. This demo paper also introduces CONRAD, the software prototype which demonstrates the architecture design in action. The prototype uses a dataset of synthetic health records as data input. Its output is a derived list of people in a vulnerable situation, a summary of their ongoing health issues and related needs.

Viewing alternatives

Download history

Item Actions