UN Sustainable Development Goals - Agenda 2030
- Build resilient infrastructure, promote inclusive and sustainable industrialization, and foster innovation
- Make cities and human settlements inclusive, safe, resilient, and sustainable
Overview
The development of more efficient and accessible communication and monitoring technologies has triggered a new set of applications aimed at improving quality of life in modern cities. In this still-evolving scenario, there is a need for applications that reduce the negative impact of critical events, potentially decreasing the number of deaths and injuries while also reducing economic losses. When trying to create safer cities, it is essential to implement fast, comprehensive, and robust emergency detection.
Event-oriented applications have been developed to detect specific critical situations. By employing smart sensors and distributed monitoring approaches, dangerous events can be detected, thus triggering alert notifications to affected people, authorities, or other computer systems. In this highly dynamic scenario, different solutions have been designed to handle a given type of emergency, inevitably creating a set of incompatible and sometimes conflicting applications. Thus, to address the challenges foreseen in creating safer and more resilient cities, a different direction must be taken.
A multi-sensor unit is a special device capable of obtaining various types of data about the surrounding environment. These devices can be leveraged as a flexible and highly configurable event detection unit, providing continuous information about the occurrence of one or more critical situations in a city. In this scenario, when spatial data is also combined to compose a unified perspective of detected events, the use of these units can significantly improve how we perceive an urban environment, providing information about emergencies and recording incidents for future analysis. This integrated and flexible distributed monitoring approach enables better support for emergency management compared to various independent solutions focused only on a particular type of critical situation.
Objectives
- Develop new algorithms for obtaining configurations and physical locations of detection units
- Explore different data sources and artificial intelligence methodologies
- Address multi-objective optimization challenges for sensor deployment
- Consider network communication issues (high bandwidth, reliability, real-time response)
- Create a reference emergency management system adaptable to any city
- Improve emergency management efficiency in urban areas
Challenges Addressed
- Deployment optimization: Efficient placement of detection units considering safe and accessible areas, coverage requirements, and population configurations
- Multi-objective optimization: Handling distinct critical event probabilities across city sub-regions
- Sensor configuration: Different sensors have specific positioning characteristics that increase optimization complexity
- Network reliability: Communication issues that can compromise emergency detection system effectiveness