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Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
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Geographic Information Systems (GIS) are tools for storing, analyzing, and displaying spatial data alongside related attributes. Unlike traditional information systems that address general queries, GIS incorporates spatial components, enabling users to answer "where" and "how far." For example, GIS can process housing data linked to geographic locations like zip codes, allowing insights into population density or housing distribution through thematic maps.GIS integrates technologies such as...
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Geographic Information System (GIS) technology is essential for risk identification, action prioritization, and resource optimization in critical situations like flooding and earthquakes. By integrating spatial and demographic data, GIS provides a comprehensive framework for emergency response.GIS integrates data layers, like rainfall intensity, topography, elevation profiles, and river levels, to model high-risk flood zones. These layers assess areas susceptible to flooding based on their...
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Updated: Jun 3, 2025

Vegetated Treatment Systems for Removing Contaminants Associated with Surface Water Toxicity in Agriculture and Urban Runoff
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Upcity: Addressing Urban Problems Through an Integrated System.

Andre A F Silva1, Adao J S Porto1, Bruno M C Belo1

  • 1Computer Science Division, Aeronautics Institute of Technology, São José dos Campos 12228-900, Brazil.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
Summary
This summary is machine-generated.

Cities can integrate existing sensors for better urban problem-solving. An AI-powered system for pothole detection demonstrates improved accuracy and transparency for administrators and citizens.

Keywords:
integrated systemmodeling with UMLpothole detectionsmart citiesurban problems

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Area of Science:

  • Urban planning and smart city technologies.
  • Cyber-physical systems and data integration.
  • Artificial intelligence in municipal management.

Background:

  • Cities possess numerous sensors but lack integrated data systems, hindering collaboration and transparency.
  • Siloed data domains and stakeholders prevent effective, cross-sectoral urban problem-solving.
  • A need exists for integrated systems enabling data and dashboard sharing among city administrators.

Purpose of the Study:

  • To present a model for an integrative cyber-physical system to manage municipal problems.
  • To demonstrate the application of this model in addressing urban issues like road maintenance.
  • To enhance collaboration and transparency in city administration through shared data.

Main Methods:

  • Developed a cyber-physical system model encompassing physical objects, sensors, databases, code, and human interaction.
  • Integrated an AI model for pothole identification into citizen and operator applications.
  • Utilized cell phone cameras for citizens and operators to submit pothole images and locations.

Main Results:

  • The integrated system demonstrated high accuracy in detecting potholes, with sensor accuracy ranging from 91% to 99%.
  • AI model achieved significant accuracy in identifying potholes from submitted images.
  • Dashboards provided transparent progress views for managers and citizens, aiding problem resolution.

Conclusions:

  • An integrated cyber-physical system can effectively manage urban problems by connecting disparate data sources.
  • AI-powered pothole detection showcases the potential of integrated systems for improving city services.
  • Enhanced transparency and data sharing foster better oversight and citizen engagement in municipal management.