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Team Centelon


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CityCent

Project Info

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Team Name


Team Centelon


Team Members


Antony Thomas , Kathirvel , Prabhash , Kiran , Megha , Kavitha , Raj , Vivek C and 1 other member with an unpublished profile.

Project Description



CityCent: Empowering Safer Roads, Together

CityCent is a revolutionary mobile application designed to enhance road safety in urban environments by connecting communities and authorities through real-time data and collaborative features.

Key Features:

  • Real-Time Alerts: Receive instant notifications about traffic congestion, accidents, road closures, and other potential hazards, allowing for safer and more efficient navigation.
  • Hazard Reporting: Empower users to actively contribute to road safety by reporting potholes, broken traffic signals, dangerous intersections, and other hazards directly through the app.
  • Community-Driven Safety: Foster a sense of collective responsibility by enabling users to share information, updates, and observations about road conditions, promoting awareness and proactive safety measures.
  • Authorities Dashboard: Provide city authorities with a powerful tool to visualize real-time data, identify high-risk areas, allocate resources efficiently, and make informed decisions regarding infrastructure improvements and safety campaigns.

Benefits:

  • Improved Road Safety: Reduce accidents and injuries through real-time alerts, hazard reporting, and data-driven decision-making.
  • Enhanced Traffic Flow: Minimize congestion and travel times by providing users with alternative routes and real-time traffic updates.
  • Empowered Communities: Foster a sense of ownership and engagement in road safety initiatives, encouraging collaboration between citizens and authorities.
  • Efficient Resource Allocation: Optimize the use of resources by identifying areas of greatest need and enabling proactive interventions.
  • Data-Driven Decision-Making: Utilize comprehensive data insights to inform long-term planning, infrastructure investments, and targeted safety campaigns.

Target Audience:

  • Urban Drivers: Enhance their driving experience with real-time alerts, hazard reporting, and community-driven safety features.
  • Cyclists and Pedestrians: Navigate the city with confidence, knowing that potential hazards are being identified and addressed.
  • City Authorities: Gain valuable insights into road safety trends, enabling proactive measures and data-driven decision-making.

CityCent envisions a future where cities are safer, more efficient, and more livable for everyone.


Data Story


Road safety remains a critical concern globally, with millions of accidents occurring globally every year. We set out to address this challenge by analyzing a government-provided road accident dataset. Our exploratory analysis revealed patterns—such as accidents being more frequent during certain times, under specific road conditions, and at high-risk locations.

However, data alone wasn’t enough. We integrated real-time traffic and weather feeds to create a dynamic prediction model that can forecast potential accidents based on current conditions. This allows us to issue real-time alerts for dangerous intersections, speeding, or sudden weather changes.

To help authorities make informed decisions, we developed an AI-driven Executive Briefing Agent that generates detailed accident reports and insights. This empowers city planners to identify risk patterns and proactively improve infrastructure or adjust traffic control measures.

Our platform, CityCent, extends beyond just analysis. It provides a mobile app that delivers real-time safety alerts to citizens, while authorities can monitor and respond to potential hazards. As we refine our models and expand data integration, we aim to create a future where road safety is not just reactive but preventive—making our streets safer for everyone.

Our findings and source code can be verified via Git and the model we have created.


Evidence of Work

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Homepage

Project Image

Team DataSets

Victoria Road Crash Data

Data Set

Challenge Entries

AI applications using Open Road Crash data

How might we leverage road crash statistics and multi-agent AI-based web applications to enhance road safety and inform policy making?

Go to Challenge | 13 teams have entered this challenge.

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How might we use data insights to promote the development of sustainable urban infrastructure and reduce dependency on private vehicles?

Go to Challenge | 26 teams have entered this challenge.

Smart infrastructure for data-driven decision making

How can the council leverage climate and movement data from its multi-function poles, sensors and devices to improve asset management, optimise services, and/or design cleaner, more livable urban spaces?

Go to Challenge | 16 teams have entered this challenge.