Projects / Top Talent Project

Improving Road Safety Around Schools in Africa Using Computer Vision & Drone Images

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This is a paid opportunity. In order to be eligible to apply for this project, you need to be part of the Omdena community and have finished at least one AI Innovation Challenge.

You can find our upcoming AI Innovation Challenges at https://omdena.com/projects.

The problem

In contemporary urban environments, ensuring the safety of children and pedestrians in the vicinity of schools has emerged as a critical concern. The daily commute to and from educational institutions often necessitates the negotiation of busy roadways, pedestrian crossings, and interactions with vehicular traffic. Unfortunately, this interaction between students, pedestrians, and vehicles can sometimes result in accidents and safety hazards. Recognizing the importance of addressing this issue, our project aims to leverage cutting-edge technology to enhance road safety in school zones.

The problem at hand revolves around the need to substantially improve road safety in and around school zones. Specifically, our project addresses the following challenges:

  • Pedestrian Safety: Pedestrian crossings near schools are high-risk areas where students frequently cross busy roads. The existing infrastructure for identifying and protecting pedestrians at these crossings is often inadequate, leading to potential accidents and injuries.
  • Traffic Management: School zones experience a surge in vehicular traffic during drop-off and pick-up times. Managing this traffic flow, including accurate vehicle counting and speed monitoring, is crucial for preventing congestion and reducing the risk of accidents.

Impact:

The impact of this project is multifaceted and far-reaching, with potential benefits for various stakeholders:

  • Enhanced Safety: By developing computer vision models to identify pedestrian crossings and accurately count pedestrians, we aim to significantly reduce the risk of accidents and enhance the safety of students, parents, and all pedestrians in school zones.
  • Efficient Traffic Management: Implementing computer vision-based vehicle counting and speed estimation will contribute to smoother traffic flow around schools, reducing congestion, and minimizing the chances of accidents caused by traffic-related issues.
  • Data-Driven Insights: The deployment of a user-friendly dashboard to visualize data will provide valuable insights for school authorities, traffic management agencies, and local governments. This data can inform decision-making processes related to road safety improvements and traffic management strategies.
  • Resource Optimization: Efficiently managing traffic and enhancing safety can lead to resource optimization for local authorities, potentially resulting in cost savings and improved resource allocation.
  • Community Confidence: By proactively addressing road safety concerns in school zones, our project aims to boost community confidence in the safety of school environments and the commitment of local authorities to student well-being.

In conclusion, our project endeavors to tackle the pressing issue of road safety around schools using advanced technology, with the ultimate goal of creating safer and more secure environments for students, pedestrians, and everyone else.

The project goals

The main project goal is to enhance road safety in proximity to educational institutions through the utilization of drones and cutting-edge computer vision technology. The primary utility of the developed solution will be in informing infrastructure improvements around schools and evaluating the impact of improvements that are put in place.

Scope:

  • Development of a computer vision model for identifying pedestrian crossings.
  • Implementation of a computer vision model for accurately counting pedestrians.
  • Creation of a computer vision model for counting vehicles without identifying them individually.
  • Development of a computer vision model for estimating the average and maximum speeds of vehicles.
  • Deployment of a user-friendly dashboard to provide visual representations of the gathered data.

**More details will be shared with the selected team.

Why join? The uniqueness of Omdena Top Talent Projects

Top Talent opportunities come as a natural next step after participating in Omdena’s AI Innovation Challenges.

Everyone in the community is eligible to participate once they have shown the relevant skills based on the merit of involvement in past Omdena challenges and the community.

If you are looking for the next challenge after participating in one or more Omdena AI Innovation Challenges, then we believe you have made the right choice! With a healthy, pressured environment, you will be pushed to contribute, learn and grow even more.

Find more information on how an Omdena Top Talent Program works

First Omdena Project?

Join the Omdena community to make a real-world impact and develop your career

Build a global network and get mentoring support

Earn money through paid gigs and access many more opportunities



Eligibility to join an Omdena Top Talent project

Finished at least one AI Innovation Challenge

Received a recommendation from the Omdena Core Team Member/ Project Owner (PO) is a plus



Skill requirements

Good English

Machine Learning Engineer

Experience working with Computer Vision is a plus.



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