Enhancing Orphanage Well-Being Through Computer Vision

Local Chapter Cairo, Egypt Chapter

Coordinated byEgypt ,

Fares Elmenshawi

Status: Completed

Project Duration: 28 Jul 2023 - 01 Sep 2023

Open Source resources available from this project

Github Repository

Project background.

Every child deserves a safe and nurturing environment to grow and thrive, but unfortunately, many children around the world find themselves in orphanages due to various circumstances. In Egypt, there is a pressing need to ensure the well-being of children living in orphanages and to provide them with the best possible care. To address this challenge, we propose the implementation of a computer vision system for extensive analysis of orphanages in Egypt.

The story behind this project stems from the recognition that traditional methods of monitoring and evaluating orphanages often fall short in capturing the nuanced aspects of child well-being and caregiver performance. The limited resources and manpower available make it difficult to maintain consistent oversight, leading to potential gaps in care and missed opportunities for improvement. It is essential to leverage modern technology to revolutionize the way we analyze and support these vulnerable children.

The problem at hand is multifaceted. Ensuring the mode of children, understanding their activities, and monitoring worker performance are crucial aspects of maintaining a healthy and supportive environment within an orphanage. By harnessing the power of computer vision, we aim to go beyond superficial observations and delve deeper into the emotional well-being, daily experiences, and interactions of the children.

The problem.

We propose implementing a computer vision system in Egyptian orphanages to address the problem of limited monitoring and evaluation. This solution will revolutionize care provision and positively impact the local community. By accurately determining children’s emotional states and activities, the system will improve child well-being. It will optimize resource allocation, inform decision-making, promote accountability, and support research and policy development. Ultimately, our goal is to create a nurturing environment where vulnerable children can thrive.

Project goals.

- Implementing a computer vision system to accurately determine the mode of children in orphanages in Egypt, providing insights into their emotional well-being. - Developing algorithms to determine and track the activities of children throughout the day, enabling a better understanding of their engagement levels and areas for improvement. - Creating an automated system to monitor and evaluate the performance of workers in orphanages, ensuring adherence to protocols and providing feedback for improvement. - Generating insightful data in real-time, allowing for continuous analysis and decision-making to enhance the well-being of the children and optimize resource allocation. - Designing intuitive data visualization tools and dashboards to present the analyzed data in an easy-to-understand manner, enabling stakeholders to make informed business decisions. - Collaborating with child welfare experts and stakeholders to ensure the project is conducted ethically, respects privacy, and aligns with local cultural norms and regulations. - Conducting research using anonymized data to contribute to a broader understanding of child welfare in orphanages and support evidence-based policy development. - Promoting positive change within the local community by improving the quality of care and support provided to vulnerable children in Egyptian orphanages.

Project plan.

  • Week 1

    1. Evaluate person detection systems, balancing accuracy and computation.
    2. Assess face detection systems, considering accuracy and computation, and use the output for face detection.
    3. Explore face recognition systems, finding the right balance between accuracy and computation.

  • Week 2

    1. Implement a tracking algorithm, ensuring a balance between robustness and real-time performance.
    2. Develop an activity recognition system.

  • Week 3

    1. Create a system to determine the mood of a person, based on defined cues or behaviors.
    2. Integrate the system components and verify their seamless operation.

  • Week 4

    1. Generate insights from the collected data and establish relevant metrics.
    2. Design a user-friendly dashboard for visualizing the insights effectively.

  • Week 5

    1. Develop a Flask web app for hosting the dashboard.
    2. Containerize the code using Docker for easier deployment and reproducibility.
    3. (Optionally) Deploy the system on a web service, considering scalability and reliability.
    4. (Optionally) Create a mobile application for users to submit pictures and locations of homeless children.

Learning outcomes.

1. Understand and apply computer vision techniques for analyzing images or video footage.
2. Learn and implement machine learning algorithms for tasks such as object detection, and activity recognition.
3. Gain proficiency in data analysis and visualization techniques to extract insights and patterns from the generated data.
4. Develop skills in designing user interfaces and data presentations for effective communication of the analysis results to stakeholders.

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