EcoEd: Sustainability Insights for Schools

Empowering schools to reduce resource waste and promote eco-friendly practices through actionable insights powered by machine learning. Make sustainability simple, impactful, and collaborative!

Comment

Inspiration

      ▶The idea for EcoEd was born from a shared desire to make schools more environmentally conscious while empowering students to actively participate in sustainability efforts. Observing the inefficiencies in resource usage and the lack of actionable insights for students and staff inspired us to create a tool that bridges this gap using data and machine learning.

What it does

      ▶EcoEd is an AI-powered application designed to help schools manage resources sustainably and promote eco-friendly practices. Here are its key functionalities:

                •Resource Usage Analysis: Tracks energy, water, and waste usage trends using real or simulated data.

                •ML-Powered Insights: Utilizes the Random Forest algorithm to predict high resource consumption periods and suggest actionable steps to reduce waste.

                •Interactive Dashboards: Visualizes data through graphs, charts, and heatmaps to help users understand trends and areas for improvement.

                •Gamified Engagement: Encourages students to participate in sustainability efforts with leaderboards, badges, and challenges.

                •Actionable Recommendations: Provides tailored suggestions to schools, such as upgrading to energy-efficient appliances or implementing conservation policies.

How we built it

     ▶Defining the Problem: We identified key challenges schools face in managing resources sustainably, such as high energy consumption and lack of engagement in eco-friendly initiatives.

                 •Data Collection:

                      »Simulated utility usage data for electricity, water, and waste management.

                      »Survey responses from students and staff regarding resource usage habits.

                •Algorithm Implementation:

                     »Leveraged the Random Forest algorithm to predict high consumption periods and analyze feature importance.

                     »Used Python libraries like scikit-learn, pandas, and numpy for data processing and modeling.

                •Visualization:

                    »Created interactive dashboards using Plotly to display trends, predictions, and suggested actions.

                    »Designed gamified leaderboards to encourage eco-friendly behaviors among students.

                •Frontend and Backend Development:

                    »Built the user interface using Streamlit for simplicity and accessibility.

                    »Connected it to a Flask backend for processing data and running ML models.

Challenges we ran into

      •Data Availability: Limited access to real-world data meant relying on simulated datasets, which may not fully capture real-life complexities.

      •Model Optimization: Tuning the Random Forest model to ensure accurate predictions and meaningful insights required extensive testing and iteration.

      •User Interface Design: Balancing functionality and simplicity was challenging to ensure that both tech-savvy and non-tech-savvy users could easily navigate the app.

Accomplishments that we're proud of

       •Successful Implementation of Random Forest: Integrating a machine learning algorithm to generate actionable insights was a significant achievement, given the challenges of tuning and optimization.

       •Interactive and User-Friendly Dashboard: Designing a visually engaging and intuitive interface that communicates data effectively to a diverse audience.

       •Simulated Real-World Impact: Creating a model that can be easily adapted to real-world use cases, demonstrating its potential to improve sustainability in schools.

       •Team Collaboration: Effectively dividing tasks and leveraging each team member's strengths to deliver a cohesive and impactful project.

        •Raising Awareness: Highlighting the importance of sustainability in schools and sparking conversations about resource efficiency among students and staff.

What we learned

                   Working on this project provided valuable insights into the following areas:

      •Machine Learning: Understanding the practical application of the Random Forest algorithm for predicting patterns and generating actionable insights.

      •Sustainability Practices: Gaining knowledge about eco-friendly practices that can be implemented in schools.

      •Collaboration: Learning how to work effectively as a team, dividing responsibilities, and bringing together diverse skill sets.

What's next for EcoEd: Sustainability Insights for Schools

      •Integration with IoT Devices: Incorporate real-time data from IoT sensors for more accurate tracking and predictions.

      •Expanding the Dataset: Collaborate with schools to collect real-world data and refine the model for greater accuracy and relevance.

      •Customizable Features: Allow schools to tailor the app to their specific needs, such as adding custom metrics or unique sustainability goals.

      •Mobile App Development: Extend the platform to mobile devices for on-the-go engagement and accessibility.

      •Educational Campaigns: Develop resources and workshops to teach students and staff about sustainability and the importance of data-driven decision-making.

      •Scaling Beyond Schools: Adapt EcoEd for use in other community settings, such as offices, colleges, and local businesses, to promote widespread sustainability practices.
Share this project:

Updates