Inspiration
The inspiration for EcoLens stemmed from our shared passion for the environment and our desire to leverage cutting-edge technology to make sustainable living accessible and effortless. With increasing awareness about climate change and environmental degradation, we wanted to create a tool that empowers individuals to make eco-friendly choices in their daily lives. EcoLens is our answer to the call for action, blending technology and sustainability to help users live their best eco-conscious lives.
What it does
EcoLens is an intelligent app powered by Google Gemini Generative AI, designed to assist environmentally conscious individuals in their journey towards sustainable living. By simply snapping photos of objects or scenes in their surroundings, users can receive tailored insights in three key areas:
- Recycling Insights: Guidance on how to properly recycle items and reduce waste. It can also tell consumers if something is greenwashed, which may be useful when out and about shopping and even online.
- Biodiversity/Nature Insights: Information on local flora and fauna, promoting awareness and conservation efforts.
- Vegan Food Insights: Recommendations and recipes for delicious vegan meals, supporting a plant-based lifestyle.
EcoLens provides personalized, actionable advice to help users make informed decisions that benefit the planet.
How we built it
Building EcoLens was a collaborative effort that involved several key steps:
- Ideation and Research: We started by brainstorming features that would be most beneficial to environmentally conscious users. We conducted extensive research on current environmental challenges and sustainable practices.
- Integration with Google Gemini Generative AI: Leveraging the powerful capabilities of Google Gemini, we integrated its AI functionalities to recognize and analyze photos taken by users.
- Development: Using a combination of front-end and back-end technologies, we developed the app’s user interface and core functionalities. Our tech stack included React Native for a seamless cross-platform experience and Node.js for the backend.
- Training the AI Model: We trained the AI model with a diverse dataset to ensure accurate recognition and insightful recommendations across the three key areas of focus.
- Testing and Iteration: Rigorous testing was conducted to refine the app's performance and user experience, incorporating feedback to make continuous improvements.
Challenges we ran into
Throughout the development of EcoLens, we faced several challenges:
- Adaptable Image Model: Making the image model adaptable to accurately recognize a wide range of photos and provide relevant insights for nature, food, and recyclable items was a significant challenge. Ensuring the AI could distinguish between these categories required extensive training and fine-tuning.
- Tool Selection: Choosing the right tools and technologies that could seamlessly integrate with Google Gemini and provide a smooth user experience was crucial. We needed tools that were both robust and flexible to support our diverse feature set.
- Accurate Responses: Ensuring the AI provided accurate and reliable insights for recycling, nature, and vegan food required meticulous data collection and validation. This was critical to maintaining user trust and delivering valuable information.
- Greenwashing Detection: Implementing a feature to identify greenwashing and determine the recyclability of items added an extra layer of complexity. It was essential to develop criteria and algorithms that could effectively evaluate the sustainability claims of products.
Accomplishments that we're proud of
We are incredibly proud of several accomplishments achieved during this project:
- Successful AI Integration: Seamlessly incorporating Google Gemini’s advanced AI capabilities to deliver accurate and useful insights to users.
- User-Centric Design: Creating an app that is not only functional but also user-friendly, ensuring that users of all ages and tech-savviness can benefit from EcoLens.
- Positive Environmental Impact: Developing a tool that has the potential to significantly influence individuals’ lifestyle choices in favor of sustainability.
What we learned
The journey of building EcoLens was a tremendous learning experience for our team. We gained deeper insights into:
- AI Technology: Enhanced our understanding and skills in leveraging AI for practical applications, particularly in the field of image recognition and analysis.
- Sustainable Practices: Broadened our knowledge of environmental issues and sustainable living practices, which we embedded into the app’s functionalities.
- Team Collaboration: Improved our collaborative skills, learning to navigate and overcome obstacles as a cohesive unit.
What's next for EcoLens
The future of EcoLens is bright and filled with exciting possibilities. Our next steps include:
- Feature Expansion: Adding more categories and insights, such as water conservation tips and eco-friendly product recommendations. We also want to make it multimodal and take in a "video" feed and you can just talk to it naturally instead of having to tap the picture button. It will also have greater context and reasoning abilities as models improve and become cheaper. We may even possibly add options to ask further questions. We also want to add options to add items onto a "free marketplace" which will promote reuse and a circular economy, in a literal sense. We also want to give options to use AI to post items on Ebay and other platforms.
- Enhanced AI Capabilities: Continuously improving the AI model for even greater accuracy and a wider range of recognitions.
- Community Engagement: Building a community feature where users can share their sustainable living tips and success stories, fostering a supportive eco-conscious network.
- Global Reach: Expanding the app’s reach to users worldwide, incorporating localization features to cater to different regions and cultures.
With EcoLens, we aim to create a global movement towards a more sustainable future, one snap at a time.

Log in or sign up for Devpost to join the conversation.