Inspiration
Our team's inspiration for our project stemmed from a collective concern for environmental conservation and a desire to leverage technology for positive change. We recognized the pressing issue of litter and pollution in our communities and sought to create a solution that empowers individuals to take action and make a difference.
What it does
TrashBots utilize AI image recognition to detect and report litter, simplifying cleanup efforts.
How we built it
In terms of technologies, we utilized a combination of AI image recognition with ChatGpt 4, web development frameworks such as HTML, and CSS, to create our trashbots web application.
Challenges we ran into
Throughout our project development, we encountered several challenges. One of the biggest challenges was refining the stylesheet to align with our aesthetic vision. We spent considerable time tweaking the layout of the page to ensure it met our design standards. Additionally, utilizing generative AI tools such as ChatGPT posed its own set of challenges. We had to ensure we prompted the right questions and understood how our domain for HTML/CSS worked, rather than simply expecting to receive the code we needed.
Adding functional behavior to the website was another significant challenge. We wanted to ensure that the page would scroll smoothly to certain elements when clicked by the user. Applying hover effects using CSS to change the appearance of icons also presented difficulties. Overall, we were focused on optimizing the user experience and ensuring seamless integration of these various features, which required quick thinking and problem-solving skills.
Accomplishments that we're proud of
Our project achievements include successfully incorporating ChatGPT-generated images/logos into our web application, complemented by the implementation of CSS code. This integration significantly contributed to the development of a user-friendly platform that simplifies environmental engagement for all users.
What we learned
Despite these challenges, our team learned valuable lessons in collaboration, and problem-solving. We gained a deeper understanding of AI image recognition technology, web development, and user interface design. Furthermore, we honed our communication skills and learned to adapt to adapting our project requirements.
What's next for Trash Bots
Looking ahead, we aim to enhance the capabilities of our TrashBots platform by integrating a blend of AI image recognition algorithms, web development frameworks like JavaScript, and backend technologies. This will refine our TrashBots web application, ensuring a smoother user experience. Moreover, our plan includes integrating APIs for geolocation services and notifications, adding further layers of functionality and convenience. Additionally, we intend to introduce features such as gamification elements, community forums, and educational resources. These additions will deepen user engagement and promote environmental stewardship. Expanding our reach is another goal, as we strive to collaborate with local communities, organizations, and governments. Together, we aim to make a meaningful impact in the ongoing battle against litter and pollution. Given more time, we would have implemented SQL databases to efficiently store and manage information related to locations, user activities, and other relevant data. This would have allowed us to offer more personalized user experiences and conduct insightful analytics to better understand user behaviors and trends.
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