Project CoolCity

Chatbot
Home
AI recommendation based on the Environmental Data
Environmental Data of selected location
Map
Current Location

Inspiration

We are tackling the escalating urban temperatures caused by climate change, which are disrupting daily life. In our cities, temperatures have risen significantly due to solar heat, industrial emissions, vehicular heat, and other natural factors. We aim to develop an AI-powered solution to mitigate these rising temperatures.

What it does

Our AI system, designed to reduce urban temperatures, generates feasible solutions based on indices of rising temperatures. Additionally, we have created a ChatBot using the Gemini API to provide accurate answers in any situation.

How we built it

Map Interface Display: An interactive map allows users to click on various points. Location Data Retrieval: Upon clicking a point, the system fetches latitude and longitude using Maptiler API and LeafletAPI calls.

Environmental Data Display: Using OpenWeatherAPI and AgroMonitoringAPI, the system displays environmental data such as air index, temperature, air pollution levels, soil index, and other natural heat indices. The GoogleAirQualityAPI is also used for air quality index. Data Processing: Collected data is sent to Gemini'sAPI for detailed analysis. Solution Generation: Gemini's API analyzes the data and generates optimal solutions considering natural and local factors. Solution Display: The solution is displayed through a user-friendly interface. Gemini-Based ChatBot: A ChatBot developed using Gemini API provides suitable answers to user queries.

Challenges we ran into

The main challenges Project CoolCity likely faced include:

Integrating multiple data sources and APIs Developing a complex AI system for environmental analysis Ensuring real-time processing and response Generating accurate long-term predictions Creating an intuitive user interface for complex data Ensuring scalability across different urban environments Developing an accurate and versatile ChatBot Balancing interdisciplinary knowledge requirements

Accomplishments that we're proud of

We finished the project. We worked in team and collaborated with each other.

What we learned

We gained valuable experience in integrating diverse environmental data sources with AI technology to address complex urban climate challenges.

What's next for Project CoolCity

We have to enhance the functionality more by adding more features.

Built With

Submitted to

AI for Change Hackathon
- Winner Generation XYZ Domain
- Winner 1 year of Wolfram|One Personal Edition + 1 year of Wolfram|Alpha Pro

Created by

I worked on integrating the Gemini API and also developed some APIs using Node.js and Express.js. Also, I worked on visualizing the map using Maptiler and leaflet and creating the AI powered chatbot.

Md. Farhan Islam Shuvro
But I have promises to keep, And miles to go before I sleep.
I worked in the backend for connecting different API's, helped to design frontend components and integrated these and maintained git branches.

Ibne Bin Rafid
BSc. Software Engineering @ IIT, DU | Coding Enthusiast | Web Developer | UI/UX Designer | Problem-Solver
I worked on the back end and integrated the Google Maps API for displaying the Air Quality Index (AQI). Additionally, I contributed to the front-end styling and design. It was a great experience working on a team project.

Tanvir Hasan Abir
I worked on frontend and project idea making. It's a great opportunity for me to work in a group.

Khandakar Mehedi Hasan