Inspiration
We took a lot of inspiration from CBRE's existing technology products, especially CBRE ServiceInsight. Using the energy consumption data that ServiceInsight already collects, we focused on calculating and presenting this information in a way that’s easy to understand and visually engaging. We also built on CBRE's existing design system, adding our own modern touch to create a fresh look.
What it does
Our project helps building owners improve sustainability and energy efficiency with an easy-to-use, interactive solution. It includes a portfolio dashboard that shows key energy metrics, such as total electricity consumption, heating, cooling, and peak energy usage. Interactive charts break down energy emissions into categories like IT equipment, lighting, and HVAC systems. Users can filter data by year and month to track trends and patterns. A renewable energy chatbot also offers personalized advice on adopting greener practices and renewable energy solutions, making it easier for building owners to manage energy and reduce their environmental impact.
Psychology in Data
Our team consists of non-CS majors: three Cognitive Science students and one Biology student. We used our unique backgrounds to present the data in a visually engaging way, applying Gestalt Principles of Perception. According to the Interaction Design Foundation, 'Gestalt principles or laws describe how the human eye perceives visual elements, simplifying complex scenes into basic shapes.' With this in mind, we aimed to make the energy data easy for building managers to skim and understand quickly.
How we built it
Our project began by generating dummy data to simulate realistic metrics for a single office building, such as energy usage and environmental patterns. We cleaned and analyzed this data to develop a backend pipeline capable of visualizing trends by month and year, ensuring meaningful insights could be extracted. Once the frontend was completed, we worked on integrating it with the backend to enable users to interact dynamically with the visualizations and select the data they wanted to explore. To enhance functionality, we integrated OpenAI's LLM into the backend to create a chatbot named GreenIQ, designed to act as a green energy expert. GreenIQ provides tailored advice, answers energy efficiency questions, and makes sustainability concepts accessible through natural conversation. The final product combines data visualization and expert insights, empowering property managers to make informed decisions about energy use in office buildings.
Challenges we ran into
One of the major challenges we faced was integrating the frontend with the backend. Specifically, we needed to send user-selected year and month data from the frontend to the backend and return the appropriate values and visualizations. However, we encountered persistent issues with our POST and GET requests, which made it difficult to establish smooth communication between the two components. Debugging and resolving these issues, including managing request formats and ensuring proper data handling, took up the majority of our development time. This experience, though time-consuming, greatly improved our understanding of frontend-backend integration.
Accomplishments that we're proud of
An accomplishment we are particularly proud of is successfully building the chatbot in a relatively short amount of time, despite the significant challenges we faced with integrating the frontend and backend for the dashboard. While the integration process required extensive debugging and problem-solving, we were able to shift focus and efficiently develop the chatbot component, which added significant value to our project. The chatbot, designed to act as a green energy expert, exceeded our expectations in functionality and user engagement, making it a standout feature of our work
What we learned
We used Flask for the first time and successfully learned how to integrate it with a React frontend, overcoming the challenges of combining these technologies. Additionally, we gained valuable experience in conceptualizing a meaningful idea and transforming it into a working proof of concept within a demanding 24-hour timeframe. This process sharpened our ability to adapt, innovate, and collaborate under tight deadlines.
What's next for CarbonWise
Our next steps for CarbonWise involve creating interactive visualizations that allow property managers to simulate how changes in the consumption of specific electricity types, such as HVAC, general, processing, heating, or cooling, impact overall energy usage. A key feature will be a simulator that lets users test the effects of adjusting these variables on total energy consumption, providing actionable insights into optimization. Additionally, we plan to incorporate a cost analysis tool to highlight the financial benefits of adopting greener practices, further incentivizing property managers to make sustainable choices. These features will enhance the platform's value by empowering users to experiment with strategies for improving energy efficiency and reducing costs.
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