Things you'll learn: MechE, ECE, HVAC systems, data science, Python, data visualizations, working with external partners

The BR sub-team will work to optimize the daily operations of Cornell University's Biomass Grinding facility by creating 1) a machine that will dry biomass particles evenly and efficiently, and 2) a system that keeps the facility at a reasonable temperature. Ultimately, the team will aim to reduce the facility's energy consumption and operating costs, utilizing guidance from contacts in the BEE, CEE, and ECE departments as well as the Campus Sustainability Office. For the Fall 2023 semester, the team is considering starting an additional project relating to lighting retrofitting. It has good potential in creating a direct connection to Earth Source Heating and expanding the team in terms of new recruits, since it involves specific data analysis and computational implementations.

Things you'll learn: Working with external partners, policy, data analysis, Tableau

The BPA sub-team is working to improve Cornell's Sustainability Dashboard, which is a website where the general public and Cornell students can track Cornell's progress towards sustainability and carbon neutrality. BPA is focusing on data analysis for the dashboard, primarily using information collected from the annual STARS (Sustainability, Tracking, And Ranking System) report on categories such as carbon neutrality, education, engagement, campus operations, and governance & finance. For the Fall 2023 semester, BPA will be looking to start a new project, possibly relating to expanding micro mobility solutions in Ithaca.

Things you'll learn: HTML, CSS, Python, Pandas, stats, data science, data visualization, design, Figma, Plotly Dash, databases, APIs, working with external partners

In partnership with the Campus Sustainability Office, the FHED sub-team aims to reduce the usage of high energy demanding equipment at Cornell. Particularly, FHED has been focusing on fume hoods, which are some of the most energy intensive devices on campus since they replace heated air from inside the room with cold air from outdoors. Their goal is to create a web dashboard that displays real-time energy usage of each fume hood on campus, which could be used to identify energy-intensive fume hoods. This past semester, they performed thermodynamic calculations in Python using API connections to Cornell’s Energy Management & Control System (EMCS) portal and developed a prototype of the dashboard using the Plotly Dash Python library. Going forward, the team will adapt the dashboard's user interface to client-based needs of 135 Cornell laboratory managers, as well as automate client outreach based on device control, status, and usage.

Things you'll learn: Python, Pandas, Machine Learning, APIs, working with external partners

The SC sub-team aims to reduce errors in Cornell's record of its campus energy consumption by detecting meter faults and anomalies. In the fall, SC focused on quality control, including detecting missing data, repetitions, sudden spikes in heating or cooling, and discrepancies from previous years. Going forward, SC plans to 1) improve baseline algorithms, 2) use ML packages to make the model predictive (e.g., based on weather patterns), 3) collaborate with other faculty and staff working in smart buildings, 4) establish methods of communicating when meters need to be fixed, and 5) develop more advanced model selection techniques based on biophysical formulas.

Things you'll learn: Machine Learning, working with external partners

The ETD sub-team is a new sub-team that aims to develop a Wave Energy Converter (WEC) that will power an Integrated Multi-Trophic Aquaculture Farm (IMTA) with the goal of addressing food security and less carbon-intensive food supplies. Members of the sub-team will have the opportunity to compete in the Marine Energy Collegiate Competition (MECC) and develop this WEC with help from the researchers of the Symbiotic Engineering and Analysis (SEA) Laboratory in the MAE department.