GateAI

• 

  1.0. Challenge Expiration Date

• 

  1.1. Challenge Expiration Date

• 

  1.2. Challenge Expiration Date

• 

  1.3. Challenge Expiration Date

• 

  2.0. Consumption Prediction

• 

  2.1. Consumption Prediction

• 

  2.2. Consumption Prediction

• 

  3.0. Productivity Estimation

• 

  3.1. Productivity Estimation

• 

  3.2. Productivity Estimation

• 

  3.3. Productivity Estimation

What It Does

The GateAI Suite provides insights, predictions, and recommendations related to warehouse management, in-flight food consumption, and employee productivity.

What We Offer

• Warehouse Data Twin: Includes risk assessments for your products, waste prediction, and simulation tools to prepare for flight delays or changes in consumption. It also provides operational recommendations to optimize performance.
• Consumption Prediction: Estimates the number of dishes that should be prepared based on specific flight parameters.
• Productivity Analytics: A centralized dashboard that visualizes EBT (Estimated Build Time) vs. ABT (Actual Build Time) for each trolley, employee, and site, transforming operational data into actionable KPIs.

How We Built It

We developed the project in Python, using the following libraries:

• Polars and Pandas for data manipulation
• NumPy for computational operations and visualizations
• Scikit-learn for machine learning model implementation
• Streamlit for creating an interactive dashboard UI

Challenges We Faced

The main challenge was understanding Gate Group’s business model in a short time frame. Since we had only theoretical knowledge of machine learning and data analysis, adapting that knowledge to a real-world context required creativity and rapid learning.

Accomplishments We're Proud Of

We’re proud to have developed a fully functional and valuable suite in such a limited timeframe, capable of simulating real operational scenarios.

What We Learned

• Gained insights into how Gate Group’s operations function
• Learned to implement and fine-tune machine learning models
• Strengthened our ability to collaborate effectively under time pressure

What's Next for GateAI

• Integrate IoT sensors to achieve more accurate monitoring
• Retrain ML models with real data, since the initial datasets were limited and partially synthetic
• Migrate the UI to a fully web-based experience
• Consolidate all tools into a single integrated platform

Built With

• ai
• analytics
• api
• data-science
• kpi-dashboard
• machine-learning
• numpy
• pandas
• polars
• python