HeatSpace | Devpost

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Optimizing Indoor Heating with Smart Algorithms and AI

Inspiration Heating inefficiencies waste energy and increase costs. Many businesses and homes suffer from poor heat distribution, leading to cold spots, excessive power usage, and discomfort.

What if we could analyze and optimize heating systems using AI and computational modeling?

HeatSpace is a smart heat optimization system that intelligently analyzes floor plans, simulates heat propagation, and recommends heater placements for maximum efficiency and comfort.

What It Does HeatSpace allows users to:

Upload a 3D Floor Plan (.usdz format) Detect cold spots using heat diffusion simulation Automatically generate optimal heater placements Visualize the heat coverage with a dynamic heatmap Adjust and fine-tune settings for improved efficiency How We Built It

Backend: Flask, NumPy, OpenCV, SciPy Frontend: Next.js (React), TailwindCSS Data Processing: USDZ to OBJ Conversion Algorithms: Heat Diffusion Simulation (Gaussian Decay Model) Optimal Heater Placement (k-D Tree + Greedy Optimization) Wall & Obstacle Detection (Computational Geometry) Why It Matters

Energy Efficiency: Reduces heating costs for homes, offices, and smart buildings Comfort Optimization: Ensures even heat distribution Sustainability: Lowers carbon footprint by minimizing wasted heat IoT & Smart Home Ready: Can integrate with smart thermostats and HVAC systems Challenges We Faced

USDZ to 2D Floor Plan Conversion – required custom 3D processing Accurate Heat Propagation Simulation – refined heat diffusion modeling Optimizing Placement for Different Room Layouts – used machine learning and computational geometry Future Enhancements

AI-Powered Adaptive Heating – dynamically adjust heat output in real-time Machine Learning for Personalized Climate Control IoT Integration with Smart Thermostats Web & Mobile App Expansion for user control