24 Thousand Data Points, 2 Thousand Images & !7 Senosrs
Agent Based Learning with Dense Spatial Data
Geo-Thermal Insights through Urban Heat Maps
Interaction with Virtual Environment
Integrated with solar charging capabilities, it brings unparalleled versatility. With seamless connectivity and precise spatial data collection, these sensors not only enhance the accuracy of our urban heat analysis and prediction models but also operate sustainably by utilizing solar charging while being battery-powered.
AI Aware aims to model relationships among vegetation, built environment, and anthropogenic activity to map sustainable urban environment. This tool will use machine learning and AI to provides real-time data analytics from a network of IoT devices, for policy makers and researchers, enabling them to understand how urban turbulent and radiant heat fluxes travel in a built environment.
Our Vision
Minimizing the effect of Turbulent and Radian
Heat in Built Environments
At AI Aware, we envision a cityscape where sustainability and comfort coexist seamlessly. Our mission is to revolutionize urban planning through advanced technology, modeling intricate relationships among vegetation, structures, and human activity. Harnessing the power of machine learning and AI, we provide real-time analytics, empowering decision-makers to understand and mitigate the impact of turbulent and radiant heat in built environments.
Beyond data analytics, our vision extends to making a tangible impact on society. In cities like Karachi, where heatwaves pose health crises, AI Aware emerges as a crucial tool. Imagine a future where emergencies related to heatwaves are minimized through proactive planning, all facilitated by insights from our innovative model.
Our Features
AI Aware is structured into distinct components, covering aspects such as sensor data acquisition, GPS coordinate retrieval, and seamless communication with the server, collectively forming a robust system for predicting, mapping and analyzing, urban environmental conditions.
Stationary devices capturing real-time thermal data for precise urban heat mapping.
On-the-go device capturing and geo-tagging thermal data for model training.
Dynamic system collecting, storing, and forwarding data for immediate insights.
Algorithms forecasting temperature trends to enhance urban planning and mitigate the impact of heat on built environments.
Physical representations and interactive visualizations of geographic data, fostering a deeper understanding of diverse landscapes.
Creating virtual replicas of physical environments, enabling immersive and enhanced decision-making and analysis.