Atomfair Brainwave Hub: SciBase II / Artificial Intelligence and Machine Learning / AI-driven solutions for environmental and climate challenges

AI-driven solutions for environmental and climate challenges

Showing 121-132 of 176 articles

Marrying ethology with swarm robotics to design bio-inspired collective behaviors

Via multimodal fusion architectures for early wildfire detection using satellite and drone data

Employing spectral analysis AI to detect methane leaks in permafrost regions

Via deep-ocean carbon sequestration with autonomous robotic monitoring

Enhancing quantum radar systems with entangled microwave photon pairs for stealth detection

Optimizing ocean iron fertilization monitoring with autonomous underwater drones and satellite tracking

Through morphological computation in soft robotics for uneven terrain navigation

Quantifying microplastic transport across continental drift velocity gradients

Leveraging quantum vacuum fluctuations for ultra-precise metrology applications

Using blockchain for carbon credit verification in reforestation projects

Optimizing urban microclimate resilience through AI-driven green infrastructure placement by 2040

Optimizing urban heat island mitigation strategies for megacity-scale solutions using spectral analysis AI