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 61-72 of 176 articles

Through magnetic pole reversal impacts on global avian migration patterns

Using autonomous methane detection drones for precision landfill emissions monitoring

Calibrating stratospheric aerosol injection for precise climate intervention

Monitoring ocean iron fertilization impacts with autonomous underwater drones

Targeting plastic-eating enzymes through directed evolution and computational protein design

Employing spectral analysis AI for real-time monitoring of atmospheric methane leaks

Using blockchain for carbon credit verification with IoT-based emission tracking

Embodied active learning during last glacial maximum conditions simulation

Anticipating 2080 population peaks and their impact on global resource distribution

Blockchain-based carbon credit verification with emphasis on interdisciplinary approaches for fraud prevention

For stratospheric aerosol injection calibration using unconventional methodologies

Marrying ethology with swarm robotics to model collective predator-prey dynamics