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 85-96 of 176 articles

Using blockchain for carbon credit verification in sustainable supply chains

Stratospheric aerosol injection calibration for regional climate stabilization by 2035

Bridging sonar technology with bat echolocation for underwater navigation in autonomous submarines

Designing attojoule-scale neural networks using superconducting spin wave interferometry

Employing AI-optimized renewable grids for stabilizing microgrids during solar storms

Deploying blockchain-verified carbon credit systems for rainforest conservation with real-time satellite monitoring

Through morphological computation for adaptive soft robot locomotion in rough terrain

Autonomous methane detection drones for pinpointing landfill emissions with AI-driven analytics

Employing soft robot control policies for adaptive deep-ocean carbon sequestration

Using autonomous methane detection drones for precision agriculture emissions monitoring

Accelerating coral reef restoration through electro-accretion and AI-driven monitoring

Sim-to-real transfer for training autonomous drones in extreme weather conditions