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 145-156 of 176 articles

Via multi-modal embodiment: octopus-inspired soft robots with distributed cognition for underwater exploration

Phase-change material synapses for edge AI devices preparing for 2032 processor nodes

Using gate-all-around nanosheet transistors for ultra-low-power neuromorphic computing chips

Bridging sonar technology with bat echolocation for sub-millimeter 3D mapping in viscous fluids

Employing spectral analysis AI for real-time detection of methane leaks in pipelines

Autonomous methane detection drones for real-time emissions monitoring in megacity-scale environments

Autonomous methane detection drones for pinpointing leaks in urban natural gas infrastructure

Sparse mixture-of-experts models for predicting 2040 climate migration patterns

Using blockchain for carbon credit verification with 2025 cost reduction targets

For 2040 climate migration scenarios with collaborative robot cells

With resistive RAM for in-memory computing architectures in edge AI devices

In plant communication networks for precision agriculture disease detection