Acoustic Analysis
IBM-donated AI software examines acoustic variance in the field. Researchers observed that bee wing frequencies inside hives closely resemble wave frequency patterns produced by Tokamak Fusion Research at Stanford SLAC.
From Uganda’s national sensor network to beehives and mussel beds, each project adds a layer to a multi-layered neurology for the planet, joined with satellites and atmospheric, water-quality and underground sensors. Together they reveal climate patterns, lead to new discoveries and corrective action, and deepen our understanding of humanity’s role in preserving our environment.
Real, government-backed deployments of the Enterprise Neurosystem architecture, built with national ministries, research institutions, and local communities.
A GenAI-to-GenAI communications protocol, born from the Enterprise Neurosystem community and now adopted by ECMA as a global standard.
Earlier & ongoing
We anticipate deploying hundreds of non-intrusive sensor networks across a multitude of species in nature — forests and fungi, ant colonies, beehives, mussels, birds, kelp, coral reefs, and more.
IBM-donated AI software examines acoustic variance in the field. Researchers observed that bee wing frequencies inside hives closely resemble wave frequency patterns produced by Tokamak Fusion Research at Stanford SLAC.
US bee populations decline roughly 45% annually. Multi-function sensors detect ultrasonic signals, pollutants, and gas levels inside hives, running on AI Acoustics software donated freely by IBM Research.
Underground fungal networks that support plant ecosystems display electrical patterns that may be akin to morse code, and could potentially represent a form of communication.
In collaboration with JPL, academic and industry researchers analyze ocean pollutants, beach plastics, methane plumes, and mass changes with coverage ranging from 9×9 meter to 200×200 mile spans.
Led by engineers from Verizon and other telecom firms, this project develops AI-enhanced 5G/6G frameworks for remote data transmission.
The community explores leveraging MEG research patterns for field architecture applications in both AI and network communications.