The hydrogen landscape is highly fragmented. It consists of many silos, each focused on their own problems, but not communicating. There is production, with a myriad of colors of the rainbow of the different types of hydrogen that exist today. There is storage and transportation, which could easily eclipse the cost of production if not properly managed.
Next comes the myriad of use cases and applications – so why will hydrogen be the best solution in all of these circumstances? How will demand curves and resulting pricing curves dictate broader adoption?
Last but not least is the influence of legal, regulatory, and governmental impacts. How will the actions of governments around the globe either accelerate or impede the adoption of hydrogen?
Complex Interacting Processes and Systems in the Hydrogen Ecosystem
WHY Multi-Modal, Trust-Assured AI?
For any complex group of interacting processes and systems generating data, we seek to do four things:
Faciliate
Facilitate and incentivize public-private data exchange across silos while maintaining ownership rights and ensuring validity, security and transparency.
Understand
Generate correlations, find cause and effect relationships, and develop insights, as well as operational models of interacting processes and systems. We will train our AI Models using proprietary data, hydrogen specific.
Optimize
Multi-objective, multi-parameter optimization using operational models.
Control Find anolomalies, adjust process and system parameters to eliminate them.
Contact Info@H2AI.Tech Headquarter located at 705 Cambridge St., Cambridge, MA 02141
