OASEES aims to create a decentralized intelligent edge framework for swarm architectures and improve swarm-edge capabilities by leveraging a Decentralized Autonomous Organization (dao).
By leveraging the dao paradigm, the OASEES aims to ensure transparent and decentralized decision-making, manage interactions and transactions within the ecosystem, and enable seamless monetization of Machine Learning (ML) models or data through ERC-based (erc20, erc721) tokenization.
OASEES presents a modular-based architecture composed of several layers, notably the Infrastructure_Layer, Service_Layer leveraging Decentralized Application (DAPP), Identity_Layer relying entirely on Self-Sovereign Identity (SSI) Paradigm, and Programming_Layer enables new development-based on data availability and services provided by OASEES.
OASEES portal enables users to explore the Machine Learning (ML) models in a decentralized environment and potentially collaborate (use existing models or data and/or propose new models based on data availability) to improve swarm-edge capabilities in Health, Energy (e-vehicles), Drone Swarm for area and infrastructure inspection, Structural safety for buildings, Manufacturing via collaborative robotic automation, and Wind Turbine Maintenance (Wind Energy).
Credits to Akis Kourtis, PhD, for excellent coordination and deep acknowledgment to all team members involved in the project for their hard-working spirit.
The mid-term review for the OASEES project.
