OASEES – Open autonomous programmable cloud apps & smart sensors

Open autonomous programmable cloud apps & smart sensors

The OASEES project will deliver a European, fully open-source, decentralized, and secure Swarm programmability framework for edge devices and leveraging various AI/ML accelerators (FPGAs, SNNs, Quantum) while supporting a privacy-preserving Object ID federation process.

Use Cases:

01.

e-Health

The outcome of this pilot will be an intelligent edge device capable of sensing, recording and analysing patients’ utterances, as well as providing smart, adaptive and personalised guidance on rhythm and intonation. The system will usable both in rehabilitation centres during sessions with therapists and at home. We will adopt a privacy-by-design approach when collecting and treating patients’ acoustic data

02.

Energy

The real-field pilot will demonstrate the capability of deploying and coordinating in a scalable yet near the real-time way the operation and management of swarms of IoT-based devices (e-vehicles), which will be coordinated and programmed through the OASEES SDK and orchestration platform.

03.

Drone Swarm for area and infrastructure inspection

Autonomous drone inspections provide tower companies with data and insights to expand their infrastructure by gathering high-resolution aerial data, generating accurate 3D models and a 360-degree panoramic view of a potential antennae location. It helps to identify potential obstructions, establish the distance from nearby existing antennae, and acquire local permits easily. It also enables tower companies to adapt their existing site to the 5G network needs in urban environments.

04.

Structural Safety for Building and Critical Infrastructure

The structural condition of critical infrastructures is inferred by processing data from local sensors, SENSO operates a decision support software that collects this structural data and helps in decision-making during critical times. Currently, the collection of sensor data takes place on customer’s premises, but it is inefficient and causes data privacy concerns and increased response time. A distributed DSS architecture, with components at the edge and the central cloud, would be more beneficial.

05.

Collaborative robotic automation

This use case investigates the application of a finishing machine in the context of medium and large-scale industrial operations. The machine is specifically designed to meet the demands of companies that prioritize high-quality sanding and finishing outcomes. The study takes into consideration the ongoing transformation of the furniture market, which is shifting from mass production to a more customized approach characterized by small batch production and even single piece fabrication. The research highlights the machine’s ability to enhance the thermal properties of treated wood materials.

06.

Wind Energy

Blockchain can be used in the distribution and operation of IoT networks as a target for DAO paradigms, providing a backend for distributed data structures to securely store transactions in a decentralized manner. Smart metering is a key enabler for integrating smart energy renewable systems to existing infrastructure. In the OASEES project, novel IoT-based meters will be implemented to support on-the-fly programmability, using IoT sound transducer (microphones) applied to wind turbines

Our motive

The need for a comprehensive and open solution for edge processing

Recent developments in edge computing have led to the emergence of various infrastructure and service management platforms, including open-source options. However, to fully realize the potential of edge processing, a holistic solution incorporating central infrastructures and smart devices is required. Despite the distributed and heterogeneous nature of cloud computing, there is a lack of open management frameworks. Existing solutions, such as hybrid core/edge management offerings, are limited in scope and are not suitable for private deployments. Accessibility is a crucial aspect for researchers, thus, user-friendly interfaces for data management and ML/AI algorithm selection and optimization are necessary. Unfortunately, these are currently lacking in edge orchestration solutions.

The OASEES project aims to create a new programmability framework that will allow edge devices to work together in a decentralized and secure way, using advanced technologies such as AI/ML accelerators (FPGAs, SNNs, Quantum) and a privacy-preserving Object ID federation process. This framework will be fully open-source and developed specifically for Europe.