Collecting and analysing large amounts of data in the Cloud-to-Edge computing continuum raises novel challenges. Processing all this data centrally in cloud data centres is not feasible anymore as transferring large amounts of data to the cloud is time-consuming, expensive, degrade performance and may raise security concerns. Therefore, novel distributed computing paradigms, such as edge and fog computing emerged to support processing data closer to its origin. However, such hyper-distributed systems require fundamentally new methods. To overcome the limitation of current centralised application management approaches, Swarmhestrate will develop a completely novel decentralised application-level orchestrator, based on the notion of self-organised interdependent Swarms. Application microservices are managed in a dynamic Orchestration Space by decentralised Orchestration Agents, governed by distributed intelligence that provides matchmaking between application requirements and resources, and supports the dynamic self-organisation of Swarms. Knowledge and trust, essential for the operation of the Orchestration Space, will be managed through blockchain-based trusted solutions using methods of Self-Sovereign Identities (SSI) and Distributed Identifiers (DID). End-to-end security of the overall system will be assured by utilising state-of-the-art cryptographic algorithms and privacy preserving data analytics. Due to the imminent complexity of the decentralised system, novel simulation approaches will be developed to test and optimise system behaviour (e.g., energy efficiency) in the early stages of development. Additionally, the simulator will be further extended into a digital twin running in parallel to the physical system and improving its behaviour with predictive feedback. The Swarmchestrate concept will be prototyped on four real-life demonstrators from the areas of flood prevention, parking space management, video analytics and a digital twin of natural habitat.

IntelWATT aims to develop innovative, cost efficient, smart separation technologies applied in energy and water intensive industries. The goal of the project is to demonstrate 3 TRL7 case studies that will achieve water preservation along with energy production and material recovery. The proposed solutions will also target at zero liquid discharge while implementing maximum water reuse. Tailor made sensors and automated decision making mechanisms will optimize the process conditions in real time. The case studies will be implemented in crucial EU and global industrial applications such as electricity production, mining and metal plating. -Case study 1:Demonstration prototype for CTBD treatment. The development of efficient, cost effective, smart solutions for water management in a thermoelectric power plant, aiming at minimization of the cooling tower blow down (>99% recovery) trough developing a pilot unit of 100 m3/day treatment capacity installed in the premise of PPC’s unit V (natural gas combined circle facility, Megalopolis, Greece) based on a closed loop, near zero liquid discharge approach. -Case study 2: Demonstration of a symbiotic concept between industries: sustainable production of energy and water. In this context, an integrated pilot unit (100 m3/day) comprised by Reverse Electrodialysis (RED) and solar powered membrane distillation (MD) systems. -Case study 3: The application of a novel, hybrid high recovery RO (HRRO) / Ion exchange (IX) resin prototype will demonstrate the recovery of valuable electrolytes and fresh water preservation in a plastic electroplating facility. The process is aiming towards recovering up to 95 % of Chromium and Copper and 50% of Nickel, while preserving 65% of fresh water. Implement smart sensor technology for online monitoring, real time process adaptation and deep learning, with customizable intelligent industrial process software module based on an agnostic protocol connectivity cloud infrastructure.