Smart resource management

Europe loses 25% of its water supply to leaks. Although 1 billion m³ of treated wastewater is reused annually, 6 billion more could be saved and utilised. COSMIC will develop AI-driven solutions for water treatment plants to improve efficiency and sustainability. 

Flood risk mapping for fair insuranceFighting energy poverty in social housingSizing an energy-storage system for on- shore power supplyEnergy sustainability indicators basedon waste separationLeak detection inbiomass district heatingEnergy optimisation anddecarbonisation of wastewatertreatment plantsUrban cooling system using rainwaterSustainable management of a renewable energy communityPredictive maintenance of PV plantsSustainableresidential buildingsTertiary-use buildings (schools)Industrial energy communitiesEfficient usage of heat pumpsRenewable energy communityPrivate housing in multi-family buildings

Pilots are real-world testbeds where Core technologies and AI innovations are combined to develop and validate scalable energy solutions.

A part in the city with a lot of water

Image from pexels.com by Nancy Bourque

Pilot location in Spain 

This pilot builds on the Urban LABCartujaQanat and in the LIFEWATERCOOL facilities innovations to create an integrated system for managing energy, water, and thermal comfort in a primary school, using photovoltaic power, heat pumps, and rainwater harvesting to enhance climate resilience and ensure sustainability in the face of floods, droughts, and heatwaves. 

Core technologies:

  1. Data Standardisation and Preparation
  2. Energy‑Grid Optimisation Microservices
  3. High Performance Computing- based multi-fidelity and physics design of resilient built environment

AI solutions from Third Parties: 

  • Materials resilience models 

  • Urban elements, Nature based and Biodiversity solutions for the urban environment models for simulations 

  • Climate-risk valuation methods for buildings 

  • Vegetation resilience models 

  • Irrigation models 

Problem addressed: Lack of efficient, sustainable cooling systems in public spaces 

Expected outcomes: Demonstration of an integrated district system for energy, water and climate control, Creation of a smart, rule-based urban control system 

WWTP

Image from pixabay.com by jarmoluk

Pilot location in Spain 

This pilot aims to optimise wastewater treatment plant (WWTP) operations by using AI-based forecasting and control to reduce energy use, costs, and emissions, while increasing the integration of renewable energy sources like biogas and PV for smarter, more flexible plant management.

Core technologies:

  1. Data Standardisation and Preparation
  2. Big Data Analytics Framework
  3. Energy‑Grid Optimisation Microservices
  4. RECreation platform for managing Renewable Energy Communities

AI solutions from Third Parties: 

  • Digital twin for energy management 

  • Data-driven forecasting models 

  • Multi-parameter energy optimisation solutions   

  • Predictive control solutions 

Problem addressed: High energy consumption and limited integration of renewables that WWTPs are facing 

Expected outcomes: Improved environmental and operational sustainability of wastewater treatment, A replicable smart energy management model for WWTPs that boosts resilience and promotes integration of renewables

Woot for biomass heating

Image from pexels.com by Faraz Ahmad

Pilot location in Finland 

This pilot aims to optimise district heating through AI-driven leak detection, demand forecasting, and integration of thermal storage, enhancing energy efficiency, reducing costs, and setting a precedent for smart heating in cold-climate cities. 

Core technologies:

  1. Data Standardisation and Preparation
  2. Big Data Analytics Framework
  3. Energy‑Grid Optimisation Microservices
  4. RECreation platform for managing Renewable Energy Communities

AI solutions from Third Parties: 

  • Predictive algorithms and software coding 

  • Generative AI tools 

Problem addressed: Undetected heat leaks and inefficient energy use in district heating networks leading to higher operational costs, increased emissions and energy waste 

Expected outcomes: Improved energy efficiency and system reliability through the deployment of AI-powered tools, Scalable AI-driven heat demand forecasting and optimisation models that can support the smart integration of thermal storage and renewable resources 

EXPLORE ALL COSMIC PILOTS