Improving the resilience of industrial supply systems through the application of Artificial Intelligence.

Implementation period

January 2022 to August 2022

Scope of work

Digital technology: Internet of Things and Machine Learning

Digitalization and efficiency of processes in the industry.


ACLIMA https://aclima.eus/
ANBIOTEK S.L https://www.anbiotek.com/
h2ï analytics SL https://hdosi.es/
SASTESA https://www.sastesa.es
University of Zaragoza https://www.unizar.es/
ZINNAE https://zinnae.org/


This project has been funded by the national programme for clusters support “Ayudas a Agrupaciones Empresariales Innovadoras” (AEIs) of the Ministry of Industry, Trade and Tourism. Recovery, Transformation and Resilience Plan – Funded by the European Union – NextGenerationEU.


The challenge addressed by the project is to provide the industry with a tool to internalise water risk in its strategic intelligence as a key element to improve its resilience to disruptive events in water resources management.
The opportunity for this comes primarily from three emerging aspects of BIG DAT technologies:

  • The digitisation of the water cycle in the industry, extending and reinforcing it in the raw water harvesting aspects (IoT).
  • The incorporation of open government data from the networks of water quantity and quality control officers.
  • Advanced data analysis using Artificial Intelligence tools.


The project’s overall objective is to improve the resilience of industry supply systems in both quantity and quality, improving water security levels in the face of structural water scarcity and drought events by using AI and IoT.

Provide the industry with a solution for forecasting and evaluation of trend states of water availability and quality.

  • Develop a digital platform (IoT and AI techniques) for management based on sensors and indicators.
  • Establishment of water cycle indicators.
  • Management of alerts/establishment of protocols.
  • Integration of other environmental controls operated by other administrations.
  • Improve water management efficiency/improve competitiveness.
  • Improve water quality.
  • Promote the company’s strategic intelligence.


The project is closely linked to improving the water supply resilience to the industry by incorporating risk analysis to reduce uncertainty about its magnitude and the economic impact it will have on the rest of the sector’s water management value chain. RINDIA addresses the risk aspects of the catchment, the first element and the cornerstone of the entire supply system.

In this context, the proposed solution includes implementing a digital platform that integrates Artificial Intelligence (AI) algorithms and Internet of Things (IoT) technology for monitoring and predicting water availability and quality parameters.