Partners: Chair of Energy Efficient Systems, Department of Information Systems, University of Bamberg,  Athena Research CenterAmphiro AGFraunhofer ISIWaterwise, Aguas de Alicante


Funded by: European Commission


Principal investigators:   Anna Kupfer, Samuel Schöb


Budget: EUR 3’202’288


Timeframe: Mar 2014 – Aug 2017


Research questions: Ubiquitous sensing and data analytics to understand and positively influence personal hot water consumption.





Efficient water management is a challenging issue with the potential to affect the longterm well-being, economy and security of society. Policies for sustainable water management have been established in the EU. However measures to support efficient water use for citizens are currently lacking. Consumers have limited means to accurately monitor their water consumption and thus stimuli to modify their behaviour towards a sustainable lifestyle.
A potentially groundbreaking approach for efficient water use and reuse lies within the empowerment of consumers. The principles of open knowledge and participation have provided solutions and driven innovation in similar challenging and complex issues. We believe that a similar bottom up method, in which citizens can voluntarily adopt low cost water monitoring services, self-induce behavioural changes, and accordingly demand better services, can be a catalyst for large-scale changes in efficient water management.
The DAIAD project constitutes an innovative approach for addressing the challenge of efficient water management through real-time knowledge of residential water consumption, bringing together leading members of the water and ICT domains. Our goal is to research and develop innovative low cost, inclusive technologies for real-time, high granularity water monitoring and knowledge extraction. We will devise multi-modal feedback interfaces, recommendation, and analysis services to communicate knowledge and incur behavioural changes to consumers in residential settings. We will apply big data management and analysis technologies to provide efficient management and analysis of real-time water consumption data, as well as multiple relevant data sources. This will enable water stakeholders to gain novel insight and explore the hidden correlations of the parameters that shape water demand strategies and water pricing, thus leading to more efficient water management.