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In June 2021, Droople entered a partnership with the Embedded Systems Laboratory (ESL) at the EPFL and the ALTIS Group (Valais) to implement the joint Research and Development project WaSTeLeSS. The project is planned to run until 2023 and achieve significant water savings in buildings through an advanced monitoring system based on distributed intelligence. 

This is a result of the awarded grant made possible by Innosuisse, Switzerland Innovation together with its innovation partners from the Swiss economy and in collaboration with EPFL Tech4Impact. These funds are designed to give innovation projects a considerable boost, make them ready for market launch or allow them to embark on further development.

The ESL at the Institute of Electrical Engineering at EPFL, directed by Prof. D. Atienza, covers a wide range of research, teaching, and technology transfer activities related to the design of next-generation smart embedded systems and Internet of Things (IoT) objects.

Altis

The implementation of decentralized water monitoring frameworks at point-of-use should bring numerous benefits for property owners, managers, and tenants. It has great potential to reduce water and energy consumption. Also, it can minimize maintenance costs of sanitary hardware, heating and cooling systems, reduce CO2 emissions, and protect buildings from potential water damage thanks to water leakage localization on the last mile of the water grid.

Break-through capabilities for embedded devices with ultra-low power requirements

Droople was founded with the vision of implementing the smart grid for water. Indeed, in 2018, the United Nations World Water Development Report stated that nearly 6 billion people will suffer from clean water scarcity by 2050. To save every drop of this precious resource, Droople proposes a complete water intelligence solution at the point of use. It enables remote monitoring and conditional-based maintenance of any water-driven assets.

The WaSTeLeSS project has been set up to overcome the limitations of the currently embedded computing architectures used in water grid monitoring, where currently the sensing devices capture data from physical or chemical process and communicate them to the cloud to be processed using advanced data analysis techniques. However, no processing and analyses are done directly on the sensing devices, which limits the reaction time of the system and can imply a significant amount of energy spent on data communication to the cloud.

Therefore, the game-changing collaboration between Droople and the EPFL-ESL will advance the field of AI-enabled embedded devices with ultra-low power requirements, bringing break-through capabilities to both hardware and software layers by using edge AI computing. The introduction of the mesh sensor network architecture will enable massive synchronization of Machine Learning capabilities among the network nodes. It will also facilitate knowledge sharing among the entire mesh networks of smart sensors via federated machine learning, and a new fog computing system design.

The partners aim to tap into the many advantages offered by edge computing and federated learning. For example, by enabling a decentralized decision process and cloud autonomy of smart devices, the baseline response time of sensors can be dramatically improved in case of possible water leaks or issues on the water grid. Moreover, the communication energy between the device and the cloud can be reduced between 10 to 50 times, and the device lifetime target  can be extended up to 10 years. 

Innosuisse is the Swiss Innovation Promotion Agency and a federal entity under public law with a separate legal personality. Innosuisse’s role is to promote science-based innovation in the interests of industry and society in Switzerland.