Hydrobionets

Autonomous Microbiological Control of Water Quality based on Heterogeneous Self-Organized Wireless BioMEM Sensor and Actuator Networks”, 10/2011 – 09/2014.

Funded by: European Commission,  FP7 STREP ICT project #287613.

Partners: UVEG (Spain, Coordinator: B. Beferrul-Lozano), FORTH-ICS (PI: P. Tsakalides),  KTH (Sweeden), CNM (Spain), Acciona Agua (Spain), Ateknea Solutions (Hungary).

Total cost/Funding: €3,178,914/€2,350,000 (FORTH-ICS: €637.518/€478.500).

SPL Contact Person: Prof. Panagiotis Tsakalides.

Summary: Recent advances in ICT and MEMS have led to devices incorporating wireless communication, processing and storage capabilities, as well as diverse sensing and actuation functionalities in a single unit that is compact, economical, autonomous, and destined to become ubiquitous. This revolution appears in the form of dense and distributed Wireless Sensor Networks, the potential of which is enormous for various applications that are of great interest to society, including water monitoring and management in large-scale industrial plants, where microbiologic control of water quality is crucial. A basic understanding of system performance limits and the optimal design of large-scale, robust in-network practical algorithms associated with such biological signals remains far from mature.

HYDROBIONETS is motivated by the challenge of providing concrete and effective methodologies for the microbiological autonomous monitoring and decentralized control of water quality monitoring in industrial environments. Towards this direction a three fold objective is  established: (a) the distributed acquisition of spatio-temporal biological signals, including the specific design of BioMEMs sensors and their stable integration to WSN modules ; b) in-network cooperative processing and distributed intelligence to achieve essential tasks such as inference, detection, and decision-making; c) networked dense control to ensure adequate water quality, productivity, and energy efficiency of water treatment plants. The resulting integrated platform is ultimately to be deployed and evaluated in real-life industrial water treatment and desalination plants.

The role of SPL

  • Synthesis of on-node and in-network techniques that, based on systematic data collection and analysis, focus on monitoring the functionality of WSN topologies in RF-harsh environments;
  • Synthesis and implementation of sophisticated techniques for mitigating the impact of missing WSN values, featuring the principles of Matrix Completion;
  • Synthesis and implementation of sophisticated data management techniques for detecting uncertainties on measurements and triggering respective alerting mechanisms;
  • System architecture design, implementation, and deployment, covering various aspects ranging from network connectivity, to data storage, manipulation, and visualization.

 

Related Publications:

Tzagkarakis, George; Tsagkatakis, Grigorios; Alonso, Daniel; Celada, Eugenio; Asensio, Cesar; Panousopoulou, Athanasia; Tsakalides, Panagiotis; Beferull-Lozano, Baltasar, Signal and Data Processing Techniques for Industrial Cyber-Physical Systems, Rawat, Danda; Rodrigues, Joel; Stojmenovic, Ivan (Ed.): Cyber Physical Systems: From Theory to Practice, CRC Press, USA, 2015.

Savvaki, Sofia; Tsagkatakis, Grigorios; Panousopoulou, Athanasia; Tsakalides, Panagiotis, Application of Matrix Completion on Water Treatment Data, Proceedings of the 1st ACM International Workshop on Cyber-Physical Systems for Smart Water Networks, pp. 3, ACM 2015.

Tzagkarakis, George; Seliniotaki, Alexandra; Christophides, Vassilis; Tsakalides, Panagiotis, Uncertainty-Aware Sensor Data Management and Early Warning for Monitoring Industrial Infrastructures, Int. J. Monit. Surveill. Technol. Res., 2 (4), pp. 1–24, 2014, ISSN: 2166-7241.

Seliniotaki, Alexandra; Tzagkarakis, George; Christophides, Vassilis; Tsakalides, Panagiotis, Stream Correlation Monitoring for Uncertainty-aware Data Processing Systems, Information, Intelligence, Systems and Applications, IISA 2014, The 5th International Conference on, pp. 342-347, 2014.

Tsagkatakis, Grigorios; Tsakalides, Panagiotis, Dictionary Based Reconstruction and Classification of Randomly Sampled Sensor Network Data, Sensor Array and Multichannel Signal Processing Workshop (SAM), 2012 IEEE 7th, pp. 117-120, 2012, ISSN: 1551-2282.

 

 Achievements:

  • Design and implementation of the integrated WBN protocol stack, which outperforms benchmark solutions in RF-harsh environments;
  • Design, implementation, and deployment of the Hydrobionets platform at the pilot desalination plant of ACCIONA Agua;
  • Synthesis of a new data management framework for the real-time calculation of uncertainties and spatio-temporal correlations, accompanied by alerting mechanisms for early-warning and response, and their integration to visualization components (graphical user interface);
  • Evaluation of the Matrix Completion framework and distributed signal processing techniques for detection, estimation, and tracking at the exemplar of water treatment data.