About The Project

Goals & Objectives

Based on the need for continuous monitoring of the environment and infrastructure in the tectonically and seismically active area of ​​the Greek “SuperSite” (Corinthian, Ionian Islands, etc.) in the collaborative project PROION will be the development of three technological prototype products (with features that are implemented for the first time) as well as their verification / characterization:


Development of multiparametric data processing algorithms using intelligent methods.


InSAR reflector (with thermal expansion / contraction control)


Electronic platform (e-platform) with code name PROION

The platform develops a methodology for combined use in real-time and near real-time of measurements by MEMS 3-axis accelerometers, differential radar image interferometry, GNSS receivers (GPS) and Laser scanners, and spatial recording of results.

Figure 1. The limits of the Greek Supersite “Enceladus”

A major part of the project will be the processing of information through intelligent data analysis methods. In recent years the methods of machine learning and deep learning data have advanced significantly in the field of data analysis. They have also enabled sciences, in which the processing of large volumes of historical data (eg in Geology) which is an integral part, to record rapid and important developments. However, data processing should not be isolated from the human factor but should be able to combine the knowledge of experts with the information that can be extracted from the data to create sophisticated and optimized decision-making tools. In this proposal, in order to be able to implement what has been briefly presented above, it is necessary to use new and advanced scientific theories. Such new theories are the methods of fuzzy cognitive networks (AGMs) which together with machine learning algorithms will be able to provide a modern tool for decision making and support for monitoring critical infrastructure.

Fuzzy Cognitive Networks (VLS) is a new and innovative method belonging to the field of computational intelligence first introduced by bart kosko in 1986 [1]. They offer the ability to deal with problems in a way similar to that of the human brain, through a process that may involve vague and ambiguous situations. In this way they offer an economical, flexible and easy way to model systems behavior. The research team of EAP of PP under the guidance of Prof. Petros Groubou continued these theories and has developed new methodologies with very good and useful results that are gaining worldwide recognition. Due to the specifics of each infrastructure (physical and / or human) it is necessary to use machine learning techniques in order to achieve the combination of users’ knowledge with the data that will be taken from the meters to ensure the best knowledge of the system and achieving the most accurate and accurate results.

In particular, the proposed platform / web application will implement:



Using special algorithms that will be developed in near real time (near real time) data merging application by MEMS 3-axis accelerometers & GPS GNSS full system and will generate movement changes and distortion


Using special algorithms that will be developed in the second near real time, notations will be generated from radar data using permanent reflectors and these results will be “calibrated (checked, calibrated, adjusted) by the results of a.

Total displacements will be monitored based on the results of laser scanners and a comprehensive map of changes, displacements and distortions will be generated. The set of methodology and the three new technological products will be a “commercially innovative product” for use in the Greek, European and global markets. This proposal is submitted by a partnership of 2 research organizations and 2 companies, which have a prominent position in both research and production of advanced systems for monitoring seismic acceleration and micro-movements of the Earth’s surface. The organization chart of a complete interdisciplinary team ensures the successful implementation of the project objectives.

For the success of the goal of developing technologically innovative and perfect products for the monitoring of infrastructure in the wider area of ​​the Greek Supersite (Figure 1), it is necessary to observe a process of understanding and reasoning of individual technologies as well as predicting qualitatively and quantitatively the data describing the behavior of both accelerometers and permanent GNSS stations as well as interferometry and laser scanning methodologies. Aiming at the adequate coverage of the needs and the smooth operation of the system but also the low cost in the continuous monitoring of the environment and the infrastructure in the “tectonically and seismically active area of ​​the Greek SuperSite”, the final interconnection of the individual elements (sensor, system GPS measurements, interferometry) with the logic of creating a complete system and meeting the needs of the user. This research proposal is fully in line with the Sendai Framework for Disaster Risk Reduction. In particular, it focuses on three of the seven key objectives of the framework and in particular on reducing potential damage to critical installations, reducing the number of people affected by a disaster, and reducing the cost of potential damage.

The project was implemented within the framework of the RESEARCH – CREATE – INNOVATE action and was co-financed by the European Regional Development Fund of the European Union and national resources through the EP. Competitiveness, Entrepreneurship & Innovation (EPANEK) (project code: T2EDK-02396)

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