MARS Success Stories

Two MARS research articles are featured in one of the most prestigious international scientific journals, Computer Networks. The paper entitled ‘A compilation of UAV applications for precision agriculture‘ with authors Panagiotis Radoglou-Grammatikis, Panagiotis Sarigiannidis, Thomas Lagkas and Ioannis Moscholios has ranked 2nd in readability (most downloaded), while the paper entitled ‘Towards smart farming: Systems, frameworks and exploitation of multiple sources‘ with authors Anastasios Lytos, Thomas Lagkas, Panagiotis Sarigiannidis, Michalis Zervakis, George Livanos is ranked 7th in the list of the 25 most popular works of the journal!

It is worth noting that the two MARS research papers are distinguished among articles from popular research domains, such as 5G and IoT, although they both focus on the same research subject, precision agriculture.

The project






Work Packages



Multi-level Innovation

Smart Farming

Smart Farming

Through the MARS project, the harmonization of the procedures followed in the Greek agricultural production with those provided by the Common Agricultural Policy in the European Union, for the implementation of Smart Agriculture, are achieved.

Precision Agriculture

Precision Agriculture

The adoption of Precision Agriculture, which is the main pillar of the project, is expected to lead to significant results for the competitiveness of agricultural products, economy, prosperity and employment in Greece.

Information & Communication Technology

Information & Communication Technology

The MARS project utilizes Information & Communication Technologies for the accurate and reliable collection of information from the field in real time, as well as for the connection of recording sources with an integrated information system.

Internet of Things (IoT)

Internet of Things (IoT)

The MARS project will result in an innovative application that falls within the area of Internet of Things, combining effective data collection and processing mechanisms, supporting data access and decision-making mechanisms.

Unmanned Aerial Vehicles

Unmanned Aerial Vehicles

In the MARS project, UAVs are one of the two data sources. They are considered to be one of the most user-friendly application technologies for Internet of Things, thanks to their ability to directly connect and exchange data with any data network.

Big Data Analysis

Big Data Analysis

They offer possibilities for risk assessment, prediction of anomalies, and classification of anomalies using thoughtful and probabilistic methods. The MARS project big data analysis for the early detection and diagnosis of disease in trees and plants.

Machine Learning

Machine Learning

The MARS project utilizes machine learning technologies to optimize the evaluation of results regarding the detection of phytopathological infestations.

Computer Vision

Computer Vision

In the MARS project, computational vision technologies are used to optimize the quality of the images received by the UAVs, as well as their classification into the categories: “vegetation areas”, “dry soil areas”, “healthy areas” and “uneven areas”.

Multispectral Imaging

Multispectral Imaging

The multispectral imaging of the surface of plants and soil at various critical stages of growth of any plant species can provide valuable information about the general condition of the plant (nutritional or water stress, soil moisture, percentage of weeds or diseases, etc.).

Work Package Structure

Work Package 1 (WP1)

Requirement Analysis & Development and Dissemination Plans

It includes the requirements setting for tree protection and plant protection, the technical specifications of the materials and software to be used in Experimental Demonstrations 5, and designing MARS Architecture. It also includes the activities required for the smooth implementation of the project, the coordination of partners, monitoring the development, the writing and submitting deliverables, the problem solving and communication with the managing authority. Finally, the plan for the commercial and financial exploitation of the project’s results as well as that of dissemination and publicity actions will be drawn up.


Work Package 2 (WP2)

Remote Sensing of Crops

It involves evaluating environmental mapping or reflection methods for approximate crop imaging based on their default texture elements. It also includes the production of 3D soil models to monitor crop growth, on the basis of a comparison between expected crop yields and past crop yields. The WP2 activity also includes digital image processing, computing and machine learning to optimize the quality of images captured by UAVs, and classify them into categories, such as: “vegetation areas”, “dryland areas”, “healthy areas” etc. .

Work Package 3 (WP3)

Support, Imaging and Evaluation of Detection Methods

This WP includes the visualization of the methods for classifying the crops and link them to Geographical Information Systems (GIS). During its development, telematic applications for the management of the MARS program are being developed and a wireless sensor network is designed to monitor physico-chemical parameters related to the cultivation process. Moreover, it includes the evaluation of methods for assessing phytopathological infections and the development and customization of machine learning techniques to classify the extracted areas of the images obtained into “vegetation areas”, “dry soil areas”, “healthy areas” and “abnormal areas”.


Work Package 4 (WP4)

System Integration and UAV Programming

This WP includes the integration and customization of all components, hardware, sensors, recorders and software within MARS Architecture to simulate the experimental demonstrations. At this stage, potential problems and dynamics of equipment and methodology to be applied to WP5 are identified and addressed.

Work Package 5 (WP5)

Demonstration Experiments and Evaluation of Results

Demonstration experiments, in the Grevena and Velvento crops, will be conducted in WP5 in order to evaluate, verify and optimize the proposed research mechanisms and techniques of plant protection and tree protection established in the WP1.




Latest News

Nέα Διάκριση

Δύο ερευνητικά άρθρα του MARS διακρίνονται σε ένα από τα πιο έγκριτα, διεθνή επιστημονικά περιοδικά, το Computer Networks. Tα δύο ερευνητικά άρθρα του MARS διακρίνονται ανάμεσα σε άρθρα που προέρχονται από πλείστους δημοφιλείς, ερευνητικούς χώρους, όπως το 5G και το IoT, παρόλο που και οι δύο εστιάζουν στο ίδιο ερευνητικό αντικείμενο, δηλαδή την γεωργία ακριβείας.


Agrotica 2020

Στις 31 Ιανουαρίου 2020, σε ημερίδα που διοργάνωσε το Διεθνές Πανεπιστήμιο Ελλάδος στα πλάισια της έκθεσης Agrotica 2020 παρουσιάστηκαν οι προκλήσεις και οι προοπτικές για τη “Γεωργία Ακριβείας” με τη χρήση drones, όπως προέκυψαν από το έργο sMart fArming with dRoneS – MARS.

Μπορείτε να δείτε την παρουσίαση στο link

Ενημερωτική Ημερίδα

Ενημερωτική Ημερίδα

Την Τρίτη 2 Ιουλίου 10:00 – 13:00 σας περιμένουμε στο Τμήμα Ηλεκτρολόγων Μηχανικών και Μηχανικών Η/Υ στην Κοζάνη (Καραμανλή & Λυγερής – Αμφιθέατρο Τμήματος) στην ενημερωτική ημερίδα που διοργανώνει η κοινοπραξία του MARS: sMart fArming with dRoneS!


Kick-off Meeting

Το Kick off Meeting θα πραγματοποιηθεί στις 5-10-2018 στη βιβλιοθήκη του τμήματος Μηχανικών Πληροφορικής και Τηλεπικοινωνιών στην Κοζάνη.

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