Research & Development

Research and Development for a Sustainable Future

Our vision is to advance with Innovative Solutions day by day, investing in our team, our collaborators and in new complex projects aimed to face Climate Change challenges.

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Improving crop yields and resilience sustainably.

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Revolutionize aquaculture with sustainable solutions for success.

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Water Management

Developing innovative solutions to water challenges

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Tech Innovations

Discover groundbreaking tech innovations shaping the future

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Research and Development for a Sustainable Future

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IRRIGOPTIMAL® is an integrated solution designed with the support of a qualified team of agronomists, developed and patented by WES TRADE. The solution is made up of grounded sensors, meteorological services, a centralised software based on Artificial Intelligence and Machine Learning algorithms and can predict the optimum water irrigation needs for the next three days, thereby avoiding water loss and damage to the quality of the crops, while monitoring the crops in real time and providing a valuable Decision Support to prevent possible disease or recommend specific actions along the irrigation network (fertilisation/irrigation, etc..), monitoring and providing early alerts and remedy actions on possible diseases and insect detection tools.

IRRIGOPTIMAL® was born with the idea of responding to one of the many problems deriving from climate change, namely the scarcity of water in agriculture. Water-use reduction and water distribution management - The limited natural availability of water is a significant restriction on the productivity of the agricultural sector. Effective and efficient management of available water resources is therefore essential.

Through IRRIGOPTIMAL® we intend to reach the following goals:

  • Creation of a new integrated model driven by data and based on a Decision Support module for crop analysis.
  • Optimization of product yield, improvement in quality and damage minimization (minor probability of disease, less fertilizer, less pesticides).
  • Economic Savings - By optimizing the use of water, farmers can now realize the savings based on the reduced water and energy bills, fertilizers and pesticides. This allows farmers to maximise profits and can create a useful pathway for operational and capital reinvestment.
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  • IRRIGOPTIMAL Suite: it is a centralised Web Application hosted at WES TRADE servers where it deploys the core software solution implementing several modules including the Water Plan Prediction, Crop Monitoring, Decision Support and Disease Modules. This is the Artificial Intelligence core engine where all information incoming from a network of sensors and external services are merged, analysed and used for prediction purposes. This suite provides an extensive variety of graphs and reports to fully monitor the farms.
  • Network of Sensors: there are several sensors used to collect in-situ data useful for the prediction model. The sensors include grounded data loggers, meteorological stations and other sensors which are connected to the IRRIGOPTIMAL suite through sim cards.
  • Mobile App: it is a user-friendly app for the farmers containing only limited and useful information for operating irrigation with the saving plan. The online desktop version can be used by agronomists to conduct more detailed and extensive research. The IRRIGOPTIMAL suite has been designed and implemented in a way to easily operate through web-services to external applications if needed.
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IRRIGOPTIMAL works for several categories of crops:

leafy crops (lettuce, spinach, cabbage, water cress, kale, etc.)

fruiting crops (cucumber, eggplant, watermelon, melon, strawberries, beans, bell peppers, tomato, etc.)

fruiting trees (citrus, grapes, apples, peach, almond, apricot, plum, banana, kiwi, mango, pistachio, walnut, cherry, etc.)

tuberous and bulbous crops (potato, sweet potato, cassava, yam, carrot, artichoke, onions, garlic, kohlrabi, etc.)

grains (wheat, barley, oat, rye, triticale, corn, etc.)

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SOLEATECH project is targeted to carry on technological research to improve productivity, efficiency and the sustainability of the Mediterranean olive trees farming systems in rural areas through the development of tools and knowledge to enhance resilience addressing challenges of water, soil and energy introduced by the Climate Change.

Our research aspires to create new sustainable ways in managing the soil, preventing yield losses and enhancing food quality through the development of integrated soil data correlations for the Mediterranean regions identified and monitored by an Artificial Intelligence algorithm. SOLEATECH will be carried on by Turkish Bahcesehir University and the Maltese company WES TRADE in continuity with the already existing collaboration agreement in place among the parties and the current activities already in place in the application of Artificial Intelligence to Agriculture like WES TRADE’s IRRIGOPTIMAL solution installed in Turkey as part of PRIMA TRAINING and MOBILITY program.

SOLEATECH has been funded under the PRIMA MCST-TUBITAK Program last October and will focus its research on the optimization of olive trees cultivations; in fact, in the previous years both fruitification and quality of the olive oil have dropped by far, causing great damage to the local agricultural economy.

SOLEATECH aims to achieve the following objectives:

  • Integration of already consolidated studies, research, and tools to create an innovative Predictive Model based on Artificial Intelligence techniques to improve olive tree cultivation.
  • Identify correlations between environmental factors (soil, climate change impacts, irrigation) with crop productivity and quality.
  • Introduce Early Alerts to farmers to intervene on environmental factors to improve yield productivity while reducing the usage of pesticides, optimizing natural resources available (green approach), and reducing poorly calibrated economic practices that could induce pathogenesis in the plants themselves.
  • Implement and strengthen a Knowledge Transfer between research entities that have already developed complimentary studies and collaborated to improve precision agriculture in the Mediterranean area.
  • Involve respective Ministry of Agriculture (as both entities have collaborations in place with their correspondent national one) in the results disseminating achievements and solutions.
  • Create a model which could be fast developed and integrated in already available respective platforms to quickly reach final users with a concrete solution.


Water Management Research Initiatives


MARINA is a short-term Research Project financed by the Malta Council for Science and Technology (MCST) under the Research and Excellence program 2023.

Tuna fish farms is the largest fish farming system in Malta and recent studies have focused on the improvement of fish farm production efficiency, the effects of Climate Change on fish farming in the region, the use of new technologies to improve fish welfare and feed utilization.

The observation of fish behaviour as indicator of stress may be a valid element to prevent situations where water quality, especially compromised on open sea by microplastics may threaten tuna fish welfare and production efficiency. It has been scientifically proven that behaviour represents a reaction to the environment as fish perceive it and therefore is a key element of fish welfare. In a developing and increasingly competitive aquaculture industry, it is of paramount importance that both farmers and researchers use species-specific behavioural signals for an early assessment of poor fish welfare.

MARINA Research will focus on the design and implementation of a Machine Learning algorithm able to predict conditions where tuna fish productivity may be impacted by factors that are cause of stress for fish using in-situ data collected by IoT sensors covering water quality, presence of microplastics and observation of fish behaviour including symptoms of fish stress.

The research shall identify correlations that may alert farmers about risks in their tuna fish productivity. The research will be carried on a live lab on open sea for the measurements of data and observations when tuna cultivations is active.

Project started last August from TRL 1 and MARINA research will target it to TRL 4 and will provide an excellent basis for the realization of an integrated system to be tested on a real scenario for higher TRLs.

Water Management

Water Management Research & Development Initiatives



BLUE DROP is an R&D project co-financed by MALTA ENTERPRISE and lead by WES TRADE LTD in collaboration with the Malta College of Arts Science and Technologies (MCAST) and KORE University of ENNA. In 2020, WEST has been awarded by Malta Enterprise financing for R&D feasibility study for BLUE DROP Project focused on the Linkages between Water Distribution Pressure Transients, Water Consumption Profiles and Water Meter Performance leading to Apparent Water Losses and its possible application to technological systems/products to improve the water performance and reduce water losses. The follow-up R&D Project was recently awarded for a three-year experimentation with the support of Water Service Corporation (WSC).

Blue Drop to analyse Apparent Water Losses and Water Balance Confirmations

Apparent Water Losses (AWL) are a major source of revenue loss by water utilities and the governments that fund these utilities, with the water consumer ultimately paying the price due to resulting tariff hikes that are implemented to recuperate these losses.

The research in question shall carry out a very detailed study of Apparent Water Losses in both physical mode and in complementary simulated mode, with an aim of closely studying some three pilot zones with highly accurate instrumentation and data resolution, and then repeating and studying these values in a simulated environment. The project shall be implemented over a three-year period to allow for adequate longitudinal depth.

The main objective of the Blue Drop application is to simulate, predict and give results of water distribution network, based on algorithm deigned by Kore which is able to include presence of water tanks and transient pressure variability. One of the project challenges is develops a specific model able to identify possible apparent water losses and investigate on the effect of flow and pressure fluctuations on AWL.

Project deliverable is complete water distribution network simulation, presented in a graphical and numerical way, for each network component, providing better understanding of flow and pressure variability. User will have clear visualization in context of time and pressure oscillation, that causes water meter to lose their accuracy over time. Also, high pressure can indicate for potential burst or leakage in network. Such events can cause mass water loss and even more financial damage.


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Tech Innovations

Where Innovation Meets Research and Development



DIEM (Distributed Ledger Technology: Innovation and Ecosystem Management) Doctoral Network Project is an approved Horizon Marie Curie Project.

DIEM Consortium bring together academic, government and industry expertise to holistically investigate the managerial, economic and societal implications of Blockchain Technology.

DIEM is a Doctoral Network (Industrial Doctorates) that creates a platform for researchers to engage in the co-production of knowledge by investigating state-of-the-art challenges and societal implications of Blockchain technology across actors and industry boundaries.

The Project has officially kicked-off last April at the Vrije Universiteit of Amsterdam. DIEM will shape the future by training innovative and resilient doctoral candidates, who will be equipped to transform knowledge and ideas into real-world products and services for the benefits of our society.

DIEM focuses on 12 research areas, each hosting individual PhD projects, all interlinked and complimentary. The ultimate goal is to build an international network of interdisciplinary scholars, organizations and institutions across sectors, all driven by a common goal: Pushing the boundaries of DLT innovation.

DIEM Consortium consists of:

  • Vrije Universiteit Amsterdam (VU)
  • Durham University
  • Norwegian University of Science and Technology (NTNU)
  • IE University
  • Accenture
  • Hellenic Ministry of Digital Governance
  • WES Trade Ltd
  • CRH Nederland BV
  • Helixconnect Europe
  • Kielce Technology Park
  • YET

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