Summary
- Closed for EoI
- Profile Type
- Research & Development Request
- POD Reference
- RDRTR20240609002
- Term of Validity
- 9 June 2024 - 9 June 2025
- Company's Country
- Turkey
- Type of partnership
- Research and development cooperation agreement
- Targeted Countries
- All countries
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General information
- Short Summary
- The main purpose of this project is to quickly detect water pollution through autonomous drones, to make it predictable with artificial intelligence technologies, to produce nature-friendly solutions to these pollutions and, in addition to our own work, to train new enterpreneurs that will enable the development of approached based on innovative and research for pollution detection/pollution removal, which is an important class of blue economy.
- Full Description
- Within the scope of the project, autonomous drones equipped with high-resolution thermal cameras will be used to detect water pollution, marine debris, plastic/microplastic ratio in coastal and inland areas in 3 different pilot regions in the Black Sea. Image processing and machine learning algorithm technologies will be developed at this stage. The images to be obtained from autonomous drones will be interpreted to train artificial intelligence using image processing techniques. In addition, a system that can bring the sample to the shore for analysis from polluted area with a sampling chamber integrated into the autonomous drone will be developed. The artificial intelligence to be developed. This system will be continuously trained with laboratory data to predict areas with high water pollution and perform flight optimization and routing. Various parameters related to seawater quality (such as temperature, pH, dissolved oxygen, total dissolved matter, nitrate, chlorophyll-A, lead, coliform) will be measured in the laboratory. In this way, pollution areas on the seawater surface will be identified and an inventory will be created. A continuously improving artificial intelligence will be created with parameters that are very important for determining seawater quality and pollution levels. At this stage, data preprocessing, feature selection, model building and neural network training will be performed, while deep learning techniques, especially Convolutional Neural Networks (CNN) and Long Short-Term Memory Networks (LSTM) models, will be used to analyze complex relationships. The trained model will make predictions about the rate and cause of water pollution in the monitored area during the flight of autonomous drones. Genetic algorithms will be developed for the optimization of artificial intelligence. Briefly, the project will develop an artificial intelligence-based decision support and pollution monitoring system using remote sensing and IoT technologies. The data to be obtained with the developed system will be used to reduce both current and future pollution and to develop new solutions. In the first study for this solution proposal, it is aimed to grow Azola plant. The usability of the grown plant in the removal of pollutants such as heavy metals, nitrate, nitrogen, oil wastes, oil wastes will be examined. In another study, various nanomaterials (such as nanoparticles, nanoflowers, magnetic nanoparticles) with low cost, low toxic effect and high yield rate will be produced from organic wastes and growing plants in the region/proteins/enzymes by using green synthesis methods. The usability of the produced nanomaterials in environmental improvement studies with 3 different methods will be investigated. The usability of directly produced nanomaterials in environmental remediation studies will be investigated. In the second study, it is aimed to develop a nanomaterial+microorganism, that microorganism is found in the basin. In the third study, it is aimed to prevent pollution by integrating nano materials into various filtration systems. Due to the low number of waste treatment systems in the Black Sea and the high rate of mixing of industrial and domestic wastes into the Black Sea by means of rivers and rivers, the usability of the nano materials in industrial scale water pollution reduction studies will be examined. Adsorption modeling, thermodynamic and kinetic studies of the results obtained in these studies will be carried out. In addition to the our solution proposals, entrepreneurs with ideas for the removal of water pollution will be trained in order to bring new solution proposals. A hub named 'EnviromenTech' will be established. Entrepreneurs will be trained by providing relevant general and technical trainings. A technical infrastructure will be created for entrepreneurs to complete their prototyping processes and an environment that they can use free of charge will be provided.
- Advantages and Innovations
- Advantages: - Enabling the rapid detection of water pollution, marine debris and microplastics/plastics with remote sensing technologies, - Remote sensing technologies enable the detection of marine pollution in invisible and hard-to-reach areas, - Due to the rapid and widespread spread of marine pollution, it significantly reduces the time factor in combating pollution and enables rapid intervention, - Autonomous drones provide energy efficiency and bring IoT base solution - Within the scope of the project, examining the curative effects of Azola plant on water pollution in salty water. In the light of the positive results to be obtained, this method has the potential to be a natural and effective method that will not disrupt the ecosystem, - Development of effective, high efficiency, low cost, environmentally friendly materials and parallel methods for the removal of seawater pollution by immobilization of nanomaterials to free, microorganisms and membranes - Establishing the first and only entrepreneurship center in Turkey for environmental improvement and detection of environmental pollution and increasing the know-how of the structure only in environmental pollution Innovations: - Long-term analysis of seawater parameter data obtained by remote sensing technologies and traditional means using artificial intelligence algorithms - Analyzing the changes in the analysis results throughout the year, - Predicting future pollution based only on the image - The use of azola plant, which is mainly used in freshwater remediation studies, in the removal of pollutants in the cardeniz basin, - Production of new, low-cost, high-yield nanomaterials with commercialization potential - Realization of nanomaterial + microorganism immobilization that can be used effectively in environmental improvements that will not disturb the ecological balance - Establishment of the first and only entrepreneurship center for environmental improvement and detection of environmental pollution.
- Stage of Development
- Under development
- Sustainable Development Goals
- Goal 11: Sustainable Cities and Communities
- Goal 7: Affordable and Clean Energy
- Goal 6: Clean Water and Sanitation
- Goal 14: Life Below Water
- IPR description
-
- Image Processing - Artificial intelligence and machine learning - Drone operator - Data scientist - Optimization of drone - Nanomaterial synthesis - Environmental improvement works - Plant cultivation - Propagation of microorganisms
- Data collection for training artificial intelligence - Completion of data pre-processing - Delivering only useful data to the AI developed in TR - Detection and elimination of data anomalies
(Eligible regions listed below:
Romania: South-East region
Greece: Kentriki Makedonia and Anatoliki Makedonia Throki regions
Georgia: The whole country
Armenia: The whole country
Bulgaria: Severoiztochen and Yugoiztochen regions)
Partner Sought
- Expected Role of a Partner
-
- Image Processing - Artificial intelligence and machine learning - Drone operator - Data scientist - Optimization of drone - Nanomaterial synthesis - Environmental improvement works - Plant cultivation - Propagation of microorganisms
- Data collection for training artificial intelligence - Completion of data pre-processing - Delivering only useful data to the AI developed in TR - Detection and elimination of data anomalies - Type and Size of Partner
- University
- Type of partnership
- Research and development cooperation agreement
Call details
- Framework program
- Interreg
- Call title and identifier
-
(INTERREG VI-B) NEXT Black Sea Basin Programme
- Anticipated project budget
-
1,5 Million Euro (total project)
- Coordinator required
-
No
- Deadline for EoI
- Deadline of the call
- Project duration in weeks
-
72
- Web link to the call
- https://blacksea-cbc.net/interreg-next-bsb-2021-2027/calls-for-proposals/second…
- Project title and acronym
-
An Artificial Intelligence-Based Rapid and Holistic Approach for Marine Pollution Detection and Remediation
- Interreg
Dissemination
- Technology keywords
- 01003008 - Data Processing / Data Interchange, Middleware
- 01003003 - Artificial Intelligence (AI)
- Market keywords
- 02007016 - Artificial intelligence related software
- 02007007 - Applications software
- 02007014 - Other industry specific software
- Sector Groups Involved
- Electronics
- Renewable Energy
- Digital
- Maritime Industries and Services
- Targeted countries
- All countries
Files
Black_Sea_Basin_Info_Session