Seth Software Sp. z o.o. has received a grant from the European Union for the project “TubSensAI – Potato quality monitoring system in the process of potato storage based on identification of volatile substances and digital imaging supported by artificial intelligence.”
The aim of the project is to carry out R&D and implement an innovative system for monitoring potato quality in the storage process, based on innovative methods of monitoring volatile substances and digital imaging, which will be supported by AI and ML algorithms. The system, which uses digital imaging data and volatile substance identification data independently, will allow more effective monitoring of potato quality in storage and earlier removal from storage of potatoes affected by storage diseases.
The result of the project will be diversification of the commercial offer of Seth Software sp. z o.o. in the area of IT systems dedicated to the agri-food industry by a product innovation, resulting from the implementation of R&D work, i.e. an integrated hardware and system solution for potato quality monitoring based on identification of volatile substances and digital imaging supported by AI, aimed at potato producers and processors with their own storage facilities.
As a result of the project, the Applicant will improve its position vis-à-vis its competitors at a minimum on a national scale in the area of IT solutions for the agri-food industry.
The project plans to implement the following tasks:
- Formulation of technology concept, modeling studies, feasibility confirmation studies and development of electronic nose technology based on identification of volatile compounds in the process of potato storage (Module R&D work – industrial research)
- Studies of the volatile compound (VOC) profile of healthy and infested potatoes during storage – model studies;
- Determination by numerical methods of chemical predictors that are indicators of potato spoilage;
- Studies of changes in the VOC profile – evaluation of the effectiveness of the determined predictor(s) of potato spoilage (based on measurements made under real conditions-that is, in the storage room);
- Verification of sensor-detector system technology concept for potato spoilage predictors
- Design and testing of sensor-detector system technology for potato spoilage predictors under simulated operating conditions.
- Formulation of technology concept, modeling studies, feasibility confirmation studies and development of technology for digital imaging of potatoes during storage (Module R&D work – industrial research)
- Concept validation of a digital imaging system for potatoes;
- Model studies under simulated storage conditions of potatoes inoculated with pathogens using a hyperspectral camera. During the research, images and data will be collected to develop digital imaging technology for potatoes during storage;
- Construction of a prototype demonstrator of a digital potato imaging system;
- Development of an algorithm for determining quality parameters from potato imaging based on data acquired at the modeling stage and testing under simulated operational conditions of a storage facility.
- Development of a system for integration and harmonization of data sources from the storage facility (Module R&D work – industrial research)
- Development of a concept for an integrated system of harmonized storage data;
- Research and development of methods for data transmission, collection and storage, interoperability studies;
- Development of dashboards and research on the performance and usability of their interactive functions.
- Research in user experience optimization, user behavior analysis and business benefits;
- Research, development and validation of data filtering methods, analysis of interference elimination strategies;
- Integrating electronic nose technology and digital imaging into a storage data system;
- Development of integrated classification methods for different usage scenarios of the TubSensAI system, tuning the models produced in Task 1 and Task 2;
- Study of harmonized storage data technology under simulated operational conditions.
- Piloting the technology of an integrated system for monitoring the quality of potatoes during storage (Module R&D work – experimental development work)
- Development of the TubSensAI platform MVP version of an integrated system for monitoring potato quality during storage in a real environment;
- Pilot study of integrated potato quality monitoring system during storage in real environment.
- Pre-implementation work (Pre-implementation work module)
- Patent advocacy services, including fees, for registration of exclusive rights to trademark and patent;
- Market marketing research.
- Implementation of the results of R&D work (Implementation work module)
- Server for the support of the TubSenseAI client platform (user web interface);
- TubSensAI’s centralized plant performance monitoring platform.
As a result of the project, the following will be implemented:
- Product innovation in the form of a new product: the TubSensAI system (a potato quality monitoring system based on identification of volatile substances and digital imaging supported by artificial intelligence);
- A process innovation in the form of a fundamental change in the process of quality control of potato tubers.
In addition, as a result of the project, the Applicant:
- plans to patent the integrated hardware and software solution with AI models resulting from the implementation of the proposed project. It is planned to obtain patent protection for the solution under the registration of a European protection right;
- plans to file 1 application with the European Union Intellectual Property Office (EUIPO) for protection of the TubSensAI trademark.
#EUFunds #EuropeanFunds.
Project value: PLN 7,098,648.32
Amount of contribution from European Funds: PLN 4,933,438.15