Details of the project EPI

FruitApp - Orchard management system

31-03-2023 do 01-12-2024

2 064 342,40

own funds

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The project in question provides for the use of technologically advanced solutions to automate the implementation of decisions made on the basis of the collected data and related to the analytical process (the pursuit of data analysis that smoothly turns into decisions and then their implementation will be possible using modern technical solutions, previously unavailable in fruit-growing). In the current practice of orchard care, especially in larger areas, the flow of various information to the farmer forces them to be compared, possibly longer consultations with specialists, and then the selection of protective measures or measures and their application - the time that elapses from the appearance of information to the application of practical measures is long and, as a result, some of the actions undertaken in this way may be ineffective. The planned results of the undertaken operation include the integration of crop data in one IT solution, the development and implementation of a pr

The project includes the development and implementation of a tool based on the integration of solutions used in fruit farming. It will be a tool for machine classification and reasoning based on input data. The system will be able to work with sensors within a single interface. The source of meteorological data will be meteorological stations and sensors installed within the orchard. The source of multispectral data will be cameras mounted on the UAV (unmanned aerial vehicle). Photogrammetric flights will be carried out. Input data will pass machine classification on trained models. The result of the work of the classifiers will be a set of conclusions presented to the end user for evaluation. Soil measurements will be carried out. Soil characteristics will be obtained, as well as concentrations of plant protection products in the soil, as well as in leaves and apples. Communication between field sensors can be provided by a local hardware watch-dog or an external server. Archiving and machine processing of input data will take place on separate servers of the computing infrastructure. The presentation of input data, system work results, user notes will be provided in the form of a web application in accordance with the analysis of the hierarchy of end user needs. The operation will consist of 3 stages: development of the concept, prototypes and implementation of the finished application. The project will cover orchard areas. Meteorological stations and sensors monitoring the condition of the orchard will be set up in the orchards. The remaining areas identified during the operation will be used as test areas for training machine learning models to provide a representative sample for orchard conditions modeling based on multispectral imagery.

Contemporary fruit-growing, like agriculture, is heading towards the so-called "precision fruit farming", using a wide range of digital solutions. Increasingly, fruit growers are struggling with rising costs, both in terms of employment, resources necessary for cultivation, equipment and devices used. Fruit growers often lack dedicated tools for planning fruit-growing activities, which may reduce the efficiency of their work. The use of new technologies and innovative solutions make it possible to reduce the challenges related to the above-mentioned problems. The answer to this is the implementation of automatic solutions in all orchard activities. All applications that warn against sudden weather changes (rainstorms/storms/hailstorms, droughts), systems and applications that enable irrigation control based on the results of soil measurements, or applications for monitoring and warning about plant infection by pests are extremely useful. More and more often in horticulture, t

In the current practice of orchard care, especially in larger areas, the flow of various information to the farmer forces them to be compared, possibly longer consultations with specialists, and then the selection of protective measures or measures and their application - the time that elapses from the appearance of information to the application of practical measures is long and, as a result, some of the actions undertaken in this way may be ineffective.

The benefits of the planned operation include primarily: • Development and implementation of a set of algorithms for remote sensing data processing in a format ensuring implementation in the application. • Development and implementation of a prototype of a capsule for dropping biological microcapsules from unmanned aerial vehicles along with a prototype of an application for managing the dropping of biological microcapsules. • Development and implementation of an orchard application. It is planned to develop and implement a prototype of an unmanned aerial vehicle (UAV) integrated with a module for dropping capsules with microbiological agents to be used in commercial orchards. After the implementation of the operation, a patent application is planned for the developed and implemented application. The effects of the project focus on running commercial fruit orchards - automating the process of collecting information and decision-making based on data collected by BSP regarding the condition of individual trees/plants, data processing and identifying places that require agrotechnical treatments, e.g. additional fertilization or protection against pests.

Each farm that decides to use the proposed product will gain access to a versatile tool that has not been available on the market so far. Thanks to the wide application of various solutions, it will be possible to monitor and shape production in a sustainable way on individual farms, which will lead to minimizing losses in terms of quantity as well as quality in relation to soil and fruit. It will also help to have a real impact on low-emissions in a two-way way, both in terms of reducing the amount of pesticides used, as well as reducing the amount of fuel used during field work.

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plant cultivation and horticulture