# The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming
## 4 Model Application, Validation, and Testing  
The data aggregation and conversion platform prototype was tested using data collected from real agricultural machinery. The original test data consisted of 35 different datasets collected from agricultural machinery. Testing algorithms were developed to check the validity and format of the system's source data and the conformity of the results generated by the prototype system with the pre-designed rules. During the initial tests, it was found that six of the primary data sets were not processed properly, which led to further optimisation and refinement of the prototype during the system validation phase. After refining the model, all the tests were carried out successfully, and the prototype results were tested on actual agricultural machinery. Once the structure of the data conversion model was developed, tools for aggregating, displaying, analysing, and synthesising aggregated data were provided for convenient and efficient use. For this purpose, a set of transformed data processing and analysis methods were developed, in addition to algorithms to analyse, overlay, compare, and aggregate spatial data. Accumulated user-uploaded or other external data allow for the generation of spatial data reports that include current data as well as information accumulated over time. Using the spatial database and the functions it provides, all these methods were adapted to the location of the data on the maps. The reports generated can be accessed and data manipulation can be performed by users by logging in to the main system web page. With the help of the developed algorithms, the data fed into the system can be analysed and used for a wide range of statistical, temporal, and spatial analyses and decision making in relation to smart farming. The functionality of the web-based system includes the following:  
* The representation of uploaded data in a spatial format;
* The representation of the statistics assigned to a spatial point;
* The representation of the aggregation of the uploaded data across time intervals and space;
* The submission of various types of reports on the selected area;
* The comparison and overlap of different maps. An overview of the selected field and the work performed after importing and converting the agricultural machinery data file is shown in Figure 5. The satellite image is supplemented with a colour layer showing the data of the selected indicator (fertilisation, spraying, sowing, yield, etc.). Selecting the desired layer (colour) provides the user with initial information about the default indicator, while selecting the function History provides detailed information for the field area. The extended field history information consists of the amount of product (sowing, spraying, fertilising, etc.) and the amount of fuel used for the work in absolute terms (kg or l) and relative terms per unit area (kg/ha or l/ha). The annual average value of the parameter in question is also provided, as are the previous year's figures (if the system was charged). Functional representations of the overlay and a comparison of the field map with the statistical data assigned to a spatial point in the developed platform environment are shown in Figure 6. These functional displays allow the user to easily and conveniently compare different field indicators by moving the overlay line concerning the field area (Figure 6a) or by comparing the same field information in parallel on different parts of the screen (Figure 6b). The final stage of the platform's development was the creation of a tool for generating digital layers for smart farming for agricultural machinery. The tool allows the user to use satellite data to create plans for precision agriculture activities (fertilisation, spraying, sowing, etc.) based on the generated historical data and vegetation indexes. These plans are formed on a map in a format suitable for import into smart agricultural equipment (Figure 7).