The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming
Monitoring and control systems integrated into agricultural machinery enable the development of agricultural analyses with advanced management tools, but the full use of all available data is often limited by the lack of uniformity among data transmitted from different agricultural machines. This pa...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-10-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/13/20/11216 |
| _version_ | 1797574923126833152 |
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| author | Vidas Žuraulis Robertas Pečeliūnas |
| author_facet | Vidas Žuraulis Robertas Pečeliūnas |
| author_sort | Vidas Žuraulis |
| collection | DOAJ |
| description | Monitoring and control systems integrated into agricultural machinery enable the development of agricultural analyses with advanced management tools, but the full use of all available data is often limited by the lack of uniformity among data transmitted from different agricultural machines. This paper presents an agricultural data aggregation and conversion model that allows for the collection and use of data captured from different agricultural machines in the course of work; these data differ in their original file formats and cannot be combined and used in a common analysis system. Programming work was carried out to create the model, and a specialised software interface enabled raster data processing using a Python library together with the open-source Hypertext Preprocessor and JavaScript programming language libraries. A PostGIS extension was utilised to engage field geometry and map-layering tools. Model validation showed that the data aggregation and conversion functions ensure the evaluation of semantic content and the transformation of the aggregated data into a unified format which is suitable for further use in intelligent farming management applications. The developed model will encourage precision agriculture, with the aim of improving work efficiency and the rational use of resources, the economy, and ecology in agriculture. |
| first_indexed | 2024-03-10T21:28:58Z |
| format | Article |
| id | doaj.art-fe16bd7f302344f9a225dd59cc2ff201 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T21:28:58Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-fe16bd7f302344f9a225dd59cc2ff2012023-11-19T15:30:13ZengMDPI AGApplied Sciences2076-34172023-10-0113201121610.3390/app132011216The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart FarmingVidas Žuraulis0Robertas Pečeliūnas1Department of Automobile Engineering, Vilnius Gediminas Technical University, Plytinės Str. 25, 10105 Vilnius, LithuaniaDepartment of Automobile Engineering, Vilnius Gediminas Technical University, Plytinės Str. 25, 10105 Vilnius, LithuaniaMonitoring and control systems integrated into agricultural machinery enable the development of agricultural analyses with advanced management tools, but the full use of all available data is often limited by the lack of uniformity among data transmitted from different agricultural machines. This paper presents an agricultural data aggregation and conversion model that allows for the collection and use of data captured from different agricultural machines in the course of work; these data differ in their original file formats and cannot be combined and used in a common analysis system. Programming work was carried out to create the model, and a specialised software interface enabled raster data processing using a Python library together with the open-source Hypertext Preprocessor and JavaScript programming language libraries. A PostGIS extension was utilised to engage field geometry and map-layering tools. Model validation showed that the data aggregation and conversion functions ensure the evaluation of semantic content and the transformation of the aggregated data into a unified format which is suitable for further use in intelligent farming management applications. The developed model will encourage precision agriculture, with the aim of improving work efficiency and the rational use of resources, the economy, and ecology in agriculture.https://www.mdpi.com/2076-3417/13/20/11216smart farmingdata aggregationdata formatconversion |
| spellingShingle | Vidas Žuraulis Robertas Pečeliūnas The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming Applied Sciences smart farming data aggregation data format conversion |
| title | The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming |
| title_full | The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming |
| title_fullStr | The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming |
| title_full_unstemmed | The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming |
| title_short | The Architecture of an Agricultural Data Aggregation and Conversion Model for Smart Farming |
| title_sort | architecture of an agricultural data aggregation and conversion model for smart farming |
| topic | smart farming data aggregation data format conversion |
| url | https://www.mdpi.com/2076-3417/13/20/11216 |
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