Advanced Autonomous System for Monitoring Soil Parameters
<b>Context</b>: This research investigates the advantages of real-time monitoring of soil quality for various land management practices. It also highlights the significance of spatio-temporal soil modeling and mapping in providing a clear and visual understanding of how aridity changes o...
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MDPI AG
2025-01-01
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| Series: | Technologies |
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| Online Access: | https://www.mdpi.com/2227-7080/13/1/38 |
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| author | Băjenaru Valentina-Daniela Istrițeanu Simona-Elena Paul-Nicolae Ancuța |
| author_facet | Băjenaru Valentina-Daniela Istrițeanu Simona-Elena Paul-Nicolae Ancuța |
| author_sort | Băjenaru Valentina-Daniela |
| collection | DOAJ |
| description | <b>Context</b>: This research investigates the advantages of real-time monitoring of soil quality for various land management practices. It also highlights the significance of spatio-temporal soil modeling and mapping in providing a clear and visual understanding of how aridity changes over time and across different locations. <b>Aims</b>: This paper aims to provide a comprehensive guide to the key processes required for the development of a laboratory-based soil quality monitoring system. <b>Methods</b>: The applied methodologies involved the processes of sensor deployment, data acquisition infrastructure establishment, and sensor calibration. These procedures culminated in the development of a soil quality assessment model that was subsequently subjected to two months of laboratory testing using three distinct soil types. The analysis yielded a strong positive linear correlation between the measured and predicted soil quality values. <b>Key Results</b>: As expected, the assimilation of prior soil quality estimates within the modeling framework demonstrated a significant enhancement in the accuracy of real-time soil quality estimations. <b>Conclusions</b>: This research promotes the importance of iterative improvements of the soil quality monitoring system. The need for a long-term perspective and a plan for maintenance and continuous improvement of such systems in the ecosystem is important to improve the ease of making predictions to avoid soil aridization. The results of this research will be useful for researchers and practitioners involved in the design and implementation of soil monitoring systems. |
| format | Article |
| id | doaj-art-897d63ea80d744cfa3077ac0f9f2c43e |
| institution | Kabale University |
| issn | 2227-7080 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Technologies |
| spelling | doaj-art-897d63ea80d744cfa3077ac0f9f2c43e2025-01-24T13:50:49ZengMDPI AGTechnologies2227-70802025-01-011313810.3390/technologies13010038Advanced Autonomous System for Monitoring Soil ParametersBăjenaru Valentina-Daniela0Istrițeanu Simona-Elena1Paul-Nicolae Ancuța2Intelligent Thermo-Technical Measurements Department, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, RomaniaEnvironmental Engineering and Renewable Energy Systems Department, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, RomaniaComplex Automation and Control Systems Department, National Institute of Research and Development in Mechatronics and Measurement Technique, 021631 Bucharest, Romania<b>Context</b>: This research investigates the advantages of real-time monitoring of soil quality for various land management practices. It also highlights the significance of spatio-temporal soil modeling and mapping in providing a clear and visual understanding of how aridity changes over time and across different locations. <b>Aims</b>: This paper aims to provide a comprehensive guide to the key processes required for the development of a laboratory-based soil quality monitoring system. <b>Methods</b>: The applied methodologies involved the processes of sensor deployment, data acquisition infrastructure establishment, and sensor calibration. These procedures culminated in the development of a soil quality assessment model that was subsequently subjected to two months of laboratory testing using three distinct soil types. The analysis yielded a strong positive linear correlation between the measured and predicted soil quality values. <b>Key Results</b>: As expected, the assimilation of prior soil quality estimates within the modeling framework demonstrated a significant enhancement in the accuracy of real-time soil quality estimations. <b>Conclusions</b>: This research promotes the importance of iterative improvements of the soil quality monitoring system. The need for a long-term perspective and a plan for maintenance and continuous improvement of such systems in the ecosystem is important to improve the ease of making predictions to avoid soil aridization. The results of this research will be useful for researchers and practitioners involved in the design and implementation of soil monitoring systems.https://www.mdpi.com/2227-7080/13/1/38digital soil mappingsoil moisture sensingsoil monitoring |
| spellingShingle | Băjenaru Valentina-Daniela Istrițeanu Simona-Elena Paul-Nicolae Ancuța Advanced Autonomous System for Monitoring Soil Parameters Technologies digital soil mapping soil moisture sensing soil monitoring |
| title | Advanced Autonomous System for Monitoring Soil Parameters |
| title_full | Advanced Autonomous System for Monitoring Soil Parameters |
| title_fullStr | Advanced Autonomous System for Monitoring Soil Parameters |
| title_full_unstemmed | Advanced Autonomous System for Monitoring Soil Parameters |
| title_short | Advanced Autonomous System for Monitoring Soil Parameters |
| title_sort | advanced autonomous system for monitoring soil parameters |
| topic | digital soil mapping soil moisture sensing soil monitoring |
| url | https://www.mdpi.com/2227-7080/13/1/38 |
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