UAV Path Optimization for Precision Agriculture Wireless Sensor Networks
The use of monitoring sensors is increasingly present in the context of precision agriculture. Usually, these sensor nodes (SNs) alternate their states between periods of activation and hibernation to reduce battery usage. When employing unmanned aerial vehicles (UAVs) to collect data from SNs distr...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/20/21/6098 |
| _version_ | 1797549731473260544 |
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| author | Gilson E. Just Marcelo E. Pellenz Luiz A. de Paula Lima Bruno S. Chang Richard Demo Souza Samuel Montejo-Sánchez |
| author_facet | Gilson E. Just Marcelo E. Pellenz Luiz A. de Paula Lima Bruno S. Chang Richard Demo Souza Samuel Montejo-Sánchez |
| author_sort | Gilson E. Just |
| collection | DOAJ |
| description | The use of monitoring sensors is increasingly present in the context of precision agriculture. Usually, these sensor nodes (SNs) alternate their states between periods of activation and hibernation to reduce battery usage. When employing unmanned aerial vehicles (UAVs) to collect data from SNs distributed over a large agricultural area, we must synchronize the UAV route with the activation period of each SN. In this article, we address the problem of optimizing the UAV path through all the SNs to reduce its flight time, while also maximizing the SNs’ lifetime. Using the concept of timeslots for time base management combined with the idea of flight prohibition list, we propose an efficient algorithm for discovering and reconfiguring the activation time of the SNs. Experimental results were obtained through the development of our own simulator—UAV Simulator. These results demonstrate a considerable reduction in the distance traveled by the UAV and also in its flight time. In addition, the model provides a reduction in transmission time by SNs after reconfiguration, thus ensuring a longer lifetime for the SNs in the monitoring environment, as well as improving the freshness and continuity of the gathered data, which support the decision-making process. |
| first_indexed | 2024-03-10T15:18:37Z |
| format | Article |
| id | doaj.art-497b5f4bedd843e1b066e56ab86bd4d1 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T15:18:37Z |
| publishDate | 2020-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-497b5f4bedd843e1b066e56ab86bd4d12023-11-20T18:39:44ZengMDPI AGSensors1424-82202020-10-012021609810.3390/s20216098UAV Path Optimization for Precision Agriculture Wireless Sensor NetworksGilson E. Just0Marcelo E. Pellenz1Luiz A. de Paula Lima2Bruno S. Chang3Richard Demo Souza4Samuel Montejo-Sánchez5PPGIa-Graduate Program in Computer Science, Pontifical Catholic University of Parana, Curitiba 80215-901, BrazilPPGIa-Graduate Program in Computer Science, Pontifical Catholic University of Parana, Curitiba 80215-901, BrazilDepartment of Electrical Engineering, Pontifical Catholic University of Paraná, Curitiba 80215-901, BrazilCPGEI/Electronics Department, Federal University of Technology—Paraná, Curitiba 80230-901, BrazilDepartment of Electrical and Electronics Engineering, Federal University of Santa Catarina, Florianópolis 88040-900, BrazilPrograma Institucional de Fomento a la I+D+i, Universidad Tecnológica Metropolitana, Santiago 8940577, ChileThe use of monitoring sensors is increasingly present in the context of precision agriculture. Usually, these sensor nodes (SNs) alternate their states between periods of activation and hibernation to reduce battery usage. When employing unmanned aerial vehicles (UAVs) to collect data from SNs distributed over a large agricultural area, we must synchronize the UAV route with the activation period of each SN. In this article, we address the problem of optimizing the UAV path through all the SNs to reduce its flight time, while also maximizing the SNs’ lifetime. Using the concept of timeslots for time base management combined with the idea of flight prohibition list, we propose an efficient algorithm for discovering and reconfiguring the activation time of the SNs. Experimental results were obtained through the development of our own simulator—UAV Simulator. These results demonstrate a considerable reduction in the distance traveled by the UAV and also in its flight time. In addition, the model provides a reduction in transmission time by SNs after reconfiguration, thus ensuring a longer lifetime for the SNs in the monitoring environment, as well as improving the freshness and continuity of the gathered data, which support the decision-making process.https://www.mdpi.com/1424-8220/20/21/6098unmanned aerial vehiclepath planningprecision agriculturewireless sensor networksdata gathering |
| spellingShingle | Gilson E. Just Marcelo E. Pellenz Luiz A. de Paula Lima Bruno S. Chang Richard Demo Souza Samuel Montejo-Sánchez UAV Path Optimization for Precision Agriculture Wireless Sensor Networks Sensors unmanned aerial vehicle path planning precision agriculture wireless sensor networks data gathering |
| title | UAV Path Optimization for Precision Agriculture Wireless Sensor Networks |
| title_full | UAV Path Optimization for Precision Agriculture Wireless Sensor Networks |
| title_fullStr | UAV Path Optimization for Precision Agriculture Wireless Sensor Networks |
| title_full_unstemmed | UAV Path Optimization for Precision Agriculture Wireless Sensor Networks |
| title_short | UAV Path Optimization for Precision Agriculture Wireless Sensor Networks |
| title_sort | uav path optimization for precision agriculture wireless sensor networks |
| topic | unmanned aerial vehicle path planning precision agriculture wireless sensor networks data gathering |
| url | https://www.mdpi.com/1424-8220/20/21/6098 |
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