System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario
Creating a suitable growing environment is necessary to ensure good plant growth in a plant factory, which requires wireless sensor networks (WSNs) to monitor the environment in real time. However, existing WSN clustered routing methods hardly take into account the network unreliability caused by va...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-03-01
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| Series: | Agronomy |
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| Online Access: | https://www.mdpi.com/2073-4395/15/3/751 |
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| author | Wenhao Luo Yuan Zeng Ximeng Zheng Lingyan Zha Weicheng Cai Qing Wang Jingjin Zhang |
| author_facet | Wenhao Luo Yuan Zeng Ximeng Zheng Lingyan Zha Weicheng Cai Qing Wang Jingjin Zhang |
| author_sort | Wenhao Luo |
| collection | DOAJ |
| description | Creating a suitable growing environment is necessary to ensure good plant growth in a plant factory, which requires wireless sensor networks (WSNs) to monitor the environment in real time. However, existing WSN clustered routing methods hardly take into account the network unreliability caused by varying link quality among nodes, resulting in reduced stability and accuracy of environmental monitoring. This study proposes a wireless sensor network system strategy for improving network reliability in large-scale reliable wireless sensor networks suitable for plant factory scenarios. Firstly, a hybrid wireless sensor network was designed and built based on Wi-Fi and ZigBee communication protocols. Secondly, a nonlinear link quality prediction model for plant factory scenarios was developed using a function fitting method, taking into account the interference and attenuation caused by the dense concentration of agricultural facilities and plants in plant factories on the wireless signal propagation. Finally, a network coverage optimization scheme was designed by combining a particle swarm optimization (PSO) algorithm and link quality prediction model, and a reliable cluster routing protocol was designed by combining K-means algorithm. The results indicated that the coefficient of determination (R<sup>2</sup>) for the prediction model was 0.9962. The impact of agricultural facilities and vegetation on link quality was most significant when the node height was 0.7 m. Under the optimal node deployment, the number of nodes was 33, and the network coverage rate (CR) reached 97.512%. Compared with the traditional clustered routing method, the wireless sensor network designed in this study is more applicable to the field of plant factories; it further enhances data transmission effectiveness and link quality, improves the reliability of the network, and realizes the load balancing of the internal transmission of the network, which in turn ensures the accuracy of environmental monitoring and the stability of the system. |
| format | Article |
| id | doaj-art-154e683f7e2c492fbf5e490bef890d69 |
| institution | DOAJ |
| issn | 2073-4395 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agronomy |
| spelling | doaj-art-154e683f7e2c492fbf5e490bef890d692025-08-20T02:41:51ZengMDPI AGAgronomy2073-43952025-03-0115375110.3390/agronomy15030751System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory ScenarioWenhao Luo0Yuan Zeng1Ximeng Zheng2Lingyan Zha3Weicheng Cai4Qing Wang5Jingjin Zhang6College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, ChinaCollege of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou 510642, ChinaSchool of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, ChinaSchool of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, ChinaShanghai Xinghui Vegetable Co., Ltd., Shanghai 201419, ChinaShanghai Xinghui Vegetable Co., Ltd., Shanghai 201419, ChinaSchool of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200240, ChinaCreating a suitable growing environment is necessary to ensure good plant growth in a plant factory, which requires wireless sensor networks (WSNs) to monitor the environment in real time. However, existing WSN clustered routing methods hardly take into account the network unreliability caused by varying link quality among nodes, resulting in reduced stability and accuracy of environmental monitoring. This study proposes a wireless sensor network system strategy for improving network reliability in large-scale reliable wireless sensor networks suitable for plant factory scenarios. Firstly, a hybrid wireless sensor network was designed and built based on Wi-Fi and ZigBee communication protocols. Secondly, a nonlinear link quality prediction model for plant factory scenarios was developed using a function fitting method, taking into account the interference and attenuation caused by the dense concentration of agricultural facilities and plants in plant factories on the wireless signal propagation. Finally, a network coverage optimization scheme was designed by combining a particle swarm optimization (PSO) algorithm and link quality prediction model, and a reliable cluster routing protocol was designed by combining K-means algorithm. The results indicated that the coefficient of determination (R<sup>2</sup>) for the prediction model was 0.9962. The impact of agricultural facilities and vegetation on link quality was most significant when the node height was 0.7 m. Under the optimal node deployment, the number of nodes was 33, and the network coverage rate (CR) reached 97.512%. Compared with the traditional clustered routing method, the wireless sensor network designed in this study is more applicable to the field of plant factories; it further enhances data transmission effectiveness and link quality, improves the reliability of the network, and realizes the load balancing of the internal transmission of the network, which in turn ensures the accuracy of environmental monitoring and the stability of the system.https://www.mdpi.com/2073-4395/15/3/751wireless sensor network designlink quality assessmentnetwork coverage optimizationcluster-based routing algorithm |
| spellingShingle | Wenhao Luo Yuan Zeng Ximeng Zheng Lingyan Zha Weicheng Cai Qing Wang Jingjin Zhang System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario Agronomy wireless sensor network design link quality assessment network coverage optimization cluster-based routing algorithm |
| title | System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario |
| title_full | System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario |
| title_fullStr | System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario |
| title_full_unstemmed | System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario |
| title_short | System Design and Reliability Improvement of Wireless Sensor Network in Plant Factory Scenario |
| title_sort | system design and reliability improvement of wireless sensor network in plant factory scenario |
| topic | wireless sensor network design link quality assessment network coverage optimization cluster-based routing algorithm |
| url | https://www.mdpi.com/2073-4395/15/3/751 |
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