# UAV-Assisted Dynamic Clustering of Wireless Sensor Networks for Crop Health Monitoring
## 10 Conclusions  
We have developed and tested a dynamic data collection method where data can be collected from selected nodes in a targeted area. In this project, an UAV can move freely without considering the ground network topology. To tackle this, it is proposed that ground nodes will form clusters according to the UAV's path and the nature of data. Further we introduced a Bayesian probability- based cluster head selection process to select the best node as a cluster head. The developed system is evaluated through simulation and proof of concept devices. From the simulation results, we can conclude that the proposed system can drastically increase the network lifetime while maintaining a good throughput. For proof of concept, sensor and sink nodes are developed by using an Arduino microcontroller where the sink node is integrated with the UAV so that it can control the UAV's flight. Real time field data is collected and different parameters are monitored for performance evaluation. The measured results showed that this system is practically feasible while offering many benefits over traditional approaches. Critical data about crops like nutritional stress, bug attacks or the spread of diseases can be detected well in time so they can be cured before the crop is affected or destroyed. By using our developed system, farmers do not need the regular visits to their large farm field and they can rely on this fully automatic system to get accurate, up-to-date and precise information. Furthermore this system can help the farmers to plan the optimum utilization of resources as the system can take appropriate action on their behalf, if some threshold is achieved. Considering all this we can say that developed system will facilitate the use of IoT technology for agriculture to take care of crop health to ensure the quality and quantity of foods. Moreover, the proposed system can be extended in the future in many ways; multiple UAVs can be used in a a coordinated way to further increase the throughput. Single hop clusters can be extended to multi-hop ones at the same time that more professional sensors and sink devices can be made from the proof of concept.  
The authors gratefully acknowledge the support of SNCS Research Center at the University of Tabuk, Saudi Arabi.  
Figure 16: Performance analysis of proof of concept devices (**a**) activities of different components with respect of time (**b**) effect of varying height on throughput and energy consumption.  
**Author Contributions**: [PERSON] originated the idea, concept and algorithms as well as performed simulation study, proof of concept development and real field testing of the system; [PERSON] participated in mathematical models and algorithm development. Also perform results verification and over all supervision; [PERSON] contributed in developing signaling method, localization, performance measurement, system validation. Also validate results and system working; Manuscript proof reading, editing, change validation and rechecking is done by [PERSON]; [PERSON] supervised the project Over all working, evaluation, integration and testing.  
**Conflicts of Interest**: The authors declare no conflict of interest.