# The Impact of Cloud Versus Local Infrastructure on Automatic IoT-Driven Hydroponic Systems
## 5 Conclusions  
This study addressed the issue of configuring an infrastructure for monitoring and controlling a hydroponic system. The authors analyzed two structures: AFCI and entirely LSI. Based on the presented study, it was concluded that each proposal is suitable for a hydroponic system depending on its specific requirements and characteristics. The central research question of this study focused on optimizing the infrastructure for automatic hydroponic systems. These infrastructures depend on classic factors: cost, security, scalability, and implementation complexity. Based on the conducted study, it was demonstrated that cloud-based solutions are more suitable when a distributed monitoring infrastructure is desired. In practice, this solution can monitor multiple facilities located in different places. From a security and reliability perspective, AFCI is superior to LSI but has the disadvantage of higher operational costs compared to local solutions.  
Each infrastructure was detailed in terms of hardware and software. The AFCI solution was based on the specific services of the Microsoft Azure platform. The LSI solution used local custom-made software services. The two proposed infrastructures were implemented and analyzed from the perspective of seven indicators, which were summarized in a table after a thorough analysis. The seven parameters (RT, OR, IC, OC, CS, DA, and DS) were assessed based on tests and showed the superiority of LSI for monitoring a small-scale hydroponic system. The comparative analysis based on scoring showed that for the proposed type of hydroponic system, AFCI has a score of 3 benefits, compared to LSI, which totals 5 advantages. The analysis highlighted the superiority of LSI for the proposed automatic hydroponic system. The comparative study also highlighted the advantages of AFCI if a hydroponic system is desired that can be accessed remotely or can centrally monitor multiple hydroponic systems located in different places.  
Most current research promotes the integration of IoT infrastructures. This research highlighted that such infrastructures are helpful when the application's specific requirements demand this approach. In practice, the research demonstrated that not every problem intended for optimization can be modeled through IoT technologies.  
Through this research, the authors believe they have contributed by introducing and analyzing modern technologies into the agricultural field through a future-oriented sector represented by hydroponic systems. The authors consider this research a foundation for further farm developments considering IoT architecture elements.  
Conceptualization, C.-M.R.; methodology, C.-M.R. and A.S.; software, C.-M.R.; validation, C.-M.R., A.S. and M.P.; formal analysis, C.-M.R. and A.S.; investigation, A.S. and M.P.; resources, A.S. and M.P.; data curation, C.-M.R.; writing--original draft preparation, C.-M.R., A.S. and M.P.; writing--review and editing, A.S.; visualization, C.-M.R., A.S. and M.P.; supervision, C.-M.R. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Petroleum-Gas University of Ploiesti, Romania.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.