# Energy-Efficient IoT-Based Light Control System in Smart Indoor Agriculture
## 6 Conclusions  
The benefits and the drawbacks of smart indoor agriculture were discussed in this article, with more emphasis given to its energy consumption as its biggest disadvantage. The research was focused on tools and methods to reduce its energy consumption. Preliminary studies discussed the choice of hardware like energy-efficient LEDs instead of the other types of grow lights, PWM LED drivers that allow one to reduce the intensity of the emitted light without affecting its quality, and low-power microcontrollers to collect sensor data and control the LED drivers according to the user's requirements. The main contribution is focused on the software part of the problem, where a low-computational-cost control algorithm is proposed based on the Newton method, which iteratively updates the control values only when the light intensity is different from the desired one. Furthermore, energy-efficient methods for data transmission are used, allowing one to easily monitor the growth conditions by using wireless communication technologies and implementing communication protocols like RPL that are designed for constrained networks. The results showed that the control method performs well in small- and large-scale plant factories, and the network evaluation results showed that the data transmission quality decreases when the network size is large and when trying to reduce the energy consumption of the network by considering the MRHOF-energy objective function. Yet, it has been shown that, despite this decrease in the data transmission quality, which occurs only in extreme communication  
Figure 17: Total energy consumption of all the nodes depending on the simulation time (10 nodes case). Figure 18: Total energy consumption of all the nodes depending on the simulation time (60 nodes case). conditions when the devices are out of the range, the control method was still able to ensure the proper management of the light conditions, even in large-scale plant factories. It can be concluded that improving the energy efficiency of the production process while ensuring optimal growth conditions for plants is still possible and appears to be the best solution for future food security challenges. Different methods for the wireless management of all the growth factors, including light, temperature, humidity, ventilation, and substrate quality to maximize the plants yields in plant factories, could be the subject of future research. Conceptualization, O.H.A. and H.B. ; methodology, O.H.A. ; software, H.B. ; validation, O.H.A. and H.B. ; formal analysis, D.P. ; investigation, D.P. ; writing--original draft preparation, O.H.A. and H.B. ; writing--review and editing, A.P.A. ; supervision, A.P.A. ; project administration, A.P.A. ; and funding acquisition, A.P.A. All authors have read and agreed to the published version of the manuscript. This research was funded by the Foundation for Science and Technology (FCT/MCTES) in the framework of the Associated Laboratory--Advanced Production and Intelligent Systems (AL ARISE, ref. LA/P/0112/2020) and the R&D Unit SYSTEC (Base UIDB/00147/2020 and Programmatic UIDP/00147/2020 funds), both funded by national funds through the FCT/MCTES (PIDDAC), and project \"SNAP--Sustainable Management and Control of Agro-Production Systems\", with the reference NORTE-01-0145-FEDER-000085, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (ERDF). Not applicable. Not new data were created or analyzed in this study. Data sharing is not applicable to this article. The authors declare no conflict of interest. The following abbreviations are used in this manuscript: