## 6 Conclusions  
This paper presents a novel optimization scheme based on a DRL framework combined with a six-dimensional ChOA, named 6 DChOA, to optimize the phase shifts of RISs in a batteryless IoT network. The proposed 6 DChOA-DRL framework aimed to overcome two major challenges prevalent in IoT networks, energy harvesting limitations and communication inefficiencies due to limited transmission power, by intelligently configuring RISs. Through rigorous simulations, we demonstrated the effectiveness of our approach under various experimental settings. The 6 DChOA-DRL framework significantly improved the performance compared to conventional methods such as the CNN, PSO, DNN, and basic RL approaches. Specifically, our results show that the harvested power is maximized while ensuring an energy-efficient operation of IoT devices, particularly as the number of  
\begin{table}
\begin{tabular}{c c c c c} \hline \multirow{2}{*}{**Proposed Methods**} & \multicolumn{4}{c}{**Run Time (s)**} \\  & **RMSE \textless{} 15.00** & **RMSE \textless{} 10.00** & **RMSE \textless{} 5.00** & **RMSE \textless{} 2.50** \\ \hline
6 DChOA-DRL & 59 & 148 & 209 & 318 \\ RL & 156 & 221 & 406 & - \\ CNN & 204 & 272 & - & - \\
6 DChOA & 211 & 290 & - & - \\ DNN & 224 & 286 & - & - \\ ChOA & 495 & - & - & - \\ PSO & 529 & - & - & - \\ \hline \end{tabular}
\end{table}
Table 3: Comparison of algorithm run time based on RMSE termination conditions.  
RIS elements increases. The ability of the RIS to dynamically adjust phase shifts allowed for continuous power optimization, even as distances between the source and IoT device increased. Moreover, the proposed method significantly enhanced the achievable data rate, reaching over 14 bps/Hz under certain configurations, while competing methods struggled to provide similar performance. The comparisons between different RIS element configurations demonstrated that an increase in the number of RIS elements results in improved energy harvesting and higher achievable data rates. More importantly, the gap in performance between RIS-assisted and non-RIS systems widened as the source power increased, proving that RISs are a key enabler for extending the coverage area and operational lifetime of batteryless IoT devices. This paper also highlighted the importance of optimizing the phase shifts of RIS elements to strike a balance between enhancing the energy harvesting capability and ensuring reliable communication performance. This balance becomes particularly challenging in scenarios where the reflected signals could potentially interfere with direct transmissions. By incorporating the 6 DChOA optimization into the DRL framework, we were able to efficiently navigate the complex, non-convex optimization problem and achieve superior performance.  
Conceptualization, M.S. and A.E.O.; methodology, M.S. and M.K.; software, M.S. and A.E.O.; validation, M.S. and A.E.O.; formal analysis, M.S.; investigation, M.S., A.E.O. and M.K.; resources, A.E.O. and M.K.; data curation, M.S.; writing--original draft preparation, M.S., A.E.O. and M.K.; supervision, M.K.; project administration, M.K.; funding acquisition, M.K. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
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.