## 3 Research Methodology and Procedures  
In industrial applications where seamless communication and data exchange are essential, the reliability of wireless technologies is a critical factor. Our research stems from the recognition of the challenges posed by interference to LoRa communications in industrial contexts. Inspired by a visual representation, our study is aligned with the complexities of urban navigation. Much like the interactive navigation tool shown, our research is dedicated to navigating the complex terrain of wireless communication in industrial environments. As seen in Figure 1, the blue vehicle symbolizes mobility, reflecting the moving industrial vehicles in our study. The antenna-covered tower represents the communications infrastructure, in line with our focus on improving LoRa communications. This dynamic figure captures the essence of our research, which aims to create a concrete testbed for robust LoRa communication, even in the noisy environment typical of industrial opera \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Study** & **Focus** & **Experimental Setup** & **Major Findings** \\ \hline \multirow{2}{*}{[20]} & LPWAN communications in vehicular ecosystem & Application of LPWAN technology (LoRa) to vehicular communications & Unprecedented coverage ranges in vehicular ecosystem \\ \hline \multirow{2}{*}{[21]} & Experimental Study of LPWAN for mobile IoT applications & Not specified & Impact of mobility on LPWAN performance, need for mobility-aware protocols \\ \hline \multirow{2}{*}{[22]} & Coverage of LoRa LPWAN through real-life measurements & \multirow{2}{*}{Real-life measurements} & Impressive communication ranges of over 15 km on land, nearly 30 km on water \\ \hline \multirow{2}{*}{[23]} & UAV-based LPWAN system in remote rural environments & Two-tier LPWAN system with UAV base stations & Connectivity augmentation in remote rural areas \\ \hline \multirow{2}{*}{[24]} & LoRa-based lane-change decision aid & Vehicle-to-vehicle communication using LoRa & Enhanced driver decision-making during lane changes \\ \hline \multirow{2}{*}{[25]} & LPWAN-Based agricultural vehicle tracking & LoRa and NB-IoT technologies for agricultural tracking & Analytical expressions for maximum transmission range based on data path-loss model \\ \hline \multirow{2}{*}{[26]} & Carrier Sense mechanism in LoRa networks & Low-cost IoT LoRa framework & Reduction of collisions in both short and long LoRa messages \\ \hline \multirow{2}{*}{[27]} & Exploration of LoRa waveform theory & Quantification of orthogonality in LoRa waveforms & Nonorthogonality across various LoRa spreading factors \\ \hline \multirow{2}{*}{[28]} & Bounding technique for individual node propagation & Reduction of energy and time for individual node propagation & 73\% reduction in energy and time, leading to optimal network configurations \\ \hline \multirow{2}{*}{[29]} & Machine Learning for disseminating global configuration & Reinforcement learning for disseminating policies & 147\% increase in per-node throughput compared to alternatives \\ \hline \multirow{2}{*}{[30]} & Open-source LoRa physical layer prototype on GNU Radio & Real testbed implementation to evaluate the error rate of LoRa for uncoded and coded cases & Testbed error rate performance is within 1 dB of MATLAB simulations \\ \hline \multirow{2}{*}{Our Work} & Reliability of LoRa in NLoS conditions & Real-world settings with mobility, LoRa PHY SDR using GNU Radio & Comprehensive assessment of BLER, SINR, and data rate, demonstrating approximately 90.23\% reliability \\ \hline \hline \end{tabular}
\end{table} 
Table 1: _Cont._tions. In this way, we aim to provide industry with a reliable communication capability that facilitates efficient data navigation in the complex urban environment of modern industrial applications. In this paper, a LoRa-based architecture is designed to improve data communication and collection in urban environments using a simple vehicle.