## 7 Conclusions  
Oil pipeline monitoring is crucial for enhancing safety and minimizing the effect on humans and the environment. The advancement in sensor and communication technologies encourages implementing the IoT as a real-time monitoring system. With this advantage in this study, we have proposed cloud-enabled hybrid architecture based on 2.4 GHz-based Zigbee and LoRa communication The detection end device is the primary node for collecting the critical parameters information of pipeline and monitoring end device based on 2.4 GHz-based Zigbee and LoRa communication communicates the sensory information received from detection end device to the gateway through LoRa. The system is deployed in real-time for evaluating the proposed system, where the proposed system is logging the pressure sensor values on the Cayenne cloud server through the internet from the gateway. A simulation is performed for evaluating the network performance of LoRa and Zigbee. In future work, we will implement the IoT-based drone-enabled vision system for monitoring the pipeline in real-time.  
**Author Contributions:** [PERSON], [PERSON] and [PERSON] made contributions to conception and manuscript writing; [PERSON] and [PERSON] examined and supervised this research and outcomes; [PERSON] carried out validation; [PERSON], [PERSON] and A.S.A. revised and polished the manuscript. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was supported by Taif University Research Supporting Project number (TURSP-2020/239), Taif University, Taif, Saudi Arabia.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** Not applicable.  
**Conflicts of Interest:** The authors declare no conflict of interest.  
**Abbreviations**  
PHMSA Pipeline and Hazardous Materials Safety Administration  
LoRa Long-range  
MAC medium access control  
SCADA Supervisory Control and Data Acquisition  
PLCs programmable logic controllers  
RTUs remote terminal units  
HMI Human-Machine Interface  
WSN wireless sensor network  
WPAN wireless personal area network  
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Research** & **Objective** & **Communication** & **Customized** & **Customized** & **Simulation-** & **Monitoring** & **Remote** \\  & & & **Node** & **Gateway** & **Based** & **Analysis** & **Parameters** & **Monitoring** \\ \hline \multirow{4}{*}{[44]} & real-time pipeline & \multirow{4}{*}{Wi-Fi} & The & Gateway is not & & & \\  & monitoring and & & Arduino-based & implemented. & & & Thingspeak \\  & determine the & & module is & The data is & & server is for \\  & location of the & & implemented. & & with a & & Pulse \\  & damage on a & & Customization & & Wi-Fi-based & & analytics \\  & pipeline & & is not & Arduino & & purpose \\ \hline \multirow{4}{*}{Proposed work} & Hybrid & \multirow{4}{*}{2.4 GHz-based} & Customized & LoRa and ESP & & & IoT-based \\  & architecture for & & sensor node & 8266 Wi-Fi & Zigbee and & & Cayenne is \\  & real-time oil & Zigbee and 433 & with 2.4 & module is & LoRa & & \\  & pipeline & MHz based & GHz-based & integrated for & simulations are & & flow meter in \\  & monitoring & LoRa & Zigbee and & customizing & performed & & \\  & monitoring & & LoRa module & gateway & & & \\ \hline \hline \end{tabular}
\end{table}
Table 4: \(Cont.\)