# An IoT System and MODIS Images Enable Smart Environmental Management for Mekong Delta
## 6 Conclusions  
In recent years, environmental management has become an important issue, especially in regions that are rich in biodiversity and natural resources, such as the Mekong Delta. To effectively manage these areas, a smart environmental management system is needed to collect real-time data and provide monitoring and alerts to help protect the environment. This paper presents a smart environmental management system that automatically collects data from Internet of Things (IoT) stations and remote sensing images. The proposed system is designed to be deployed in large areas, such as the Mekong Delta, with low building and operating costs. The system uses telemetry data from IoT stations and remote sensing images to extract values of Land Surface Temperature (LST), PM10, and PM2.5 for areas without IoT stations. These two data sources are automatically collected and stored  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Date (m/d/y)** & **AOB\({}_{blue}\)** & **AOD\({}_{green}\)** & \multicolumn{3}{c}{**PM10**} & **Est. PM10** & **Error** \\ \cline{5-6}  & & & & **(\(\mathrm{\SIUnitSymbolMicro g}/\mathrm{m}^{3}\))** & \\ \hline
12/15/2022 & 307 & 215 & 27 & 13.398 & 13.602 \\ \hline
12/15/2022 & 141 & 97 & 15 & 11.87 & 3.13 \\ \hline
12/16/2022 & 185 & 127 & 12 & 12.192 & \(-\)0.192 \\ \hline
12/16/2022 & 302 & 211 & 11 & 13.323 & \(-\)2.323 \\ \hline
12/19/2022 & 346 & 242 & 12 & 13.71 & \(-\)1.71 \\ \hline
12/19/2022 & 256 & 178 & 12 & 12.88 & \(-\)0.88 \\ \hline
12/20/2022 & 220 & 152 & 20 & 13.389 & 6.611 \\ \hline \hline \end{tabular}
\end{table}
Table 6: The observations of PM10 from 1 November to 31 December 2022.  
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Variable** & **N** & **Max** & **Min** & **Mean** & **StdEv** \\ \hline LST (\(\mathrm{\SIUnitSymbolMicro C}\)) & 36 & 32.75 & 24.03 & 27.40 & 2.047 \\ \hline \(T_{air}\) (\(\mathrm{\SIUnitSymbolMicro C}\)) & 36 & 34.39 & 25.6 & 31.38 & 2.499 \\ \hline \hline \end{tabular}
\end{table}
Table 4: The observations of LST and T\({}_{air}\) from 1 May to 31 December 2022.  
in a cloud storage service for smart data processing. After processing, the monitoring values, alert notifications, and real-time visualizations are displayed on both a website and a mobile application for managers to access. In the Dong Thap Province in the Mekong Delta, experimental results show that the estimated values from our system achieve Root Mean Square Error (RMSE) values of 3.679 \({}^{\circ}\)C for land surface temperature, 4.47 \(\mathrm{\SIUnitSymbolMicro g}\)/\(\mathrm{m}^{3}\) for PM2.5, and 6.09 \(\mathrm{\SIUnitSymbolMicro g}\)/\(\mathrm{m}^{3}\) for PM10. These errors are comparable to other models for other areas reported in the literature, demonstrating the effectiveness of our proposed system. In conclusion, our proposed smart environmental management system provides an effective solution for collecting and processing data from large areas, such as the Mekong Delta. Furthermore, the system utilizes IoT stations and remote sensing images to provide real-time monitoring and alerts, making it a valuable tool for environmental management in this region.  
Methodology, V.H.P. and C.P.-Q.; IoT stations design and implementation, C.P.-Q. and T.V.P.; Implementation and Experiments, V.H.P. and D.P.H.P.; Writing--review & editing, V.H.P., D.P.H.P., T.V.P., K.N.Q. and C.P.-Q. All authors have read and agreed to the published version of the manuscript.  
This research is funded by Vietnam National University Ho Chi Minh City (VNU-HCM) under grant number NCM2021-20-02.  
The data presented in this study are available on request from the corresponding author.  
The authors acknowledge Ho Chi Minh City University of Technology (HC-MUT), VNU-HCM for supporting this study.  
The authors declare no conflict of interest.