## 4 Conclusions  
In this paper, a long-distance, real-time DCC system based on LED point clustering and lightweight image processing is proposed. The proposed LED-DCC point clustering scheme has solved the problem of a short transmission distance in existing LED-DCC systems. Meanwhile, this paper also proposes the lightweight, back-forth, fast image processing algorithm to solve the problem of processing latency introduced by point clustering and to improve the reliability of information extraction. The experimental setup is implemented on a 2.2-inch 16 \(\times\) 16 point LED display and a CMOS camera on a smartphone with a resolution of 3840 \(\times\) 2160, and an Android smartphone demodulator APP was engineered. The experiment results show that the maximum data transmission distance of the proposed LED-DCC system can reach 7 m under a BER of 0.5, which is about 9 times that of the previous LED-DCC system, and can reach a data transmission distance of 175 cm under the 7% FEC limit, which is about 12 times that of the previous LED-DCC system. Additionally, the data decoding latency caused by extracting information from each video frame is only 13.26 ms, which guarantees real-time data reception.  
In the LED-DCC systems, the main limitation of the current maximum transmission distance and the transmission rate is the low frame rate and resolution of the image sensor. However, it is possible to achieve high data rates in the range of several Mbit/s by using MIMO or using more than one color channel for data modulation, e.g., the R, G, and B channels, and achieve a longer transmission distance by using a high-resolution image sensor. Future works should be directed towards improving the channel capacity of the LED-DCC system while testing the performance under outdoor conditions, promoting the expansion of more potential application scenarios of LED-DCC.  
Conceptualization, J.L. ([PERSON]) and C.P.; methodology, J.L. ([PERSON]); software, C.P. and J.P.; validation, C.P.; formal analysis, [PERSON] ([PERSON]) and J.P.; investigation, C.P. and J.L. ([PERSON]); resources, M.L., J.F. and Z.L.J.; data curation, J.P.; writing--original draft preparation, J.L. and C.P.; writing--review and editing, [PERSON] ([PERSON]), C.P., J.P., [PERSON] ([PERSON]), M.L., J.F. and Z.L.J.; visualization, J.P. and J.L. ([PERSON]); supervision, M.L., J.F. and Z.L.J.; project administration, J.F.; funding acquisition, J.F. All authors contributed to the critical reading and writing of the manuscript. All authors have read and agreed to the published version of the manuscript.  
This work was funded by the National Key Research and Development Program of China (No. 2018 YFB1801900, No. 2019 YFE0123600), National Natural Science Foundation of China (No. 62171202), Guangdong Provincial Postgraduate Education Innovation Project (No. 2019 SFKC08), European Union's Horizon 2020 Research and Innovation Programme under the [PERSON] grant agreement No. 872172 (TESTBED2 project: www.testbed2.org (accessed on 1 September 2022)), HKU-SCF FinTech Academy and themebasecal research funding (T35-710/20-R) of RGC from the HK  
\begin{table}
\begin{tabular}{c c c} \hline \hline  & **The Previous** & **The Proposed LED-DCC** \\  & **LED-DCC System [14]** & **System** \\ \hline LED light-emitting area detection & 10.34 ms & 13.07 ms \\ LED-DCC data bit extraction & 1.49 ms & 0.19 ms \\ Total & 11.83 ms & 13.26 ms \\ \hline \hline \end{tabular}
\end{table}
Table 2: The average data decoding latency for data reception.  
Government, and National Innovation and Entrepreneurship Training Program for Undergraduate (No. 202010559036).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The data that supports the findings of this study are available within the article.  
**Conflicts of Interest:** The authors declare no conflict of interest.