## 5 Conclusions  
In the present study, an algorithm for sub-pixel optical transmitter detection has been developed and experimentally validated within the framework of camera-based optical communications. The developed algorithm is divided into four main blocks: image acquisition, simplification of potential transmitters based on their luminosity and size of the luminous region, correlation of optical signal values with theoretically expected values according to the used frame, and elimination of neighboring pixels. To reduce algorithm execution times, multiprocessing functions were used in the first two mentioned blocks, and to facilitate code development, the programming was carried out leveraging the various libraries and modules of the Python language.  
The results demonstrated improved algorithm performance and better communication quality in lower ambient light conditions and its stability. Additionally, this had a significant impact on processing times, which did not exceed an average of 1 s in any case. Furthermore, working with transmitters of the same type and wavelength also yielded better results, as most of the omitted positive rates were due to differences in luminous power between transmitters and the challenge of finding a value that met these requirements. Expressions (3) and (4) are considered to depend on the type of transmitter being used.  
While the algorithm's results are considered acceptable, the experimental part has limitations. There is a recognized necessity to carry out recordings in new and diverse scenarios with varied environmental conditions. These additional recordings would allow for a more precise adjustment of the polynomial functions defined in Section 2 of this paper. Therefore, it could yield more accurate results in different environments. In addition, a greater number of recordings would enable a more precise definition of favorable wavelengths based on the environment and the determination of maximum distances considering environmental conditions.  
To the best of the authors' knowledge, this is the only OCC discovery algorithm to encompass sub-pixel casuistry. It is true that there are other OCC discovery algorithms that rely on temporal components. For instance, ref. [19] utilizes M sequences, while ref. [20] develops an asynchronous scheme. However, these algorithms operate with transmitter arrays, resulting in much larger projections than sub-pixel. Moreover, they do not offer all the metrics used in this document for evaluating the algorithm, including execution times, percentage of false positives, SNR, etc. Therefore, no comparison has been made with other algorithms given the novelty of the case in this document and due to the scarcity of relevant data in the most related works.  
To conclude, this algorithm holds great significance for the development and introduction of OCC technology, which may have a substantial impact on 6G technology as a supporting technology. It is well suited for export as a web service or as an intermediary component for converting data into other network technologies. The primary application of this technology will focus on sensor networks, where it can enhance aspects such as node density, costs, and energy efficiency. This will have far-reaching implications across sectors such as industry, healthcare, the IoT, and more.  
Conceptualization, I.R.-Y. and V.G.; methodology, I.R.-Y. and V.G.; software, I.R.-Y.; validation, I.R.-Y., J.R. and V.G.; formal analysis, I.R.-Y.; investigation, I.R.-Y.; resources, I.R.-Y.; data curation, I.R.-Y.; writing--original draft preparation, I.R.-Y.; writing--review and editing, I.R.-Y., J.R. and V.G.; visualization, I.R.-Y.; supervision, V.G. and J.R.; project administration, J.R. and R.P.-j.; funding acquisition, R.P.-J. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the Spanish Ministry of Science and Innovation (ID2020-114561 RB-415 100).  
This research was funded by the project Ministry of Science and Innovation (ID2020-114561 RB-415 100).