Pezoa, Miguel Contreras, Játiva, Pablo Palacios ORCID: https://orcid.org/0000-0002-3958-503X, Meza, César Azurdia ORCID: https://orcid.org/0000-0003-3461-4484, Zabala-Blanco, David ORCID: https://orcid.org/0000-0002-5692-5673, Ijaz, Muhammad ORCID: https://orcid.org/0000-0002-0050-9435 and Sánchez, Iván ORCID: https://orcid.org/0000-0003-0686-8612 (2024) Design and Evaluation of a Visible Light Communication System under Varied Atmospheric Conditions for Smart and Sustainable Farming. IEEE Access, 12. pp. 194871-194880. ISSN 2169-3536
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Abstract
This paper proposes an experimental design and evaluation of visible light communication (VLC) based connectivity for smart and sustainable farming (SSF) by considering a controlled greenhouse environment. SSF integrates complete data-driven farming, allowing for precise control over humidity and temperature to produce high-quality yields. The regulation of these parameters in greenhouses is examined through various experiments that assess their influence on VLC connectivity for transmitting Internet of Things (IoT) sensor data. VLC uses Light emitting diodes (LEDs) light for data transmission using intensity modulation, offering an alternative to traditional radio frequency (RF) communication, which can negatively impact SSF due to low bandwidth and high energy cost. The proposed system uses LEDs to transmit information collected by atmospheric sensors, serving as energy sources for SSF as well as for data connectivity. The performance of the proposed VLC system was evaluated by measuring the bit error rate (BER) and the received power under various atmospheric conditions. The results indicate a possible degradation of both the received power and the BER as the humidity increases, as a result of the impact of water particles and condensation. Specifically, the findings show that between distances of 40 and 100 cm it is possible to have adequate BER and received power values to maintain communication, considering humidity less than 100%. This study paves the way for further research opportunities, such as developing adaptive algorithms to enhance the performance of VLC systems under varying environmental conditions and exploring the integration of VLCs for SSF with greenhouse technologies.
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