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Path Loss Determination Using Linear and Cubic Regression Inside a Classic Tomato Greenhouse

Author

Listed:
  • Dora Cama-Pinto

    (Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain)

  • Miguel Damas

    (Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain)

  • Juan Antonio Holgado-Terriza

    (Software Engineering Department, University of Granada, 18071 Granada, Spain)

  • Francisco Gómez-Mula

    (Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain)

  • Alejandro Cama-Pinto

    (Department of Computer Sciences and Electronic, Universidad de la Costa, Barranquilla 080002, Atlantico, Colombia)

Abstract

The production of tomatoes in greenhouses, in addition to its relevance in nutrition and health, is an activity of the agroindustry with high economic importance in Spain, the first exporter in Europe of this vegetable. The technological updating with precision agriculture, implemented in order to ensure adequate production, leads to a deployment planning of wireless sensors with limited coverage by the attenuation of radio waves in the presence of vegetation. The well-known propagation models FSPL (Free-Space Path Loss), two-ray, COST235, Weissberger, ITU-R (International Telecommunications Union—Radiocommunication Sector), FITU-R (Fitted ITU-R), offer values with an error percentage higher than 30% in the 2.4 GHz band in relation to those measured in field tests. As a substantial improvement, we have developed optimized propagation models, with an error estimate of less than 9% in the worst-case scenario for the later benefit of farmers, consumers and the economic chain in the production of tomatoes.

Suggested Citation

  • Dora Cama-Pinto & Miguel Damas & Juan Antonio Holgado-Terriza & Francisco Gómez-Mula & Alejandro Cama-Pinto, 2019. "Path Loss Determination Using Linear and Cubic Regression Inside a Classic Tomato Greenhouse," IJERPH, MDPI, vol. 16(10), pages 1-15, May.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:10:p:1744-:d:231940
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    References listed on IDEAS

    as
    1. José Sánchez & Juan Reca & Juan Martínez, 2015. "Water Productivity in a Mediterranean Semi-Arid Greenhouse District," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(14), pages 5395-5411, November.
    2. Chaichana Chaiwatpongsakorn & Mingming Lu & Tim C. Keener & Soon-Jai Khang, 2014. "The Deployment of Carbon Monoxide Wireless Sensor Network (CO-WSN) for Ambient Air Monitoring," IJERPH, MDPI, vol. 11(6), pages 1-19, June.
    3. Chih-Ning Huang & Chia-Tai Chan, 2014. "A ZigBee-Based Location-Aware Fall Detection System for Improving Elderly Telecare," IJERPH, MDPI, vol. 11(4), pages 1-16, April.
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    Citations

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    Cited by:

    1. Alexis Barrios-Ulloa & Alejandro Cama-Pinto & Emiro De-la-Hoz-Franco & Raúl Ramírez-Velarde & Dora Cama-Pinto, 2023. "Modeling of Path Loss for Radio Wave Propagation in Wireless Sensor Networks in Cassava Crops Using Machine Learning," Agriculture, MDPI, vol. 13(11), pages 1-15, October.
    2. Chamara, Nipuna & Islam, Md Didarul & Bai, Geng (Frank) & Shi, Yeyin & Ge, Yufeng, 2022. "Ag-IoT for crop and environment monitoring: Past, present, and future," Agricultural Systems, Elsevier, vol. 203(C).

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