Green wall irrigation procedures are a particularly important and hard task, given that the quality of the green wall depends on them. There is currently a wide variety of irrigation programmers available, with a range of functions and prices, thereby replacing manual activities and making it easier to maintain green walls. This paper proposes the use of low-cost automated irrigation programmers via a freeware called Arduino. The system is based on air and substrate measurements to ensure optimal plant growth and high water-use efficiency. At certain thresholds, the irrigation system is activated. This not only makes irrigation more convenient but also helps to reduce energy consumption, increases irrigation efficiency and saves time. The data is then sent via Transmission Control Protocol using Internet of Things technology, in this case ThingSpeak. The platform compiles the data and presents them in simple graphical format, thus enabling real-time monitoring from wherever there is Internet access. Together with Arduino, the project incorporates the Raspberry pi system that operates like a database via Hypertext Transfer Protocol Wi-Fi received by a Structured Query Language (MySQL) server using Hypertext Preprocessor. These data are used for the subsequent analysis of green wall performance.
Rivas-Sánchez et al. | Mejora en la retención y distribución de agua en muros verdes usando materiales alternativos […] 19 Ingeniería del Agua | 23.1 | 2019 Mejora en la retención y distribución de agua en muros verdes usando materiales alternativos como medio de crecimiento Improvement in the retention and distribution of water in green walls using alternative materials as a growing media RESUMEN Este trabajo muestra como la fibra de coco mezclada con cascarilla de arroz es útil como medio de cultivo en muros verdes, reduciendo el impacto ambiental de la explotación de musgo Sphagnum a largo plazo. Por esto, se diseñó un prototipo de muros verdes para analizar la diferencia entre ambos sustratos. La escorrentía y la retención hídrica de los sustratos se analizaron mediante sensores de flujo y humedad. El sustrato compuesto de cascarilla de arroz y fibra de coco mostró mayor homogeneidad en la distribución del agua de riego que el musgo Sphagnum. Los análisis de clorofila mostraron diferencias estadísticamente significativas entre el material vegetal plantado en el sustrato de fibra de coco y cascarilla de arroz y en el de Sphagnum, pero no se encontraron diferencias en biomasa y en el contenido hídrico. Palabras clave | Sphagnum; sustratos alternativos; Jardín vertical; Flujo de agua. ABSTRACTThis work shows how coconut fiber mixed with rice husk is useful as a growing medium in green walls, reducing the environmental impact of the Sphagnum moss exploitation in the long term. For this, a prototype of green walls was designed to analyze the difference between both substrates. The runoff and the water retention of the substrates were analyzed by flow and humidity sensors. The substrate composed of rice husk and coconut fiber showed greater homogeneity in the distribution of irrigation water than Sphagnum moss. The chlorophyll analyzes showed statistically significant differences between the plant material planted in the coconut fiber substrate and rice husk than in the Sphagnum, but no differences were found in biomass and water content.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.