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This paper reports a prototype for pH and electrical conductivity monitoring of a hydroponic circuit of germinated spinach. Real-time monitoring has been implemented with a webcam. The data acquisition system is based on the Arduino UNO hardware structure. It is used in conjunction with a Raspeberry Pi 3. In the next step, this development is loaded into an IOT platform. It is hosted on Firebase for remote monitoring of the parameters of interest, and it is accessed in a mobile application developed in APK on Android. The collected data is processed and used for the offline training of a multi-layer neural network. This process was programmed in Python language. Parameters of interest can be estimated in the possible conditions of operation of the hydroponic system.

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IoT System for Estimation of pH and Electrical Conductivity in a Hydroponic Crop by Means of an Artificial Neural Network

  • 章节

  • 发表日期：

    2026年

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  • Mario Antonio López-Pacheco,
  • Mario Cesar Maya-Rodriguez,
  • Mauricio Aarón Pérez-Romero,
  • Alejandra Armenta-Molina

摘要

This paper reports a prototype for pH and electrical conductivity monitoring of a hydroponic circuit of germinated spinach. Real-time monitoring has been implemented with a webcam. The data acquisition system is based on the Arduino UNO hardware structure. It is used in conjunction with a Raspeberry Pi 3. In the next step, this development is loaded into an IOT platform. It is hosted on Firebase for remote monitoring of the parameters of interest, and it is accessed in a mobile application developed in APK on Android. The collected data is processed and used for the offline training of a multi-layer neural network. This process was programmed in Python language. Parameters of interest can be estimated in the possible conditions of operation of the hydroponic system.