The Monitoring System of Soil PH Factor Using IoT-Webserver-Android and Machine Learning

What is it about?

This research aims to make and implement an IoT-Webserver-Android and Machine Learning-based soil PH factor monitoring tool system. The soil PH factor includes soil moisture, humidity, temperature, and sunlight. This instrument system employs IoT, Webserver, and Android technologies. Then predictive analytic algorithms based on Machine Learning. The application of the tool system has produced satisfactory outcomes. It is clear from the performance of the three subsystems: (1) the multiple sensors data acquisition tool subsystem, (2) the local web application monitoring subsystem, and (3) the Android phone monitoring subsystem. In addition to the descriptive examination of the tool system's generated data. The system can produce data sets with precision statistical values. The most accurate prediction model for predicting soil PH as an indicator of soil fertility was derived through a comparison of multiple Machine Learning algorithms. These findings indicate that the tool system has a positive effect on soil PH factor data. Due to the availability of large data, real-time data, and precision predictions, the behavior of soil PH factor indicators may be comprehended. The tool system is then capable of autonomous data monitoring and user-friendly display. Can then operate for an extended period of time. So, it becomes more energy-cost efficient. The implication for the future is that this monitoring tool system should be added with Nitrogen-Phosphorus-Potassium sensors to measure soil nutrients. Also, the system added edge-analysis to be integrated in monitoring and analyzing soil nutrients. Edge-analysis by adding the concept of Fuzzy Logic with the Mamdani procedure to detect deficiencies or excesses of Nitrogen-Phosphorus-Potassium in the soil. Results of detection of deficiency or excess of soil nutrients. Then it is conveyed to the user (farmer) via message notification the amount of nutrients needed by the soil. Message notifications via social media such as WhatsApp, Telegram or Email. So by adding edge-analysis in the monitoring system will help farmers make real-time and automatic decisions.

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Photo by Ksenia on Unsplash

Photo by Ksenia on Unsplash

Why is it important?

The focus of this article's IoT-Agriculture application is to make and implement a soil Ph factor monitoring tool system. Soil is a significant component of agricultural output. The soil provides the plant with nutrients required for growth. Several environmental and chemical soil components have a substantial impact on soil fertility and crop yields. Environmental factors including temperature, humidity, and ambient light. Soil chemical components include soil PH and Moisture. In addition to nutrients, soil fertility is also controlled by conditions that limit plant growth. Such environmental variables as temperature, humidity, and sunlight, as well as soil PH and soil moisture, must be monitored for precision agriculture. In addition, soil PH, soil moisture, temperature and humidity, and sunlight create productive soil nutrients.

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