Development of an IoT Network for Plant Soil Moisture and Temperature Monitoring with Irrigation Control

Leong, Jason Xie Wei (2020) Development of an IoT Network for Plant Soil Moisture and Temperature Monitoring with Irrigation Control. Final Year Project (Bachelor), Tunku Abdul Rahman University College.

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Abstract

This project focuses on Plant Soil Moisture and Temperature Monitoring using the Internet of Things (IoT) for plantation. This work proposes an improved version of the available IoT / Wireless Sensor Node (WSN) systems that uses WiFi as a medium of communication. The developed IoT system consists of four main sections, i.e. the Sensor Nodes, Server Node, Relay Node, and an IoT Platform. The preliminary steps for Sensor Nodes were to sense the readings (soil moisture and temperature) via sensors. Here, the conventional communication network and the sensor nodes were reviewed. After acquiring sensors’ data, sensor nodes will transmit the data to the server node via Message Queuing Telemetry Transport (MQTT). The server node will act as the broker between connected devices (sensor and relay nodes) and the IoT platform. After it receives sensor readings from sensor nodes, it will upload the sensors’ data to the IoT platform. At the same time, when the soil moisture readings are out of the optimal range (<20% and >30%), it will send a command to the relay node in order to turn on the relay switch to water the plant. The relay node will turn on the relay depending on the attributes received from the server node and the water pressure sensor’s reading. ThinsgBoard is the IoT platform being used to display and analyze the sensors’ data. Moreover, the platform is also used to control devices such as changing the sampling rate. To improve the power efficiency of the sensor nodes, a solar panel was used to charge the battery. Depending on the configurations such as sensor sampling rate, the battery life span varies from 12 to 46.6 hours without solar panel. With the solar panel, the battery life span increased to an average of 24.4%. This system is most likely to be installed in an agriculture plantation which required soil parameters to ensure the plant is in an optimal condition.