Al-Ali et al. (2015) presented a wireless irrigation system for a home garden that can be integrated with the home control systems. The system consists of a master station and a set of slave nodes connected with a wireless microcontroller. Each slave node contains a soil moisture sensor, a temperature sensor, a water valve, a ZigBee transceiver and a microcontroller. The slave microcontroller reads the temperature and soil moisture from the trees and grass, then constructs a frame for transmission. The frame is forwarded via ZigBee ad hoc network to the master station.

Al-Bahadly and Thompson (2015) gave a system that measures the soil moisture and determines whether soil requires water or not. The system simulates a garden sprinkler that utilizes a dual output tap timer which consists of two water valves. A Teensy 2.0 microcontroller reads the two moisture-sensing circuits and controls the water valves. The system is more successful because of the more reliable use of the soil probes. Tripathy et al. (2015) gave a system which uses soil moisture, light and temperature sensors to decide (Nimmagadda et al. 2020) the amount of water to be supplied to the plants. The microcontroller is configured by embedded C and Python programming languages. The sensor data are displayed to the user using graphical user interface. The user will control and monitor the system remotely.

Suzuki et al. (2013) used a support vector machine to classify the sensor data that are received from the agricultural system. A cloud system is used to support and store the sensor values. Even if users do not know the irrigation, this system is expert in irrigating agricultural field properly. Nandurkar et al. (2014) gave irrigation using IoT that saves electricity and water and thereby reduces the labor cost. The initial cost of the system was very low so that it can be used by the small farmers. This system also increases the yield of the crops.

Zhao and Ye (2008) transmitted the sensor data to the user in the form of short message using Global System for Mobile (GSM). GSM/General Packet Radio Service (GPRS) is a simple and more convenient way of communication to the end system than the internet. This network is available almost all the time even in the case of failure of the internet. The information can be sent or received with high privacy in the network. Abbas et al. (2014) has given an irrigation process which is controlled by a wireless network for watering the agricultural fields using valves. This implementation is more efficient in terms of time and quantity of water that is supplied to the fields.

Shinde and Gatlawar (2015) developed a wireless sensor network in an agro-based automation system that helps to analyze and compare the data using fuzzy logic. The monitored analog parameters are transmitted to the other side where they can be read and controlled by a set of points. Mekala and Viswanathan (2017) discuss the remote maintenance of the agriculture field. It monitors the temperature, humidity and water level in the soil. The remote-control method also includes animal or bird scaring, spraying and weeding. Based on the real-time sensor data it makes an intelligent decision-making for smart (Kasthuri et al. 2017) irrigation.

Li et al. (2014) describes the multiple access methods such as GSM, Wi-Fi, GPRS, Third Generation (3G), Enhanced Data GSM Environment (EDGE), Local Area Network (LAN) and so on. The data are stored locally in this system. The IoT gateway uses a microcontroller unit as STM32 and embedded operating system as μC/OS-III. The gateway is reliable, extendible and compatible as demonstrated by the application. The gateway is used to realize the real-time detection and control of the greenhouse and improved the power of the intelligent and automated system (Soniya et al. 2017) for greenhouse monitoring.


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