Fuzzy Logic based Smart Irrigation System using Internet of Things

Abstract

Traditional agricultural systems require huge amount of power for field watering. This paper proposes a smart irrigation system that helps farmers water their agricultural fields using Global System for Mobile Communication (GSM). This system provides acknowledgement messages about the job’s statuses such as humidity level of soil, temperature of surrounding environment, and status of motor regarding main power supply or solar power. Fuzzy logic controller is used to compute input parameters (e.g. soil moisture, temperature and humidity) and to produce outputs of motor status. In addition, the system also switches off the motor to save the power when there is an availability of rain and also prevents the crop using panels from unconditional rain. The comparison is made between the proposed system, drip irrigation and manual flooding. The comparison results prove that water and power conservation are obtained through the proposed smart irrigation system.

Introduction

In agriculture, improving crop yield is crucial to meet up swiftly growing demand of food for population intensification. By predicting ecological circumstances, crop productivity can be increased (muthunpandian et al., 2017, GutiérrezJuan Francisco Villa-Medina et al., 2017, Mohanraj and AshokumarNaren, 2015, Williams, 2012, Harrington et al., 2011). In order to advance crop productivity, there is an urgent need to shift manual methods to automation (Gondchawar and Kawitkar, 2016). Besides, the power problem has become a major issue in most of the villages where still, an everlasting solution has not been found (Ahonen et al., 2008). Crop quality is ensured depending on the data received from agricultural field such as soil moisture level, surrounding crop temperature, etc. (Arivazhagan et al., 2013). Based on availability of sunlight, the system can be switched between the solar mode and the main power supply mode for reducing consumption of electricity (Kajale, 2015). The effective utilization of water is a successful agriculture process. Over several million liters of water are needed for the conventional irrigation methodology, whereas smart irrigation methodology needs few million liters of water (Kim et al., 2008). Whenever the groundwater level is minimized, automation in irrigation methodology is necessary for effective utilization of water resources (Lin, 2011).

A lot of researchers have been performed on irrigation systems. An integrated irrigation system was developed in (Narvekar et al., 2013) to assist and monitor irrigation using the Bluetooth technology. A microcontroller system like PIC 16F88 was designed to monitor the soil, temperature within the crop fields with suitable sensor devices (Narvekar et al., 2013). SMSs are sent to organize irrigation schedule whenever there is a possibility of rain based on environmental conditions in the agriculture field (Ross, 2009). Information regarding detection of diseases is also sent to users to monitor real-time activities. Weekly irrigation evaluation is performed using measurement of soil and environmental changes based on sensor nodes (Sigrimis et al., 2001). Machine learning methods are implemented in agricultural areas for getting precision data and positive yields (Barker et al., 2018).

Automation techniques were established to increase the quality and quantity of crop yield (Bing et al., 2015). However, production is reduced due to reduction in landscape and increasing of pest and plant diseases. Efficient water management is a major concern in many cropping systems. Plant disease causes major production and economic losses in agriculture (Borghetti et al., 2017). An important reason is because of unplanned use of water due to which a significant amount of water goes to waste (Giusti and Marsili-Libelli, 2015). Automating farm irrigation allows farmers to apply appropriate amount of water regardless of availability of labor to own valves on or off and to know the plant growth status. Nowadays, automation has been implemented in all fields like industries, home automation, agriculture, etc. (Papageorgiou et al., 2016). Distributed field sensor-based irrigation systems offer an eventual solution to support irrigation supervision that produces maximum yield with water saving systems.

Smart agricultural system is a superior technology for farmers to boost the productivity of the crops yield with low cost (Navarro-Hellín et al., 2016). A soil moisture detection system based on ZigBee wireless network was proposed to deal with monitoring soil moisture content and no control function for irrigation (Vellidis et al., 2016). The IEEE 802.15.4 standard defines the physical and MAC-layer interface and can operate in either master-slave or peer-to-peer networks arrangement (Tey et al., 2015). The soil moisture monitoring system, which is based on ZigBee, controls soil moisture rate in irrigation areas through solenoid valve, but it needs the support of electricity. A wireless sensing element network is connected to central node of Zigbee, which is successively connected to Central watching Station (CMS) through General Packet Radio Service (GPRS) or Global System for Mobile Communication (GSM) technologies. The system additionally obtains Global Positioning System (GPS) parameters associated with the sector and sends them to a central watching station (Tamirat et al., 2018). The framework examines the compelling path for performing recognition of grape sicknesses through leaf highlight assessment (Salemink et al., 2017), (Rose et al., 2016).

There are many disadvantages of the existing traditional agricultural methods namely costlier and manual monitoring of the agriculture field (Poushter, 2016). Specifically, small-scale smart irrigation systems are utilized to provide the solution for dissimilar variety of plants in spite of getting the solution for moisture related issues (AngelopoulosGabriel et al., 2020). Environmental conditions are analyzed using sensors where information is shared by web-based applications (Goapa et al., 2018). The climate-related smart agriculture is implemented to increase the efficient usage of water. It is also used to increase the ground water in the agriculture field with effective analysis (Imran et al., 2019). User friendly interfaces are used to simulate irrigation parameters to complete the decision whenever climate changes in the agricultural environment (Rowshona et al., 2019). Water utilization efficiency is extremely low, i.e. crops are over irrigated or less irrigated. Accuracy is also a major defect in the manual irrigation systems (Puspitasari and Ishii, 2016, Pongnumkul et al., 2015, Philip et al., 2017, García et al., 2018, Nikzad et al., 2019, Zhang et al., 2019, Singh, 2019).

The objective of the study is to devise an integrated system in the form of plant growth monitoring and controlling irrigation to improve productivity in agriculture. To overcome the mentioned problems of the traditional agricultural methods, the proposed method is implemented for automation in agricultural systems. A plant disease monitoring system is developed to remotely monitor and control irrigation in the agricultural field, which saves water and labor cost. Increasing in accuracy is done using sensors to measure the farmland parameters like soil moisture, temperature, humidity and water flow by knowing water holding capacity of the soil in each field and water requirements and response of each crop grown. During the availability of sunlight, electricity can be utilized by energy stored using solar panel. Based on the data received from the soil moisture sensor, temperature sensor and rain sensor, water is supplied to the agricultural field. This helps in consumption of water. By using GSM technology, the full system is automated to reduce manual work drastically. Crop can also be protected from unconditional rain using a protection panel setup. This system provides a long-term sustainable solution for automatic irrigation control and plant disease monitoring. The main contributions of the paper are as follows:

• The proposed fuzzy-based smart irrigation system provides acknowledgement message about the job’s statuses such as humidity level of soil, temperature of surrounding environment periodically.

• Based on the soil moisture sensor output, the motor is turned on or off automatically to prevent excessive usage of water and electricity.

• Based on the availability of rain, the motor is turned off automatically to save power.

• Usage of solar panel reduces the power consumption drastically.

The rests of the paper are organized as follows. Section 2 presents the proposed method, and Section 3 validates it by experiments. The last section draws the conclusions and further studies.