An iot framework for smart irrigation

An IoT Framework for Smart Irrigation Urmila Harti1, Rashmi Rachh2, Nagraj S. Patil3 1

Department of CSE, VTU, Belagavi Department of CSE, VTU, Belagavi 3 Department of WLM, VTU, Belagavi 2

Abstract— This paper proposes a smart irrigation system using the process of automation. Soil Moisture Sensors and Humidity Sensors are used to detect the moisture content of the soil and irrigate the plants automatically. PIR (Passive Infrared Sensors) are used to detect the motion of animals in the field and makes an alarm in the field and ultimately send a message to the farmer using SMS Gateway. It also tests the proper working of the sensors using Time Series Analysis algorithm. Overall paper is focused on the low cost, scalable and robust system Keywords— Automation, Soil Moisture Sensor, PIR sensor, Humidity Sensor, Time Series algorithm.

I. INTRODUCTION In our country, Agriculture is main source of occupation. But rainfall for agriculture is said to be as the “Gambling of Monsoon”. As water is scarce it is necessary to use it efficiently. Farmers usually maintain a fixed interval of time and his presence is necessary to irrigate the land. But Farmer wont check the moisture content of the soil while irrigation process is been done [1]. Also, intrusion occurs from animals like Elephants, as a result it will destroy the crops. To overcome this drawback Smart Irrigation and agriculture surveillance has been proposed. The experimentation setup introduces two nodes: Sensor Node and the Control Node. Sensor Node comprises of Soil Moisture Sensor, DHT11 and PIR Sensor. Control Node comprises of Atmega-328 which is built on Arduino Uno board.

The Sensor Node sends the soil moisture value and temperature/ humidity values at a fixed interval of time to the Control node. At the receiver end i.e., microcontroller will receive the values from the sensor and control the motor ON/OFF when some threshold value is reached and buzzer an alarm when motion of animal is detected [3]. Finally send a message to the user regarding the intrusion detection.

The rest of the paper introduces the system components in section II. The proposed methodology is explained in section III. The section IV gives the cost analysis. Finally the paper is concluded in section V. II .

A.

SYSTEM COMPONENTS

SOIL MOISTURE SENSOR

It acts as a sensor node. It has 3 pins.

‘S’ stands for signal input ‘+’ stands for power supply connected to 5V

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

‘-‘stands for GND The current passes through the two probes when it is inserted into the soil. Then the resistance is read to calculate its moisture level.

B.

PASSIVE INFRARED SENSOR

The PIR sensor has 3 pins VCC is connected to 5V GND is connected to ground Vout is connected to the digital pin It has 2 slots which has material that is sensitive to Infrared. When the sensor is idle it will detect same amount of Infrared. When a motion is detected, it causes differential change between two halves. The negative differential change occurs when warm body leaves the sensor area. The sensor can detect around an area of 10mt from the lens [4-7].

C.

HUMIDITY SENSOR

The Humidity Sensor DHT11 uses 3 pins Vcc is connected to 5V GND is connected to ground DATA is connected digital value pin It will send the humidity and temperature value that is sensed from DATA pin to the Arduino-Uno microcontroller.

ARDUINO UNO It is built with ATMEGA328 microcontroller, 6 Analog I/P pins, 14 Digital I/O pins, 5V Operating voltage, 7-12V I/P Voltage which is recommended and upto 20V its limited, 40mA is used by DC current per I/O pin, 50mA is used by DC current for 3.3V I/O pin, 2KB by SRAM, 1KB by EEPROM, 32KB for Flash Memory (0.5KB is used by boot loader).

D.

MOTOR PUMP This is controlled by the ATMEGA328 microcontroller. When soil moisture and temperature is above some threshold value, it will automatically get ON. And once the soil meets the certain moisture content it gets OFF. E.

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

ALARM It is controlled by the microcontroller at the control node. When PIR sensor detects a warm motion, the alarm will buzzer and indicates the farmers in the field that an intrusion has been detected.

III. PROPOSED SYSTEM F.

Figure.1. Functional Block Diagram

The block diagram of the proposed Smart Irrigation and Intrusion detection system is shown in Figure. 1. The functionality is explained as below:User logs in to the control terminal and set the desired temperature / humidity criteria for watering and this data moves to Aurdino microcontroller via internet.

Microcontroller watches the current temperature and humidity and when it matches the rules set by microcontroller, motor controller is switched ON to water the plants and after the time expiry the motor controller is switched OFF. Microcontroller continuously monitors the PIR sensors and when an intrusion detected, alarm is sent to control terminal and a notification is sent to the Farmer via SMS on his cell. ď ś Time Series Analysis algorithm – The time series analysis algorithm is designed to overcome the limitations mentioned in [2]. It is designed to detect four kinds of sensor failures: Missing value, Flat line error, Out of bound error and Spike error.

Based on the sensor values, the microcontroller controls the water motor pump and the alarm. But it’s equally necessary to check if the sensors are working correctly. So an algorithm is designed to achieve this goal and it will also inform the user about the sensor that is not working on the graphical user interface.

Figure. 2 Graph showing Missing value and Out of Bound Error in Sensor values

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

A sensor keeps on sending the values to the microcontroller at a fixed interval of time. But when a sensor misses a value at certain interval of time then it gives as Missing Error (as shown in blue line in the graph where it miss a value at time=1).

When a sensor sends a value above some threshold values then it is said as out of bound value. As we can say that current temperature is 28˚ - 30˚C in a certain place and if it raises suddenly crosses threshold value, then such a condition is given as Out of Bound Error.(In Fig. 2 at time=3 it reaches sensor value=60)

Figure. 3 Graph showing Spike and Flatline Error in the sensor values

When as sensor gives a same values for every interval of time then it seems an error have occurred in sensor. In such a situation it gives as flatline error (Fig. 3 depicts brown line as 35 ˚C for every time slot).

When a sensor value spikes at a high value (such a situation occurs when a short circuit occurs and cause damage to the sensor). Usually temperature sensors take value from 0-100. But in Fig. 2 a blue line depicts a spike error that causes temperature sensor to cross 100 ˚. Such an error is termed as Spike error.

So this algorithm will judge the working of the sensor by checking these four conditions and display it on the GUI built on the PC. III. COST ANALYSIS The test for this system is evaluated on the basis of the sensor values acquired every time the microcontroller is started. The Matlab platform is used to connect with SMS gateway. The sensors are been tested using Time Sense Analysis algorithm in Net beans IDE. The PC is equipped with minimum requirements Intel Core 2 Duo processor with 2GB of RAM. It is very essential for a user to build a cost effective system irrespective of which place it’s been applied.

Table -1 Cost Chart

COMPONENT

QUANTITY

TOTAL COST

ARDUINO-UNO

1

Rs. 1000

Soil Moisture Sensor

1

Rs. 200

DHT11 Sensor

1

Rs. 150

PIR Sensor

1

Rs. 100

Alarm

1

Rs. 100

Motor

1

Rs. 300

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International Journal of Recent Trends in Engineering & Research (IJRTER) Volume 02, Issue 08; August - 2016 [ISSN: 2455-1457]

Table 1 show the approximation cost of the complete irrigation surveillance system. It will cost around approximately Rs.2000. If we are installing more sensors then the cost will increase. But ultimately it’s affordable to user.

IV. CONCLUSION In this work, we have implemented a smart agricultural system for better irrigation and intrusion detection. We have added IOT interface system to it and made remote management possible, In addition we have applied Time Series Analysis to detect the sensor error and report errors. With this system it is possible to monitor filed remotely.

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