LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

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Description

LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

               Irrigation is a very important factor when it comes to industrial farming. Here we introduce a system to monitor the whole field. This method is more effective than a normal field monitoring system. Water is an expensive commodity when it comes to most places in the world. This paper proposes and implements a prototype automatic irrigation system with LoRa. In this case, sensors are used to determine whether it is time to water the field or not by measuring different parameters. Both sensors are connected to a raspberry pi. These sensors can be placed at the plant side to read moisture, humidity, and temperature. DHT11 can measure the temperature and humidity of the field. Further, this data can be transferred to a remote monitoring system using LoRa. In this system there will be a sprinkler that will be activated if the moisture content is low, this sprinkler will be always off if the humidity is high, which means it is raining. Only the person who knows account information can log in to the account to see the output. Data can be also uploaded to a cloud such as thingspeak for remote analysis. LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi


LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

INTRODUCTION:

              Considering the global temperature hikes in the past decade water has become a very precious commodity for the lifeline of farming. Every other process in farming has been automated according to the need of the process. Irrigation systems in most farms across the world still follow the same conventional periodic watering methods. This leads to inefficient use of water resources. This system proposed here rectifies this problem through analysis of the field based on different parameters such as temperature, humidity, and soil moisture content. After analysis water is irrigated in a systematic way to avoid excess usage when not needed. In this system, remote analysis is also possible through IoT. LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi


LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

EXISTING SYSTEM:

  • Pumps that will sprinkle water in a periodic manner
  • No analysis is done to identify the most needed parts
  • Manual or automated systems working periodically
  • Manual irrigation technique

DISADVANTAGES:

  • No analysis
  • More expensive
  • In an existing system for the irrigation process, it needs manpower
  • Consumption of water high
  • The accuracy of output is less

LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

PROPOSED SYSTEM:

  • Monitoring plant parameters using sensors
  • Raspberry pi is used in the sensor node
  • It can be programmed by using the python program
  • Collected data is uploaded to the cloud for further analysis and future purpose
  • Uses a single sensor node for a region of field and a number of irrigation nodes for the same region all are connected to the central sensor node through LoRa
  • Here thing speak cloud is used, since it is free it makes the project less expensive
  • A remote camera is used for monitoring and analyzing plant leafs
  • Through leaf analysis, it is possible to detect plant diseases

ADVANTAGES:

  • Moisture and weather analysis based irrigation
  • Saves water
  • Low-cost implementation
  • Lora’s long-range communication is used
  • The image processing technology is implemented LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

BLOCK DIAGRAM:

SENSOR NODE:

LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

MASTER NODE:

LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi 1

CIRCUIT DIAGRAM:

LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi RECIEVER

LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi TRANSMITTER

BLOCK DIAGRAM EXPLANATION:

  • There are two sensors in this system
  • One for measuring moisture another for temperature and humidity
  • All the sensors are connected to raspberry pi
  • Both sensors are connected to digital pins through the GPIO interface
  • Here we use Lora module as a transmitter and a receiver, It is interfaced with raspberry pi in the sensor node and nodemcu in the master node
  • PC camera is used in the prediction process
  • LCD is interfaced with node MCU for displaying the process
  • The water pump is used to supply water for crops, It is interfaced with raspberry pi LoRa based Monitoring System for Agriculture with Predictive Using Raspberry Pi

HARDWARE REQUIREMENTS:

  • Raspberry pi
  • Node MCU ESP8266
  • LoRa module
  • Moisture sensor
  • DHT11 sensor
  • Water pump
  • LCD 16×2

SOFTWARE REQUIREMENTS:

  • Programming platform: Arduino IDE, python3 IDLE
  • Raspberry pi OS: Raspbian stretch
  • Programing language: Embedded C, python3 

REFERENCES:

[1] B. D. Kumar, P. Srivastava, R. Agrawal, and V. Tiwary?Microcontroller Based Automatic Plant Irrigation System,? International Research Journal of Engineering and Technology, vol. 04 no. 05, pp. 1436? 1439, 2017.

[2] R. Kumar and H. R. Gautam, ?Climate Change and its Impact on Agricultural Productivity in India,? Journal of Climatology and Weather Forecasting, vol. 2, no. 1, pp. 2?4, 2014.

[3] M. Giri and D.N. Wavhal, ?Automated Intelligent Wireless Drip Irrigation Using Linear Programming,? International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) vol. 2, no. 1, pp. 1?5, 2013.

[4] D. Bansal and S. R. N. Reddy,?WSN Based Closed Loop Automatic Irrigation System,? International Journal of Engineering Science and Innovative Technology (IJESIT), vol. 2, no. 3, pp. 229? 237, 2013.

[5] Devika, C. M., K. Bose, and S. Vijayalekshmy. “Automatic plant irrigation system using Arduino.” IEEE International Conference on Circuits and Systems (ICCS), Thiruvananthapuram, India 20-21 Dec 2017.


 

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