Smart Irrigation System

Project Summary Project consists of 3 modules. Inference Engine  Inference engine is a component of this system that applies logical rules to the knowledge base to deduce new information. To build a smart irrigation system it is pertin

Project Title

Smart Irrigation System

Project Area of Specialization

Electrical/Electronic Engineering

Project Summary

Project Summary

Project consists of 3 modules.

Inference Engine

 Inference engine is a component of this system that applies logical rules to the knowledge base to deduce new information. To build a smart irrigation system it is pertinent that we use accurate information that may eventually lead us to maximize output by minimizing the input. Inference engine will store information about the conditions that are ideal to produce healthy crops. This information will be stored in presets for different types of crops, in essence, it contains information about the amount of water, the pH value and nutrients of soil and the ions required to produce maximum yield. This module of the project will compare its knowledge base already fed to it, to the results obtained by the sensors deployed in the field.

After comparisons, the inference engine will be able to suggest any new changes if necessary, to the farmers and actuators deployed in the field.

Monitoring System

A monitoring system will be installed across the field. This monitoring system consists of sensors with RF module installed on them and all of these sensors will be connected to the Arduino which will collect and analyze the collected data and will propagate this collected data to the inference engine.

Actuators

Actuators will consist of pumps and injectors. Any new changes that will be suggested by the inference engine as required for the cultivation will be implemented by these actuators.

Project Objectives

Project Objectives

The aim of this project is to accomplish tasks in following sequence.

1. Sensors

The prototype will be able to collect data from the soil through sensors:

• Moisture sensor
• NPK(Nitrogen-Phosphorus-Potassium) sensor

This data will be stored temporarily in database as present state.

2. Software

The data stored will then be compared with the presets for corresponding crops for ideal condition factors in terms of NPK concentrations and moisture content in soil.

At front-end, an easy to use UI will guide the user in successfully comparing data.

The prototype will then suggest any necessary actions required for an ideal yield.

the field to accurately supply water in the field.

3. Actuators

The system after recommending course of actions, will activate the fuel pump injectors in the field to accurately supply water in the field.

Control System:

• Suggesting fertilizers to the user
• Activating actuator
• Feedback loop

Project Implementation Method

Project Implementation Method

Implementation of project will be done in 3 phases.

PHASE I

Sensors:

• Moisture Sensor
• NPK Sensor

Interfacing sensors with microcontroller

• configurationRS485 converter

Data collection with maximum accuracy (calibration)

PHASE II

Data collection for presets

Interfacing with raspberry pi

• Establishing presets
• Designing comparator

PHASE III

Designing Actuators:

• Fabrication of pipeline
• Installation of pump
• Calibration of pump
• Installation of injectors
• Calibration of injectors
• Optimization of control process by controlling flow rates.

Benefits of the Project

Benefits of the Project.

Pakistan is primarily an agricultural state. Its economy is highly dependent on agro-based industry and agriculture itself. According to United Nations Development Program (UNDP), Pakistan may run out of fresh water supply by 2025. Part of the problem is caused by the global climate change, but a lot of the issue is caused by inefficient use of Pakistan’s water resources. According to Pakistan Council of Research in Water Resources (PCRWR) report “Water Requirements of Major Crops in Central Punjab”, Pakistan consumes 93% of its water resources for irrigated cultivation. The same report also states that 60% of the irrigation water is lost during the conveyance and application of the resource in fields. Primary reason as stated by the same report is that the lack of knowledge in the agriculture industry about irrigation scheduling. This may be a result of not having accurate climate information, properties of soil and the requirements of the cultivation. Mismatch between any of the aforementioned resources lead not only to water loss but also to the loss of cultivated yield. Since many intermediate industries like textile and food are directly dependent on the cultivation output, their productive efficiencies may also be compromised.

This project aims to solve the aforementioned issues by the introduction of a smart irrigation system which can assist the farmers in effectively and easily monitoring their vast fields in terms of their soil and water needs according to their cultivation crops and currently prevailing climatic conditions. The system can also assist the farmers by providing help with the selection of required fertilizers by utilizing historical data in conjunction with an inference engine.

Technical Details of Final Deliverable

Technical Details of Final Deliverable

Components of FYP:

Components sensing:

• Moisture Sensor
• NPK Sensor
• RS485 converter

Interfacing sensors with microcontroller Raspberry pi.

Creating logics and set of rules for actions to be performed by actuators on certain set of values sensed by sensors deployed in irrigation field.

Actuators:

• Fabrication of pipeline
• Fabrication of pump
• Fabrication of injectors

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Agriculture

Other Industries

Core Technology

Robotics

Other Technologies

Sustainable Development Goals

Clean Water and Sanitation

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com