T
his project aims to design and fabricate a smart irrigation system
using IoT to optimize water usage, save energy, and increase crop
yield The outcome of this project will be a cost effective and
sustainable solution that benefits farmers and the environment In this
project, we have designed and developed a system for measuring and
monitoring soil moisture by integrating a low cost soil moisture sensor
with IoT, cloud computing, and mobile computing technologies.
Modelling And Fabrication Of Smart Irrigation System Using IOT.pdf
1. MODELLING AND FABRICATION
OF
SMART IRRIGATION SYSTEM USING IOT
.
Group Members
Vinal Kumar
Anurag Singh
Aarya Pal
Nihal Gautam
Gaurav Pratap
Guided By
Dr. Himanshu Mishra
2. 1. INTRODUCTION
2. WEEKLY PLANNING
3. OBJECTIVES
4. CIRCUIT DIAGRAM
5. FLOW CHART
6. PROJECT MODEL
7. DEVELOPED CONTROL SYSTEMS
8. ADVANTAGES
9. DISADVANTAGES
10. WORKING OF MODEL
11. CHALLENGES IN REAL IMPLEMENTATION
12. ADVANTAGES
13. DISADVANTAGES
14. LIMITATIONS
15. CONCLUSION
16. REFERENCES
CONTENTS
3. INTRODUCTION
This project aims to design and fabricate a smart irrigation system
using IoT to optimize water usage, save energy, and increase crop
yield. The outcome of this project will be a cost-effective and
sustainable solution that benefits farmers and the environment. In this
project, we have designed and developed a system for measuring and
monitoring soil moisture by integrating a low-cost soil moisture sensor
with IoT, cloud computing, and mobile computing technologies.
4. In our smart irrigation system project, effective weekly planning
plays a crucial role in maximizing efficiency and developing
project model. By breaking down the project into weekly
milestones, we ensure a systematic approach towards achieving our
objectives. Each week is dedicated to specific tasks and goals that
contribute to the overall success of the project.
Our weekly planning for the Smart Irrigation Project model
encompasses essential activities, including code development for
system control, app development for remote monitoring, and model
testing for performance evaluation.
WEEKLY PLANNING
5. OBJECTIVES
1. Water Conservation
2. Automated Irrigation
3. Real-time Alerts and Notifications
4. Energy Efficient and Cost Savings
5. Crop Health and Yield Improvement
6. Sustainability
7. Weather-based Irrigation Scheduling
8. Integration with Sensor Technology
9. Data Analytics and Decision Support
10. Prevention of Over-Irrigation and Under-Irrigation
11. Integration with Other Smart Agricultural Systems
12. Scalability and Adaptability to Different Crop Types
13. Minimization of Environmental Impact
14. Enhancing Water Use Efficiency
15. Support for Precision Agriculture Practices
10. WORKING OF MODEL
1. The soil moisture sensor continuously measures the moisture
level in the soil.
2. The DHT11 sensor measures the temperature and humidity of the
air and soil.
3. The Node-MCU receives the moisture, temperature, and humidity
data and compares them with predefined threshold values. If the
moisture or temperature or humidity level falls below the
threshold, indicating a need for irrigation, the microcontroller
activates the motor .
4. Once the moisture, temperature or humidity level reaches the
desired range, the Node-MCU deactivates the motor.
5. Throughout the operation, the Node-MCU can send real-time
data to an IoT cloud server for analysis, and remote monitoring.
11. CHALLENGES IN REAL
IMPLEMENTATION
1. Scalability
2. Connectivity
3. Sensor Accuracy
4. Power Supply
5. Data Management
6. Training to Farmers
7. Skilled Person required
8. Maintenance and Support
9. User Acceptance and Education
10. Cost and Return on Investment
12. ADVANTAGES
1. Water Conservation
2. Automated Control
3. Precision Irrigation
4. Water and Cost Savings
5. Data-driven Insights
6. Increased Efficiency
7. Reduction in Manual Labor
8. Environmental Sustainability
9. Integration with Weather Forecasts
10. Real-time Alerts and Notifications
11. Remote Monitoring and Control
12. Prevention of Overwatering
13. Reduction in Water Runoff and Erosion
13. DISADVANTAGES
1. Technical Challenges
2. Limited Compatibility
3. Potential System Failures
4. Maintenance and Upkeep
5. High Initial Cost and Setup
6. Dependence on Technology
7. Limited Customization Options
8. Power Dependency and Backup
9. Complexity and Learning Curve
10. Reliance on Internet Connectivity
11. Data Security and Privacy Concerns
12. Environmental Impact and Sustainability Concerns
14. LIMITATIONS
1. Power Dependency
2. Technical Challenges
3. Limited Compatibility
4. Potential System Failures
5. Dependence on Technology
6. Limited Customization Options
7. Reliance on Weather Forecast Accuracy
8. Limited Accuracy of Sensor Readings
9. Environmental Factors and Interference
10. Limited Scalability for Large Agricultural Areas
11. Limited Effectiveness in Remote or Rural Areas
15. CONCLUSION
Smart irrigation systems using IoT offer efficient and
sustainable water management in agriculture. They enable
precise and automated irrigation control, leading to optimized
water usage, improved crop yield, and reduced water wastage.
IoT technology provides real-time monitoring and remote
access, enhancing convenience for farmers. It promotes
environmental sustainability by minimizing water usage and
conserving energy. Despite challenges, smart irrigation systems
are a promising solution for addressing water scarcity and
enhancing agricultural productivity. Further research and
advancements will drive optimization and widespread adoption,
contributing to sustainable agriculture and water resource
management.
