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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
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
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.
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
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
CIRCUIT DIAGRAM
FLOW CHART
NO
NO
YES
YES
PROJECT MODEL
DEVELOPED CONTROL SYSTEM
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.
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
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
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
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
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.
1. Savva, A. P. and K. Frenken (2002) Irrigation Manual Planning, Development
Monitoring and Evaluation of Irrigated Agriculture with Farmer Participation.
Volume Modules 1-6.
2. Kulkarni, S.A., F.B. Reinders and F. Ligetvari (2006) Global Scenario of
Sprinkler in Micro-Irrigated Areas. Sept 10 - 16 2006, PWTC, Kuala Lumpur
7th International Micro Irrigation Congress.
3. Smart Irrigation System © www.clovity.com
4. Watering on crops © www.gvsprinklers.com.au/
REFERENCES
THANK
YOU

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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.
  • 16. 1. Savva, A. P. and K. Frenken (2002) Irrigation Manual Planning, Development Monitoring and Evaluation of Irrigated Agriculture with Farmer Participation. Volume Modules 1-6. 2. Kulkarni, S.A., F.B. Reinders and F. Ligetvari (2006) Global Scenario of Sprinkler in Micro-Irrigated Areas. Sept 10 - 16 2006, PWTC, Kuala Lumpur 7th International Micro Irrigation Congress. 3. Smart Irrigation System © www.clovity.com 4. Watering on crops © www.gvsprinklers.com.au/ REFERENCES