Mini project of smart irrigation system for precious farming

It was mini project

1. K.S.R. COLLEGE OF ENGINEERING ( AUTONOMOUS) DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING MINI PROJECT REVIEW Smart Irrigation System for Precision Farming Batch Members Karthick S (73152114509) Shanthosh Kiran R (73152114046) Sugumar V (73152114049) 1 14-08-2024 EEE/KSRCE

2. CONTENT Abstract Introduction Objectives Existing System Proposed System Conclusion 14-08-2024 EEE/KSRCE 2

3. ABSTRACT Water scarcity is a pressing challenge in agriculture, often leading to inefficient irrigation practices that either waste water or fail to meet crop needs.
Our system continuously monitors soil moisture levels and weather conditions in real-time, using this data to provide farmers with data-driven irrigation recommendations. A mobile application , powered by Blynk IoT , will deliver timely alerts and insights, allowing farmers to make informed decisions on when and how much to irrigate. By integrating predictive analytics from weather forecasts , the system ensures that irrigation schedules are adjusted based on upcoming weather events, further optimizing water consumption.
The cloud platform, powered by Thingspeak plays a crucial role in this solution, facilitating data storage, processing, and remote access. 14-08-2024 EEE/KSRCE 3

4. INTRODUCTION Agriculture faces significant challenges in water management, with traditional irrigation practices often leading to inefficient water usage. This not only wastes valuable water resources but also negatively impacts crop yields and sustainability.
To address these challenges, we propose a Smart Irrigation System that utilizes advanced technologies to optimize water usage in farming.
The system employs ThingSpeak as the cloud platform to collect, analyze, and visualize data from various sensors. Through a mobile application powered by Blynk IoT, farmers receive notifications and recommendations based on both current condition and weather forecasts. 14-08-2024 EEE/KSRCE 4

5. OBJECTIVES To Optimize Water Usage: Utilize real-time soil moisture data and weather forecasts to deliver precise irrigation recommendations, reducing water wastage and ensuring crops receive the optimal amount of water. Improve Crop Yields: Increase crop productivity by maintaining optimal soil moisture levels and adjusting irrigation schedules based on predictive analytics. Facilitate Remote Monitoring: Enable farmers to monitor and control their irrigation system remotely through a mobile application, providing real-time updates and alerts. Promote Sustainable Farming: Support sustainable agricultural practices by minimizing water consumption and improving resource efficiency. Implement Advanced Technology: Integrate IoT sensors, cloud-based analytics (via ThingSpeak), and a user-friendly mobile app (via Blynk IoT) to deliver a comprehensive and intuitive irrigation solution. 5 14-08-2024 EEE/KSRCE

6. EXISTING SYSTEM 14-08-2024 EEE/KSRCE 6

7. EXISTING SYSTEM cont… The existing system consists of an ESP8266 microcontroller connected to several environmental sensors, including rain, humidity, temperature, and pressure sensors. These sensors collect real-time data on weather conditions.
The gathered data is transmitted to the Blynk IoT application, which enables users to monitor and control the system remotely through a mobile interface. This setup provides real-time updates and ensures efficient management of environmental conditions.
The system currently operates without the use of a weather API or cloud platform, relying solely on the ESP8266 and Blynk IoT for real-time data handling and user interaction. 14-08-2024 EEE/KSRCE 7

8. 14-08-2024 EEE/KSRCE 8 PROPOSED SYSTEM Microcontroller (ESP8266) Weather API Power Supply Mobile application (Blynk IoT) Cloud Platform ( Thingspeak ) Temperature and Humidity sensor Rain sensor

9. 14-08-2024 EEE/KSRCE 9 PROPOSED SYSTEM ESP8266 and Sensors Integration: The existing system uses an ESP8266 microcontroller connected to various sensors, including rain, humidity, temperature, and pressure sensors. These sensors provide real-time environmental data. Blynk IoT Application: The system is integrated with the Blynk IoT application, allowing real-time monitoring and control through a user-friendly mobile interface. Weather API for Prediction: In addition to real-time data, the system incorporates a weather API to provide predictive insights, enhancing decision-making for better service and resource management. Cloud Platform: The system leverages a cloud platform for data storage, processing, and remote access, ensuring scalability and robust data management.

10. 14-08-2024 EEE/KSRCE 10 CONCLUSION The Smart Irrigation System for Precision Farming leverages the power of IoT, real-time sensor data, and cloud-based analytics to revolutionize water management in agriculture. By integrating the ESP8266 with various environmental sensors, utilizing the Blynk IoT application for real-time monitoring, and incorporating weather predictions through a cloud platform, the system offers a comprehensive solution for optimizing irrigation practices.
This approach not only enhances water efficiency but also improves crop yields, reduces operational costs , and promotes sustainable farming practices. The successful implementation of this system demonstrates the potential of technology to address critical challenges in agriculture, paving the way for more innovative and efficient solutions in the future.

11. THANK YOU 11 14-08-2024 EEE/KSRCE