Smart irrigation system for precision farming
- 1. TITLE PAGE SMART INDIA HACKATHON 2024 • Problem Statement ID – 1554 • Problem Statement Title- Smart Irrigation System for Precision Farming • Theme- Agriculture, FoodTech & Rural Development • PS Category- Hardware • Team ID- 144 • Team Name (Registered on portal) - Team Sheti
- 2. IDEA TITLE 2 @SIH Idea submission- Template TEAM SHETI IDEA / SOLUTION : Sensor Integration: Soil moisture, temperature, and rain sensors collect real-time data on field conditions. Master and Slave Microcontroller Setup: The system uses ESP32 microcontrollers, with a slave controller gathering sensor data and a master controller making irrigation decisions based on the data and crop schedules. Automation: The system automatically adjusts the irrigation process based on the sensor data, crop requirements, and weather conditions. For example, it stops irrigation if rain is detected. Remote Monitoring and Control: Farmers can monitor and control the irrigation system remotely via a web or mobile application, which uses MQTT protocol to communicate sensor data in real-time. Power Efficiency: Solar energy is used to power the system, enhancing sustainability. Problem Resolution : Automated Irrigation: Sensors provide real-time data to optimize watering, reducing water waste. Remote Control: Farmers can monitor and adjust the system via mobile or web apps, improving efficiency. Weather & Energy Efficiency: Weather forecasts adjust irrigation, and solar power cuts energy costs. Unique Value Propositions (UVP) : Real-time Data Collection Remote Monitoring and Control Weather Integration User-Friendly Interface Energy Efficiency
- 3. TECHNICALAPPROACH Internet of Things (IoT): IoT sensors, such as soil moisture sensors and DHT11 sensors, are used to collect environmental data (e.g., soil moisture, temperature, humidity) in real-time. NODE MCU: A microcontroller that processes sensor data and controls the irrigation system based on preset conditions. Cloud Computing: The system uses a cloud platform to store data, perform analytics, and enable remote monitoring and control via web or mobile apps. Web /Mobile Interface: Wi-Fi or other wireless communication protocols are used to transmit data between sensors, the NodeMCU, and the cloud. Actuators: Motor drivers and solenoid valves are used to control the irrigation equipment (e.g., pumps and sprinklers) based on the system's analysis of the sensor data. TEAM SHETI
- 4. FEASIBILITY AND VIABILITY Analysis of the feasibility of the idea IoT Sensors monitor real-time soil moisture, temperature, and humidity to optimize irrigation. NodeMCU Microcontroller processes data and controls water pumps and valves for automated irrigation. Cloud Integration stores data, enables remote control, and adjusts schedules based on weather forecasts. Mobile/Web Interface allows users to monitor, adjust, and automate irrigation from anywhere, ensuring water efficiency and crop health. Potential challenges and risks Connectivity Issues: The system relies on stable internet access for real-time data transmission and cloud integration. In rural or remote areas with poor connectivity, this can lead to delays or disruptions in irrigation control. Initial Setup Costs: The high upfront costs for IoT sensors, microcontrollers, and cloud services might be a barrier for small-scale farmers, despite long-term savings from water and energy efficiency. Maintenance and Technical Expertise: Regular maintenance of sensors and microcontrollers, along with the need for troubleshooting technical issues, may require specialized technical support, adding to operational costs and complexity. 4 @SIH Idea submission- Template TEAM SHETI
- 5. IMPACT AND BENEFITS Water Conservation Enhanced Crop Yields Cost Savings Environmental Benefits Increased Resilience Community Development Scalability 5 @SIH Idea submission- Template TEAM SHETI
- 6. RESEARCH AND REFERENCES 6 @SIH Idea submission- Template Science Journal : https://doi.org/10.1051/e3sconf/202447201026 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8235149/ OpenAI. Whisper AI Model for Speech-to-Text Transcription. Retrieved from https://openai.com/research International Journal of Industry and Sustainable Development (IJISD), Volume 3, Issue 1, August 2022 Tinkercad TEAM SHETI