Smart Greenhouse Monitoring with Predictive Crop Health using ML
Objective
The objective of Smart Greenhouse Monitoring with Predictive Crop Health using ML is to create an intelligent system that monitors environmental conditions and predicts crop health using machine learning. This helps optimize growth, prevent diseases, and improve agricultural productivity.
Abstract
This project presents a smart greenhouse monitoring system using Arduino Uno, DHT11, soil moisture sensor, pH sensor, MQ135 gas sensor, LCD display, relay, DC water pump, and buzzer. The system continuously monitors environmental and soil conditions inside the greenhouse. A machine learning model is used to predict crop health and identify stress conditions. Based on the predictions, the system automatically controls irrigation and alerts users during abnormal conditions. The proposed system provides an intelligent, low-cost, and automated solution for efficient greenhouse management and improved crop productivity.
Keywords: Smart Greenhouse, Arduino Uno, Machine Learning, Soil Moisture Sensor, Precision Agriculture.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
Hardware components:
- Arduino UNO
- LCD
- DHT11
- Soil Moisture Sensor
- PH Sensor
- MQ135 Sensor
- Arduino Cable
- Relay
- DC Water Pump
- Connectors-10.
Software requirements:
- Arduino IDE
- Python IDLE
- Embedded c
Learning Outcomes
- Arduino pin diagram and architecture
- How to install Arduino UNO / setup software
- Setting up and installation procedure for Arduino UNO
- Introduction to Arduino UNO environment / development setup Basic programming in Arduino UNO (Embedded C)
- Basics of Embedded programming using Arduino UNO
- Basics of IoT platforms
- Working of power supply
- About Project Development Life Cycle:
- Planning and Requirement Gathering (software, tools, hardware components, etc.)
- Schematic preparation
- Code development and debugging
- Hardware development and debugging
- Development of the project and output testing
- Practical exposure to:
- Hardware and software tools
- Solution providing for real-time problems
- Working with team/individual
- Work on creative ideas
- Skills developed:
- Project development skills
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginative skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation skills
- Thesis writing skills
Paper Publishing
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Disclaimer - Takeoff Edu Group Projects are not associated or affiliated with IEEE in any way. The IEEE Projects mentioned here are mentioned in the context of student projects, whose ideas are derived from IEEE publications, not projects of or by IEEE.
