Raspberry Pi: AWS Automated Smart Greenhouse
Objective
The objective of this project is to develop an automated smart greenhouse using Raspberry Pi 4 that monitors temperature and humidity to control a heater and fan, maintaining optimal conditions. The system also provides a dashboard for real-time environmental data and device status, offering a low-cost, reliable, and scalable solution for precise climate management.
Abstract
The Raspberry Pi AWS Automated Smart Greenhouse is an IoT-based system designed to monitor and control greenhouse conditions automatically. The system uses a Raspberry Pi as the main controller along with a soil moisture sensor, DHT11 temperature and humidity sensor, and MQ135 sensor for environmental monitoring. An ADC converter is used to process analog sensor data. The collected data is uploaded to the AWS cloud for real-time monitoring and storage. When the soil moisture level falls below a preset threshold, a relay-controlled DC pump automatically irrigates the plants. A buzzer generates alerts when abnormal conditions are detected. The system helps improve crop growth, conserve water, reduce manual effort, and support smart agriculture through automation and cloud-based monitoring.
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:
- Raspberry Pi
- SD Card
- Soil Moisture Sensor
- DHT11 Sensor
- MQ135 Sensor
- ADC Converter
- Relay Module
- DC Water Pump
- Buzzer
- Power Supply
- 12V Adapter
- Connectors – 30
Software components:
- Python
- Raspbian OS
Learning Outcomes
- Understand Raspberry Pi architecture and GPIO configuration
- Learn how to install and configure Raspbian OS and required Python libraries
- Interface analog sensors with Raspberry Pi using MCP3008 ADC
- Implement image classification using Artificial Neural Networks
- Develop real-time skin analysis using USB camera input
- Build automated health screening systems with display and alert features
- Integrate temperature and heartbeat monitoring in diagnostic systems
- Analyze and interpret classification output for healthcare applications
- About Project Development Life Cycle:
- Planning and Requirement Gathering (software’s, 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.
- Project development Skills:
- Problem analyzing skills
- Problem solving skills
- Creativity and imaginary skills
- Programming skills
- Deployment
- Testing skills
- Debugging skills
- Project presentation 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.
