IoT-Based Atmospheric Pollution Level Analyzer using Raspberry Pi
Objective
The main objective of this project is to develop an IoT-Based Atmospheric Pollution Level Analyzer using Raspberry Pi that monitors air quality in real time using environmental sensors. It detects harmful gases and particulate matter, uploading data to an IoT platform for remote monitoring and alerts. The project focuses on creating a prototype that ensures accurate sensing, data logging, and cloud-based visualization of pollution levels.
Abstract
The IoT-Based Atmospheric Pollution Level Analyzer is designed to continuously monitor environmental air quality using multiple gas sensors connected to a Raspberry Pi. The system measures harmful gases, temperature, and humidity levels in real time. Sensors such as MQ135, MQ2, MQ6, and DHT11 are used to detect air pollutants and environmental conditions. The collected data is processed by the Raspberry Pi and uploaded to a cloud platform through IoT technology for remote monitoring. Whenever pollution levels exceed predefined thresholds, a buzzer alert is activated to notify users immediately. This system helps in pollution monitoring, environmental protection, industrial safety, and smart city applications.
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
ADC Converter
MQ135 Air Quality Sensor
MQ2 Sensor
MQ6 Sensor
DHT11 Sensor
Buzzer
SD Card
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:
o Planning and Requirement Gathering (software’s, Tools, Hardware components, etc.,)
o Schematic preparation
o Code development and debugging
o Hardware development and debugging
o Development of the Project and Output testing
· Practical exposure to:
o Hardware and software tools.
o Solution providing for real time problems.
o Working with team/ individual.
o Work on Creative ideas.
· Project development Skills:
o Problem analyzing skills
o Problem solving skills
o Creativity and imaginary skills
o Programming skills
o Deployment
o Testing skills
o Debugging skills
o Project presentation skills
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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.
