An IoT Based Assessment in Workspaces: Indoor Air Quality vs Thermal Comfort
Objective
This study presents an IoT-based system for assessing indoor air quality and thermal comfort in workspaces such as educational institutions and hospitals. The system monitors key air pollutants including CO?, PM2.5, and TVOCs, along with temperature and humidity, using a custom-built sensor network. Real-time data is processed through complex event processing and analyzed using machine and deep learning techniques. An LSTM model forecasts IAQ, while a decision tree regressor identifies relationships between environmental parameters and pollutants.
Abstract
Indoor environmental conditions play an important role in maintaining employee health, comfort, and productivity in modern workspaces. This project presents an IoT-Based Assessment in Workspaces: Indoor Air Quality vs Thermal Comfort using environmental monitoring and automated control techniques. The proposed system uses an Arduino microcontroller integrated with DHT11 and MQ135 sensors to monitor temperature, humidity, and air quality conditions inside workplace environments. A NodeMCU module is used for IoT-based cloud uploading and continuous environmental monitoring. An LCD display shows live environmental parameters and system conditions. The system uses a relay-controlled Peltier module for thermal comfort management, where the module operates in cooling mode when temperature increases and switches to heating mode when temperature decreases. An MQ135 gas sensor is used for detecting harmful gases and poor air quality conditions. If abnormal gas concentration is detected, a CPU fan is automatically activated to improve air circulation and maintain suitable indoor air quality. The proposed system improves workplace environmental monitoring, supports thermal comfort management, enhances indoor air quality control, and promotes healthier and smarter workspace conditions using IoT technology and automation techniques.
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
- NodeMCU
- DHT11 Sensor
- MQ135 Gas Sensor
- Peltier Module
- Relay Module
- CPU Fan
- LCD Display
- Power Supply
- 12V Adapter
- Connectors – 30
Software components:
- Embedded C
- Arduino IDE
Learning Outcomes
- Arduino pin diagram and architecture
- How to install Arduino IDE and required software
- Setting up and installation procedure for Arduino IDE
- Introduction to Arduino development environment
- Basics of Embedded C / Python programming
- Basics of IoT platforms
- Working of power supply
- 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
- Thesis writing skills
Paper Publishing
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