SMART AIR 5.0 invites you to submit unpublished research chapters in Smart Environment exploring the field of IoT, AI and Machine Learning for monitoring Air Quality Index. 

The book "Smart Air: Transforming Air Quality Monitoring with IoT, AI, and Drone Technology" explores how cutting-edge innovations in technology have revolutionized the way air quality is monitored. This book examines how big data and cloud computing provide effective processing and storage of enormous amounts of air quality data, while IoT devices offer real-time data gathering and remote accessibility. It looks at deep learning models for anomaly identification in AQI data, neural networks for accurate AQI forecasting, and machine learning for air quality analysis and prediction. There is also discussion of the creative use of AI for industrial emission control, transfer learning for model optimization, and drone technology for real-time monitoring. The book also discusses the financial elements of air quality monitoring, placing a strong emphasis on investment plans and cost-benefit assessments, and it links these technological developments to international sustainability objectives. "Smart Air" provides a thorough overview of the future of air quality management, making it an invaluable resource for anybody interested in the nexus of environmental science and cutting-edge technology.

Submission Guidelines

We are pleased to invite you to contribute your research as a chapter in the book titled “Smart Air: Transforming Air Quality Monitoring with IoT, AI and Drone Technology” to be published by Taylor and Francis Group.

• No Publication Fee.
• Similarity Index should be less than 10%.
• All chapters must be original and simultaneously not submitted to another journal or conference or book.

Template

Length of Chapter could be between 15 - 20 Pages (approx).

File Format: MS Word (.doc or .docx)

Times New Roman - 11 Points with 1.5 Spacing.

Single Column Page Layout

All text, figures, equations, and images should be original and in open (editable) format, Please provide them in at least 300 dpi.

Table of Content / Full Chapters Not limited to :

1.  IoT based AQI Monitoring
2. Role of Big data and Cloud Computing in AQ Monitoring
3. Air Quality Analysis and Prediction using Machine Learning
4. AQI Prediction using Neural Network
5. Anomaly Detection in AQI Data using Deep Learning
6. AQI Real-Time monitoring using Drone technology
7. Industrial Emission Monitoring using AI
8. Transfer Learning and Model Optimization for AQI
9. Economic Aspects of Air Quality Monitoring
10. Sustainability Goals and Air Quality Index 

Editors

Dr. Sanjay Saini , Department of Physics and Computer Science, Dayalbagh Educational Institute , Agra , India.

Mr. Amarjeet Singh Chauhan, Department of Physics and Computer Science, Dayalbagh Educational Institute , Agra , India.

Mr. Mohit Yadav, Department of Physics and Computer Science, Dayalbagh Educational Institute , Agra , India.

Contact

All questions about submissions and any query should be emailed to : mohit173333@dei.ac.in