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AI-Driven Smart Air Quality Monitoring and Predictive Pollution Control System Using IoT and Edge Computing

Air pollution has become a major environmental threat, yet traditional monitoring systems rely on expensive fixed stations with limited coverage and delayed reporting. This project introduces an AI-driven Smart Air Quality Monitoring and Predictive Pollution Control System that integrates IoT sensors, edge computing, machine learning, and cloud analytics for real-time, scalable monitoring. A network of low-cost sensors measures pollutants such as PM2.5, PM10, CO₂, CO, and NO₂, sending data to an edge device (ESP32/Raspberry Pi) for cleaning, filtering, and anomaly detection. Edge processing minimizes latency, saves bandwidth, and enables rapid local decision-making. Cleaned data is then uploaded to the cloud, where models like Random Forest, XGBoost, and LSTM generate short- and long-term pollution forecasts. An interactive dashboard visualizes real-time AQI, spatial patterns, and predictive insights to support timely interventions. Overall, this cost-effective system demonstrates key CS engineering skills and offers a practical framework for smarter, healthier, and more resilient cities.

Published by: Daksh Jain

Author: Daksh Jain

Paper ID: V11I6-1280

Paper Status: published

Published: December 13, 2025

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Research Paper

Parkinson’s Disease – History, detection, and cure

This paper talks about the neurodegenerative disease commonly known as Parkinson's disease, about the history of this disease and its causes, various subtypes, as well as how the diagnosis of this disease takes place. It has mainly 3 causes those being environment, genetics, or interactions. It usually happens to people above the age of 60, but there are younger cases as well. This disease causes loss of dopaminergic neurons in the brain; these neurons help in motor activities of the body, thus their loss causes loss of motor activities of the body. The dopamine-producing neurons Substantia Nigra are directly affected. The neurons degenerate due to the accumulation of Alpha’s nuclein in the brain. The paper discusses how motor, non-motor and psychological aspects should be taken into account during the identification of this disease.

Published by: Prisha Teotia

Author: Prisha Teotia

Paper ID: V11I6-1272

Paper Status: published

Published: December 13, 2025

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Research Paper

AI Bias in Data Training

This research paper talks about AI bias in data training and how it creates age, gender and cultural discrimination. This paper also talks about how spreading awareness about AI bias can help mitigate the issue. It examines how biased training data distorts decision-making in various fields like hiring, healthcare and law enforcement. This paper shows us the need for transparency, accountability and awareness in AI systems and how mitigating data bias is essential for creating an AI system that is fair, responsible, and that can be held accountable in case of any biased decisions and output.

Published by: Sarjas Gauhar Singh

Author: Sarjas Gauhar Singh

Paper ID: V11I6-1287

Paper Status: published

Published: December 12, 2025

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Research Paper

Ergonomic Mechanical Tools for Reducing Repetitive Strain Injuries among Workers in Small-Scale Manufacturing Units

Repetitive strain injuries (RSIs) have emerged as a major challenge within small-scale manufacturing environments, damaging worker health and productivity. Ergonomically designed mechanical tools are increasingly recognized as a pivotal solution to this chronic problem. This paper undertakes a thorough examination of RSI etiology, analyzes ergonomic design methodologies relevant for mechanical tools, and synthesizes practical recommendations for designing interventions targeted at small enterprises. Emphasizing both technical and organizational dimensions, the discussion highlights evidence-based strategies and implementation barriers, providing a comprehensive roadmap for sustained ergonomic improvement.

Published by: Nevaan Aggarwal

Author: Nevaan Aggarwal

Paper ID: V11I6-1277

Paper Status: published

Published: December 11, 2025

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Research Paper

Echo Scan – AI Detection of Synthetic and Fake Voices

In a world where voice-based technologies are rapidly evolving, the rise of AI-generated synthetic voices poses serious concerns for authenticity, privacy, and security. Echo Scan is a machine learning-based system designed to differentiate between real human voices and artificially generated ones. The system leverages acoustic features, waveform analysis, and deep learning techniques to identify subtle inconsistencies that are often overlooked by the human ear. Through extensive training on diverse datasets and voice patterns, Echo Scan aims to act as a reliable shield against voice cloning, fraud, and misinformation. This project not only strengthens digital trust but also sets the foundation for future advancements in audio forensics and secure voice authentication.

Published by: Soham Nimse, Aakshaj Nadpurohit, Gayatri Narwade, Rugved Nigade, Nikhil Nagargoje, Priti Nikam, Vikas Nandeshwar

Author: Soham Nimse

Paper ID: V11I5-1298

Paper Status: published

Published: December 11, 2025

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Research Paper

Efficiency of Carbon Fibre for the Automotive Industry

This paper explores the role of carbon fibre reinforced plastic (CFRP) in improving the efficiency, safety and sustainability of modern automobiles. The aim is to determine how beneficial carbon fibre is in making vehicles lighter, cleaner and more energy efficient. It examines CFRP’s advantages over traditional materials such as steel and aluminium, its applications in vehicle design and the manufacturing challenges that limit large-scale use. The paper also discusses recycling methods and environmental improvements that make CFRP more sustainable, along with future prospects for its wider use in the automotive industry.

Published by: Ritvik Pahwa

Author: Ritvik Pahwa

Paper ID: V11I5-1244

Paper Status: published

Published: December 11, 2025

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