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Mugeshbabu Arulmani

I’m an Electronics and Communication Engineering graduate from Sona College of Technology, Salem. I’m passionate about web & app development, UI/UX design, IoT, and AI/ML, and I build real-world solutions across platforms.

🔧 Skills & Technical Expertise​

  • UI/UX design, web & mobile app development
  • Programming Languages: HTML, CSS, JavaScript
  • AI / Machine Learning: Neural networks, image processing, classification
  • Hardware & IoT: Embedded systems, microcontrollers (NodeMCU), PIR sensors oai_citation:1‡ResearchGate

🎓 Education​

🧠 Research & Publications​

📰 Published Chapters and Conference Articles:​

Determination of Convolutional Neural Network for Removing Gaussian Noise from Digital Images (April 2024)​

In Contemporary Perspective on Science, Technology and Research, Vol. 9. Co-authored with Eldho Paul and Harish Seshamoorthy, this chapter presents a residual convolutional neural network (FFCNN) implemented via Flask for effective denoising of photos affected by Additive White Gaussian Noise (AWGN), using batch normalization and GPU support to achieve high PSNR and SSIM scores. oai_citation:3‡ResearchGate

Futuristic Flask with Convolutional Neural Network for Removing Gaussian Noise from Digital Images (Intelligent Systems Conference, 2022)​

Focuses on a deep learning model integrated with Flask for real-time image denoising and user interaction. oai_citation:4‡ResearchGate oai_citation:5‡Astrophysics Data System

Auto Surveillance Using IoT (November 2022)​

Designed an IoT-based video surveillance system using NodeMCU and Wi‑Fi, featuring remote alerts via ThingSpeak. oai_citation:6‡ResearchGate

🚀 Projects & Innovations​

  • Futuristic Flask CNN (FFCNN): Real‑time image denoising model built with Flask + CNN
  • IoT Surveillance System: Microcontroller-based motion detection system with remote alert integration

Open source contributions are available on GitHub repositories linked on my website.

🌐 Online Presence & Portfolio​