Automatic Characteristic FTIR Frequency Analysis

M Rihan; M Yamin; M Adil; Arvinkanth Suvarna; Mr. Mounesh K

Automatic Characteristic FTIR Frequency Analysis

December 2024

Vol-11, Issue-1

Paper ID: 25489

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Science and Engineering

Keywords

FTIR spectroscopy molecular analysis functional group identification automation in spectroscopy signal processing artificial intelligence (AI) machine learning spectral frequency detection data preprocessing noise reduction overlapping peaks pharmaceuticals polymers environmental monitoring cloud-based analysis

Abstract

Fourier Transform Infrared (FTIR) spectroscopy is a cornerstone technique for elucidating molecular structures and identifying functional groups by analyzing their unique vibrational frequencies. Traditional FTIR analysis often involves laborious manual procedures, susceptible to human error and time constraints. Recent advancements, driven by computational methods, signal processing, and artificial intelligence (AI), have ushered in automated FTIR analysis, facilitating faster and more accurate identification of characteristic frequencies. This review explores cutting-edge innovations in automated FTIR analysis, focusing on methods for detecting and interpreting key spectral features. It delves into advancements in software technologies, machine learning models, and data preprocessing techniques that enhance accuracy and efficiency. The paper examines applications across diverse fields, including pharmaceuticals, polymer science, and environmental monitoring, while acknowledging persistent challenges such as spectral noise, overlapping peaks, and data standardization. Finally, the review highlights emerging trends and future prospects, including AI-powered solutions and cloud-based platforms, that are poised to revolutionize FTIR spectroscopy.

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Author Information

#	Name	Institute / Affiliation
1	M Rihan	Alvas institute of engineering and technology
2	M Yamin	Alvas institute of engineering and technology
3	M Adil	Alvas institute of engineering and technology
4	Arvinkanth Suvarna	Alvas institute of engineering and technology
5	Mr. Mounesh K	Alvas institute of engineering and technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

Rihan, M, Yamin, M, Adil, M, Suvarna, Arvinkanth, & K, Mr. Mounesh (2024). Automatic Characteristic FTIR Frequency Analysis. International Journal of Advance Research and Innovative Ideas In Education, 11(1), 1448-1451.

MLA Style

Rihan, M, et al. "Automatic Characteristic FTIR Frequency Analysis." International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 1, 2024, pp. 1448-1451.

IEEE Style

M Rihan, M Yamin, M Adil, Arvinkanth Suvarna, and Mr. Mounesh K, "Automatic Characteristic FTIR Frequency Analysis," International Journal of Advance Research and Innovative Ideas In Education, vol. 11, no. 1, pp. 1448-1451, 2024.

Vancouver Style

Rihan M, Yamin M, Adil M, Suvarna Arvinkanth, K Mr. Mounesh. Automatic Characteristic FTIR Frequency Analysis. International Journal of Advance Research and Innovative Ideas In Education. 2024;11(1):1448-1451.

Harvard Style

Rihan, M, Yamin, M, Adil, M, Suvarna, Arvinkanth, & K, Mr. Mounesh (2024) 'Automatic Characteristic FTIR Frequency Analysis', International Journal of Advance Research and Innovative Ideas In Education, 11(1), pp. 1448-1451.

Chicago Style

Rihan, M, et al. "Automatic Characteristic FTIR Frequency Analysis." International Journal of Advance Research and Innovative Ideas In Education 11, no. 1 (2024): 1448-1451.

Turabian Style

Rihan, M, et al. "Automatic Characteristic FTIR Frequency Analysis." International Journal of Advance Research and Innovative Ideas In Education 11, no. 1 (2024): 1448-1451.