Preliminary study: Development of an automated data collection system for gamma ray measurements using Python

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出版年:IOP Conference Series. Materials Science and Engineering vol. 1326, no. 1 (Apr 2025), p. 012002
第一著者: Yusuff, SM
その他の著者: Tamron, MANM, Mustapha, I, Ismail, AH, MF Abdul Rahim, Idris, SA, NA Abd Rahman, Ramli, N
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IOP Publishing
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022 |a 1757-8981 
022 |a 1757-899X 
024 7 |a 10.1088/1757-899X/1326/1/012002  |2 doi 
035 |a 3196570912 
045 2 |b d20250401  |b d20250430 
100 1 |a Yusuff, SM  |u Malaysian Nuclear Agency , Bangi, 43000 Kajang, Selangor, Malaysia 
245 1 |a Preliminary study: Development of an automated data collection system for gamma ray measurements using Python 
260 |b IOP Publishing  |c Apr 2025 
513 |a Journal Article 
520 3 |a This paper presents an automated data collection system for gammaray measurement using the Python programming language. The system automates experimental data collection from gamma-ray detection systems, providing greater confidence in research results. The objective of this study is to develop a Python coding system for automated data collection and to produce significant graphical data results. The study used Python coding to continuously measure and analyze gamma rays emitted from Ba-133 radioactive material, which were detected using a scintillation detector and counted using a scaler ratemeter. The coding system used NumPy, Pandas, Matplotlib, and Tkinter Python packages, and Microsoft Visual Studio Community for integration. The Beer-Lambert attenuation law formula is embedded in the coding system to produce intensity against time graphical data results for various sample materials. The developed Python code was integrated into the gamma-ray detection system. The automated data collection system operates without significant lag or errors for 3 hours of gamma-ray measurements with 6 to 10 seconds of time interval speed. The graphical user interface (GUI) and data output are visualized immediately and continuously, and all data output can be safely stored on the computer. A Python-based automated data collection system was successfully developed, allowing efficient visualization of significant graphical data results. This system can reduce radiation exposure for radiation workers and may integrate with cloud computing for remote operation in the future. 
653 |a Radioactive materials 
653 |a Cloud computing 
653 |a Radiation effects 
653 |a Gamma rays 
653 |a Data collection 
653 |a Python 
653 |a Graphical user interface 
653 |a Visual programming languages 
653 |a Automation 
653 |a Radiation 
653 |a Coding 
700 1 |a Tamron, MANM  |u International Islamic University of Malaysia , 53100 Kuala Lumpur, Malaysia 
700 1 |a Mustapha, I  |u Malaysian Nuclear Agency , Bangi, 43000 Kajang, Selangor, Malaysia 
700 1 |a Ismail, AH  |u Malaysian Nuclear Agency , Bangi, 43000 Kajang, Selangor, Malaysia 
700 1 |a MF Abdul Rahim  |u MAHSA University , Jalan SP 2, Bandar Saujana Putra, 42610 Jenjarom, Selangor, Malaysia 
700 1 |a Idris, SA  |u University Malaysia of Computer Science and Engineering (UNIMY) , VSQ@PJ City Centre, Jalan Utara, Section 14, 46200 Petaling Jaya, Selangor, Malaysia 
700 1 |a NA Abd Rahman  |u Malaysian Nuclear Agency , Bangi, 43000 Kajang, Selangor, Malaysia 
700 1 |a Ramli, N  |u Malaysian Nuclear Agency , Bangi, 43000 Kajang, Selangor, Malaysia 
773 0 |t IOP Conference Series. Materials Science and Engineering  |g vol. 1326, no. 1 (Apr 2025), p. 012002 
786 0 |d ProQuest  |t Materials Science Database 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3196570912/abstract/embedded/H09TXR3UUZB2ISDL?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3196570912/fulltextPDF/embedded/H09TXR3UUZB2ISDL?source=fedsrch