Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS)
The increasing demand for high-quality vegetable oils has amplified the need for efficient, and accurate, oil recognition systems. This paper introduces the Portable Intelligent Oil Recognition System (PIORS), a pioneering advancement in the field. PIORS stands as the first-ever portable, AI-powered...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-12-01
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| Series: | Smart Agricultural Technology |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772375524002296 |
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| author | Montaser N.A. Ramadan Mohammed A.H. Ali Shin Yee Khoo Layth Hamad Mohammad Alkhedher |
| author_facet | Montaser N.A. Ramadan Mohammed A.H. Ali Shin Yee Khoo Layth Hamad Mohammad Alkhedher |
| author_sort | Montaser N.A. Ramadan |
| collection | DOAJ |
| description | The increasing demand for high-quality vegetable oils has amplified the need for efficient, and accurate, oil recognition systems. This paper introduces the Portable Intelligent Oil Recognition System (PIORS), a pioneering advancement in the field. PIORS stands as the first-ever portable, AI-powered device tailored for rapid and accurate oil type identification, capable of delivering results within a mere five seconds. Using advanced machine learning, PIORS can distinguish between various oil types such as sesame, black seed, flaxseed, and almond oils, ensuring the quality and safety of the final product. The device's innovative design integrates an advanced sensor array with seamless Bluetooth connectivity, offering real-time data synchronization with mobile applications. Several Machine learning models, including Support Vector Machines (SVM), AdaBoost, Random Forest, K-Nearest Neighbors (K-NN), Gradient-Boosting Decision Tree (GBDT), and Extreme Gradient Boosting (XGBoost) were implemented and thoroughly validated to obtain correct categorization. The results show that the XGBoost instantaneous classification algorithm continuously beat the competition, obtaining an astounding success rate of 97 percent in predicting and differentiating between the four oil classes. PIORS not only sets a new standard for speed and efficiency in oil quality assessment but also paves the way for groundbreaking applications in food safety, environmental monitoring, and quality control processes. This paper details the development, implementation, and validation of PIORS, showcasing its potential to revolutionize the agri-food industry with its cutting-edge, AI-driven approach to oil recognition. |
| format | Article |
| id | doaj-art-7b538ee562154275a23f4fc04c3cbe7b |
| institution | OA Journals |
| issn | 2772-3755 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Smart Agricultural Technology |
| spelling | doaj-art-7b538ee562154275a23f4fc04c3cbe7b2025-08-20T02:38:46ZengElsevierSmart Agricultural Technology2772-37552024-12-01910062410.1016/j.atech.2024.100624Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS)Montaser N.A. Ramadan0Mohammed A.H. Ali1Shin Yee Khoo2Layth Hamad3Mohammad Alkhedher4Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, MalaysiaDepartment of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, Malaysia; Corresponding author.Department of Mechanical Engineering, Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, Malaysia; Centre of Research Industry 4.0 (CRI 4.0), Faculty of Engineering, Universiti Malaya, 50603, Kuala Lumpur, MalaysiaQatar Mobility Innovations Center, Qatar University, Doha, QatarMechanical and Industrial Engineering, Abu Dhabi University, Abu Dhabi, United Arab EmiratesThe increasing demand for high-quality vegetable oils has amplified the need for efficient, and accurate, oil recognition systems. This paper introduces the Portable Intelligent Oil Recognition System (PIORS), a pioneering advancement in the field. PIORS stands as the first-ever portable, AI-powered device tailored for rapid and accurate oil type identification, capable of delivering results within a mere five seconds. Using advanced machine learning, PIORS can distinguish between various oil types such as sesame, black seed, flaxseed, and almond oils, ensuring the quality and safety of the final product. The device's innovative design integrates an advanced sensor array with seamless Bluetooth connectivity, offering real-time data synchronization with mobile applications. Several Machine learning models, including Support Vector Machines (SVM), AdaBoost, Random Forest, K-Nearest Neighbors (K-NN), Gradient-Boosting Decision Tree (GBDT), and Extreme Gradient Boosting (XGBoost) were implemented and thoroughly validated to obtain correct categorization. The results show that the XGBoost instantaneous classification algorithm continuously beat the competition, obtaining an astounding success rate of 97 percent in predicting and differentiating between the four oil classes. PIORS not only sets a new standard for speed and efficiency in oil quality assessment but also paves the way for groundbreaking applications in food safety, environmental monitoring, and quality control processes. This paper details the development, implementation, and validation of PIORS, showcasing its potential to revolutionize the agri-food industry with its cutting-edge, AI-driven approach to oil recognition.http://www.sciencedirect.com/science/article/pii/S2772375524002296ESP32Food safetyIoTMOXOil recognitionPIORS |
| spellingShingle | Montaser N.A. Ramadan Mohammed A.H. Ali Shin Yee Khoo Layth Hamad Mohammad Alkhedher Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) Smart Agricultural Technology ESP32 Food safety IoT MOX Oil recognition PIORS |
| title | Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) |
| title_full | Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) |
| title_fullStr | Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) |
| title_full_unstemmed | Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) |
| title_short | Revolutionizing agri-food technology: Development and validation of the Portable Intelligent Oil Recognition System (PIORS) |
| title_sort | revolutionizing agri food technology development and validation of the portable intelligent oil recognition system piors |
| topic | ESP32 Food safety IoT MOX Oil recognition PIORS |
| url | http://www.sciencedirect.com/science/article/pii/S2772375524002296 |
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