چکیده مقاله
The integration of artificial intelligence AI with nanotechnology has revolutionized sensor technology, driving advancements in environmental monitoring, medical diagnostics, and industrial automation By leveraging nanomaterials such as graphene, carbon nanotubes CNTs , metal oxides e g , ZnO, SnO₂ , molybdenum disulfide MoS₂ , and MXenes, sensor performance has been significantly enhanced in terms of sensitivity, accuracy, and environmental resilience This study conducts a comprehensive statistical analysis of AI driven sensors, utilizing a dataset comprising 307 experimental trials derived from peer reviewed literature published between 2018 and 2024 Employing advanced statistical methods, including Analysis of Variance ANOVA , Principal Component Analysis PCA , and multiple regression, we evaluate key performance metrics: sensitivity ppm⁻¹ , accuracy % , response time ms , and robustness under varying environmental conditions such as temperature and humidity Our findings underscore the exceptional performance of hybrid nanomaterials, particularly CNT graphene composites, when coupled with deep learning architectures such as Convolutional Neural Networks CNNs and Long Short Term Memory LSTM models Furthermore, we highlight the critical need for material specific calibration and adaptive AI frameworks to ensure operational reliability in dynamic environments This study advocates for standardized testing protocols and the establishment of open access datasets to promote reproducibility and scalability, providing a robust foundation for the future development of AI driven nanosensor technologies
کلیدواژهها
نویسندگان
Sepehr Ghasemlou
Bachelor of Engineering and Materials Science, Urmia University
شیوه ارجاع
Ghasemlou, Sepehr,1404,Comparative Statistical Analysis of AI-Enhanced Sensors Functionalized with Diverse Nanomaterials: Sensitivity, Accuracy, and Environmental Resilience,21st International Conference on Innovation and Research in Engineering Sciences
ارائهشده در
مجموعه مقالات بیست و یکمین کنفرانس بین المللی نوآوری و تحقیق در علوم مهندسی31 تیر 1404