Air Pollution: Sensitive Detection of PM2.5 and PM10 Concentration Using Hyperspectral Imaging

Abstract

This paper proposes a method to detect air pollution by applying a hyperspectral imaging algorithm for visible light, near infrared, and far infrared. By assigning hyperspectral information to images from monocular, near infrared, and thermal imaging, principal component analysis is performed on hyperspectral images taken at different times to obtain the solar radiation intensity. The Beer–Lambert law and multivariate regression analysis are used to calculate the PM2.5 and PM10 concentrations during the period, which are compared with the corresponding PM2.5 and PM10 concentrations from the Taiwan Environmental Protection Agency to evaluate the accuracy of this method. This study reveals that the accuracy in the visible light band is higher than the near-infrared and far-infrared bands, and it is also the most convenient band for data acquisition. Therefore, in the future, mobile phone cameras will be able to analyze the PM2.5 and PM10 concentrations at any given time using this algorithm by capturing images to increase the convenience and immediacy of detection.

Identification of Early Esophageal Cancer by Semantic Segmentation

“…However, most of these biosensors have a high limit of detection, thereby leading to poor sensitivity in early-stage cancer detection. With the increase in the domestic air-pollution rate, the risk for EC is constantly increasing [ 38 , 39 ]. Despite the rapid development of AI in recent years, EC continues to have the lowest survival rate because its symptoms are difficult to detect.…”

Intelligent Identification of Early Esophageal Cancer by Band-Selective Hyperspectral Imaging

“…HSI has previously been used in numerous classifications fields, such as agriculture [ 33 ], astronomy [ 34 ], military [ 35 ], biosensors [ 36 ], air pollution detection [ 37 , 38 ], remote sensing [ 39 ], dental imaging [ 40 ], environment monitoring [ 41 ], satellite photography [ 42 ], cancer detection [ 43 ], forestry monitoring [ 44 ], food security [ 45 ], natural resource surveying [ 46 ], vegetation observation [ 47 ], and geological mapping [ 48 ]. The advantage of HSI lies in its excellent resolution, and with a minimum spectral resolution of less than 10 nm, it can be used to obtain more information than RGB images [ 49 ].…”

Design of a Lab-On-Chip for Cancer Cell Detection through Impedance and Photoelectrochemical Response Analysis

“…Clinical studies show that the early detection of cancer can significantly increase the five-year survival rates of patients [ 9 , 10 ]. With the increase in air pollution rates, the cancer rate has been steadily increasing, and traditional techniques, such as magnetic resonance imaging, ultrasounds, and biopsies, are insufficient for early-stage cancer diagnosis [ 11 ], are expensive and time consuming, and sometimes generate false negatives [ 12 , 13 , 14 ]. Therefore, artificial intelligence (AI) cancer diagnosis methods have been built, which have been successful [ 6 , 15 , 16 , 17 , 18 ].…”