Real-Time AI-Assisted Push-Broom Hyperspectral System for Precision Agriculture

Advancing Urban Development: Applications of Hyperspectral Imaging in Smart City Innovations and Sustainable Solutions

Smart cities are urban areas that use advanced technologies to make urban living better through efficient resource management, sustainable development, and improved quality of life. Hyperspectral imaging (HSI) is a noninvasive and nondestructive imaging technique that is revolutionizing smart cities by offering improved real-time monitoring and analysis capabilities across multiple urban sectors. In contrast with conventional imaging technologies, HSI is capable of capturing data across a wider range of wavelengths, obtaining more detailed spectral information, and in turn, higher detection and classification accuracies. This review explores the diverse applications of HSI in smart cities, including air and water quality monitoring, effective waste management, urban planning, transportation, and energy management. This study also examines advancements in HSI sensor technologies, data-processing techniques, integration with Internet of things, and emerging trends, such as combining artificial intelligence and machine learning with HSI for various smart city applications, providing smart cities with real-time, data-driven insights that enhance public health and infrastructure. Although HSI may generate complex data and tends to cost much, its potential to transform cities into smarter and more sustainable environments is vast, as discussed in this review.

Advancing Urban Development: Applications of Hyperspectral Imaging in Smart City Innovations and Sustainable Solutions

Smart cities are urban areas that use advanced technologies to make urban living better through efficient resource management, sustainable development, and improved quality of life. Hyperspectral imaging (HSI) is a noninvasive and nondestructive imaging technique that is revolutionizing smart cities by offering improved real-time monitoring and analysis capabilities across multiple urban sectors. In contrast with conventional imaging technologies, HSI is capable of capturing data across a wider range of wavelengths, obtaining more detailed spectral information, and in turn, higher detection and classification accuracies. This review explores the diverse applications of HSI in smart cities, including air and water quality monitoring, effective waste management, urban planning, transportation, and energy management. This study also examines advancements in HSI sensor technologies, data-processing techniques, integration with Internet of things, and emerging trends, such as combining artificial intelligence and machine learning with HSI for various smart city applications, providing smart cities with real-time, data-driven insights that enhance public health and infrastructure. Although HSI may generate complex data and tends to cost much, its potential to transform cities into smarter and more sustainable environments is vast, as discussed in this review.

A Region-Monitoring-Type Slitless Imaging Spectrometer

In modern scientific practice, it is necessary to consistently observe predetermined zones, with the expectation of detecting and identifying emerging targets or events inside such areas. This research presents an innovative imaging spectrometer system for the continuous monitoring of specific areas. This study begins by providing detailed information on the features and optical structure of the constructed instrument. This is then followed by simulations using optical design tools. The device has an F-number of 5, a focal length of 100 mm, a field of view of 3 × 7, and a wavelength range spanning from 400 nm to 600 nm. The optical path diagram demonstrates that the system's dispersion and imaging pictures can be distinguished, hence fulfilling the system's specifications. Furthermore, the utilization of a Modulation Transfer Function (MTF) graph has substantiated that the image quality indeed satisfies the specified criteria. To evaluate the instrument's performance in the spectrum observation of fixed regions, a region-monitoring-type slitless imaging spectrometer was built. The equipment has the capability to identify a specific region and rapidly capture the spectra of objects or events that are present inside that region. The spectral data were collected effectively by the implementation of image processing techniques on the captured photos. The correlation coefficient between these data and the reference data was 0.9226, showing that the device successfully measured the target's spectrum. Therefore, the instrument that was created successfully demonstrated its ability to capture images of the observed areas and collect spectral data from the targets located within those regions.

Optical Design of a Hyperspectral Remote-Sensing System Based on an Image-Slicer Integral Field Unit in the Short-Wave Infrared Band

Grating-type spectral imaging systems are frequently employed in scenes for high-resolution remote-sensing observations of the Earth. However, the entrance of the grating-type spectral imaging system is a slit or a pinhole. This structure relies on the push broom method, which presents a challenge in capturing spectral information of transiently changing targets. To address this issue, the IFU is used to slice the focal plane of the telescope system, thereby expanding the instantaneous field of view (IFOV) of the grating-type spectral imaging system. The aberrations introduced by the expansion of the single-slice field of view (FOV) of the IFU are corrected, and the conversion of the IFU's FOV from arcseconds to degrees is achieved. The design of a spectral imaging system based on an image-slicer IFU for remote sensing is finally completed. The system has a wavelength range of 1400 nm to 2000 nm, and a spectral resolution of better than 3 nm. Compared with the traditional grating-type spectral imaging system, its IFOV is expanded by a factor of four. And it allows for the capture of complete spectral information of transiently changing targets through a single exposure. The simulation results demonstrate that the system has good performance at each sub-slit, thereby validating the effectiveness and advantages of the proposed system for dynamic target capture in remote sensing.