Given the continuous improvement in the capabilities of road vehicles to detect obstacles, the road friction coefficient is closely related to vehicular braking control, thus the detection of road surface conditions (RSC), and the level is crucial for driving safety. Non-contact technology for RSC sensing is becoming the main technological and research hotspot for RSC detection because of its fast, non-destructive, efficient, and portable characteristics and attributes. This study started with mapping the relationship between friction coefficients and RSC based on the requirement for autonomous driving. We then compared and analysed the main methods and research application status of non-contact detection schemes. In particular, the use of infrared spectroscopy is expected to be the most approachable technology path to practicality in the field of autonomous driving RSC detection owing to its high accuracy and environmental adaptability properties. We systematically analysed the technical challenges in the practical application of infrared spectroscopy road surface detection, studied the causes, and discussed feasible solutions. Finally, the application prospects and development trends of RSC detection in the fields of automatic driving and exploration robotics are presented and discussed.

Organic leafy vegetables face challenges related to potential substitution with non-organic products and vulnerability to dehydration and deterioration. To address these concerns, visible and near-infrared spectroscopy (VIS-NIR) combined with linear discriminant analysis (LDA) was employed in this study to rapidly distinguish between organic and non-organic leafy vegetables. The organic category includes organic water spinach (Ipomoea aquatica Forsskal), amaranth (Amaranthus tricolor L.), lettuce (Lactuca sativa var. ramosa Hort.), and pakchoi (Brassica rapa var. chinensis (Linnaeus) Kitamura), while the non-organic category consists of their four non-organic counterparts. Binary classification was performed on the reflectance spectra of these vegetables’ leaves and stems, respectively. Given the broad range of the VIS-NIR spectrum, stability selection (SS), random forest (RF), and analysis of variance (ANOVA) were used to evaluate the importance of the wavelengths selected by genetic algorithm (GA). According to the GA-selected wavelengths and their SS-evaluated values and locations, the significant bands for leaf spectra classification were identified as 550–910 nm and 1380–1500 nm, while 750–900 nm and 1700–1820 nm were important for stem spectra classification. Using these selected bands in the LDA classification, classification accuracies of over 95% were achieved, showcasing the effectiveness of utilizing the proposed method to rapidly identify organic leafy vegetables and the feasibility and potential of using a cost-effective spectrometer that only contains necessary bands for authenticating.

In this study, the performance of a continuous-wave (CW) deep-red Ho ${}^{\mathbf {3+}}$ /Tb ${}^{\mathbf {3+}}$ co-doped fluoride fiber laser was numerically investigated. The laser operated at approximately 750 nm and was cladding pumped by a blue diode. The laser slope efficiency is studied and discussed in relation to the effects of fiber length, output mirror reflectivity, and pump wavelength. The results indicate that Tb ${}^{\mathbf {3+}}$ ions can assist the Ho ${}^{\mathbf {3+}}$ : ${}^{\mathbf {5}}$ F ${}_{\mathbf {4}}$ + ${}^{\mathbf {5}}$ S ${}_{\mathbf {2}} \to ^{\mathbf {5}}$ I ${}_{\mathbf {7}}$ transition in overcoming the population inversion bottleneck, resulting in a significant increase in efficiency and power scalability. At a launched pump power of 60 W, the calculated CW output power of 30.86 W was associated with a slope efficiency of 52%. Such a result encourages the development of a deep-red laser that is constructed from a fluoride fiber co-doped with Ho ${}^{\mathbf {3+}}$ and Tb ${}^{\mathbf {3+}}$ .

In this study, we demonstrate that the slope efficiency for emission at 54X/75X nm in a holmium-doped zirconium fluoride (Ho3+:ZrF4) fiber is significantly enhanced by the efficient recycling of the pump excitation to the upper laser level of the visible transition through co-lasing the transition at $1.2~\mu $ m. A 0.1 mol.% Ho3+:ZrF4 fiber was able to produce continuous-wave lasers at 54X and 75X nm with slope efficiencies of 68.7% and 27.7% when directly pumped by a blue diode laser at 450 nm in a linear cavity. Although co-lasing at $1.2~\mu $ m can only improve the slope efficiency of the visible laser emission at lower pump powers, these results illustrate the potential of diode pumping for the efficient operation of rare-earth (RE) doped fluoride fiber lasers when implemented in conjunction with co-lasing mechanisms. The fundamental principles discussed in this study should be applicable to other glass and crystalline hosts.

This study presents a Q-switched numerical model that incorporates time-dependent reflectivity and its application to a visible holmium-doped fluorozirconate glass (Ho:ZBLAN) fiber laser system pumped by a blue laser diode. We systematically investigate the influence of reflectivity-switching time, pump power, and fiber length on the resulting pulse characteristics. Under a 0.8 W pump power, a reflectivity switching time of 150 ns, a fiber length of 25 cm, and a repetition rate of 100 kHz, stable deep-red Q-switched pulses with a width of 122 ns were achieved. The simulation results exhibit close agreement with experimental measurements, validating the model’s accuracy for predicting pulse dynamics. These findings provide critical guidance for the design and optimization of visible Q-switched fiber lasers and offer insights applicable to Q-switched fiber lasers across other spectral regions.