Effect Of Fog Research Articles

A modified sensor fusion framework for quantifying and removing the effect of harsh environmental condition for reliable mobile robot mapping

PurposeAn autonomous mobile robot requires efficient perception of the environment to perform various tasks in a challenging environment. The precise sensory information from the range sensors is required to accomplish prerequisites, such as SLAM, path planning and localization. But the accuracy and precision of the sensors become unreliable in harsh environmental conditions because of the effect of rain, dust, humidity, fog and smoke. The purpose of this paper is to generate robust mapping of the environment in harsh environmental conditions.Design/methodology/approachThis paper presents a novel technique, averaging data with short range selection (ADWSRS), to reduce the effect of harsh environmental (rain, wind, humidity, etc.) conditions on sensory information (range) to generate reliable grid mapping. The sensory information on laser and sonar sensors in terms of probability values (occupied/unoccupied cell) in generating grid maps are fused after passing through two newly designed pre-processing filters: laser averaging filter and short range selection filter. This proposed approach relies on various aspects such as averaging laser data analogous to current pose of the sensor, selection of short range with respect to threshold value to remove the effect of specular reflection/crosstalk of sonar and a newly designed apparatus in which dirt cover (glass cover) and air blower are coupled to remove the influence of dirt, rain and humidity.FindingsThis proposed approach is tested in different environmental conditions, and to verify the consistency of the proposed approach, qualitative and quantitative analyses are carried out, which shows 42.5 per cent improvement in the probability value of occupied cells in the generated grid map.Originality/valueThe proposed ADWSRS approach reduced the effect of harsh environmental conditions such as fog, rain and smoke to generate efficient mapping of the environment, which may be implemented in diverse applications such as autonomous navigation, localization, path planning and mapping.

Evaluation of a New Interface Combining High-Flow Nasal Cannula and CPAP

This study assessed the effects of a new interface that combined CPAP 10 cm H2O by using a helmet with high-flow nasal cannula (HFNC) at varying flows in healthy volunteers. Outcome measures included pharyngeal pressures, diaphragm kinetics, breathing frequency, the temperature inside the helmet, and comfort. After baseline assessment during spontaneous breathing, HFNC was applied at flows of 30, 40, and 50 L/min. Successively, the volunteers underwent helmet CPAP at 10 cm H2O and CPAP + HFNC at flows of 30, 40, and 50 L/min. We measured the variations of pharyngeal pressures at end-expiration and end-inspiration, referenced to spontaneous breathing for HFNC and to CPAP for CPAP + HFNC, diaphragm displacement and thickness at end-expiration and thickness at end-inspiration, breathing frequency, the temperature inside the helmet, the occurrence of the fog effect, and comfort. Variations of pharyngeal pressures at end-inspiration changes were small overall and clinically unimportant. With the mouth closed, at increasing HFNC flow, variations of pharyngeal pressures at end-expiration increased during both HFNC (from 2.8 up to 7.7) and, to a lesser extent, CPAP + HFNC (from 2.7 up to 3.8) (P < .001 for all comparisons). These variations were attenuated during open-mouth breathing. HFNC ≥ 40 L/min and CPAP + HFNC ≥ 40 L/min compared with spontaneous breathing and CPAP, respectively, increased diaphragm displacement (P = .001), thickness at end-inspiration and thickness at end-expiration (P < .003 for both). At all flows, breathing frequency was slightly, although significantly, lower with CPAP + HFNC than with HFNC alone (P < .003). The temperature inside the helmet increased slightly and insignificantly at flows of ≤40 L/min with CPAP + HFNC compared with CPAP alone. The fog effect never occurred, whereas comfort was always rated as optimal, without differences between trials. CPAP + HFNC was well tolerated, with no adverse effects. Based on our findings, there was no need to vary the CPAP level when adding HFNC. At least in healthy subjects, CPAP + HFNC at 30 L/min seemed to be the best combination.

PM2.5 vertical variation during a fog episode in a rural area of the Yangtze River Delta, China

A dense radiation fog event occurred at the Shouxian site, Anhui Province, China, from the evening of January 2 to noon on January 3, 2017. During this event, vertical profiles of particulate matter (PM) and meteorological parameters within the lower troposphere (0–1000 m) were collected using a tethered balloon. This study assessed the evolution of the PM2.5 profile with the planetary boundary layer (PBL) structure and the effects of fog on the PM2.5 concentration. The results showed the following: (1) At the surface, the average diurnal variation in Aitken mode, accumulation mode and coarse mode particles had bimodal patterns before fog formation and was mainly influenced by diurnal variation in the mixing level depth (MLD). The aerosol number concentrations decreased remarkably, and the PM2.5 was strongly scavenged from 150 μg/m3 to 45 μg/m3 during the fog process. (2) In the vertical direction, the PM2.5 distribution was affected by the PBL height and the vertical fog structure. At 05:00 LT (local time) (i.e., early morning before the fog event), the PM2.5 concentration was slightly higher in the stable layer (260 μg/m3) than in the residual layer (200 μg/m3). At 14:00 LT (haze period), PM2.5 was well mixed below 500 m, with a concentration of 310 μg/m3. After 20:00 LT, when fog formed, PM2.5 was scavenged from the surface to the upper layers, and the scavenging height was controlled by the fog top height. (3) The vertical development of fog was promoted by turbulent mixing and radiation cooling at the fog top. Turbulent mixing enhanced the particle scavenging efficiency of fog droplets by the collision-coalescence process. The PM2.5 scavenging height was corresponded to the turbulence height. Therefore, turbulence development in the fog was the essential dynamic factor driving PM2.5 reduction.

Material degradation of cfrp-to-steel joints subjected to salt fog

Effects of salt fog on CFRP-steel bonded joints were studied via simulation by accelerated cycles. CFRP-to-steel double strap joints made of two different types of laminates were subjected to salt fog cycles for 5000 h and Mode-II tests conducted to assess the degradation of their bond capacity at selected time stages of the process. Different mechanisms causing strength losses were found and analyzed. Results showed that the bond capacity of joints increased initially but was reduced at later stages. Corrosion debonding took place in the chamber between 5,000 h and 10,000 h prior to the application of external loading. Combined Attenuated Total Reflectance-Fourier transform infrared (FTIR) spectroscopy and Dynamic Mechanical Analysis (DMA) results showed that severe degradation at the interface of carbon fibers and resin only took place for one type of laminate. Galvanic corrosion was also analyzed and coupling between CFRP and steel developed due to the corrosion product depositions over the components leading to the degradation of the same type of laminate.

Optimisation of transmission map for improved image defogging

Outdoor images taken in foggy weather are not suitable for automation due to low contrast. It is a challenging task to remove fog from images specially when the image contains large sky region. The authors propose dark channel-based single image defogging technique to estimate atmospheric light which represents the amount of luminance in a scene in the absence of fog. This atmospheric light is used to reconstruct fog-free image with a transmission map. Transmission map represents the effect of fog with respect to depth in image. In this study, they propose four transmission maps to reconstruct the images with different colour contrast. Proposed method adaptively selects a transmission map depending upon the fog density to reconstruct image with optimal colour contrast. The transmission map is refined by applying Laplacian filter followed by the guided filter. Previously, dark channel prior based methods were considered to be less effective for images with large sky region, but the proposed method reconstructs better result consistently for such images, independent of the density of the fog. Experimental results show that images reconstructed by proposed method are qualitatively better than the previously proposed methods.

Propagation properties of sub-millimeter waves in foggy conditions

The propagation of millimeter (MMW) and submillimeter (terahertz, THz) waves in the atmosphere is subject to absorptive and dispersive effects. The resulting attenuation and temporal group delay increase in cloudy and hazy weather. In this work, the effects of water droplets suspended in the air on the propagation of electromagnetic radiation in submillimeter waves are studied theoretically and experimentally. A comparison is made between the link budget in THz frequencies and the expected attenuation for free space optics (FSO) links. Using the modified millimeter-wave propagation model, the frequency-dependent attenuation and group delay are expressed in terms of the complex refractivity of the atmospheric medium. The theory is employed to study the effect of fog and clouds on the accuracy of a frequency-modulated continuous-wave high-resolution radar operating at 330 GHz. In an experiment, the propagation of MMW was studied in a controlled fog chamber for various ranges of visibility, even below 1 m. The resulting attenuation and group delay of submillimeter waves were measured, while the properties of fog (optical visibility distance and water content) were monitored using FSO techniques. Apart from attenuation, the incremental group delay caused by fog also affected the accuracy of the radar. The experimental results were compared with those of an analytical model and were in good agreement even for very low visibility in very foggy conditions. Dispersive effects should be considered in the design of remote sensing radars operating in the MMW and THz regimes.

Effects of temporary fogging and defogging in plastic scintillators

Recent studies have shown that under certain environmental conditions, plastic scintillators which are used in a variety of applications in outdoor environments develop defects called “fogging”, resulting in a reduced useful lifetime and increased maintenance cost. Applications of plastic scintillators include scanning recycled steel going into a processing plant, personnel portals to scan employees, and scanning cargo and cars crossing borders of many countries. In this report, fogging was studied in conventional PVT and PS-based plastic scintillators, both field aged and freshly cast. A new fogging-resistant PVT-based formulation developed by scientists at Lawrence Livermore National Laboratory (LLNL) was tested as well. We used accelerated aging experiments via temperature and humidity cycling in controlled laboratory conditions to create observable temporary fogging defects in small samples (≤1 in3). Photoluminescence and optical transmission studies were used to evaluate the effect of the fogging. The time evolution of the induced temporary fogging formation and defogging (i.e. fading of defects in ambient conditions over time) were recorded using optical microscopy, time-lapse photography, and gravimetric analysis.

Single Image Defogging Based on Illumination Decomposition for Visual Maritime Surveillance.

Single image fog removal is important for surveillance applications and many defogging methods have been proposed, recently. Due to the adverse atmospheric conditions, the scattering properties of foggy images depend on not only the depth information of scene, but also the atmospheric aerosol model, which has more prominent influence on illumination in a fog scene than that in a haze scene. However, recent defogging methods confuse haze and fog, and they fail to consider fully about the scattering properties. Thus, these methods are not sufficient to remove fog effects, especially for images in maritime surveillance. Therefore, this paper proposes a single image defogging method for visual maritime surveillance. Firstly, a comprehensive scattering model is proposed to formulate a fog image in the glow-shaped environmental illumination. Then, an illumination decomposition algorithm is proposed to eliminate the glow effect on the airlight radiance and recover a fog layer, in which objects at the infinite distance have uniform luminance. Secondly, a transmission-map estimation based on the non-local haze-lines prior is utilized to constrain the transmission map into a reasonable range for the input fog image. Finally, the proposed illumination compensation algorithm enables the defogging image to preserve the natural illumination information of the input image. In addition, a fog image dataset is established for visual maritime surveillance. The experimental results based on the established dataset demonstrate that the proposed method can outperform the state-of-the-art methods in terms of both the subjective and objective evaluation criteria. Moreover, the proposed method can effectively remove fog and maintain naturalness for fog images.

5G-28 GHz Signal Transmission Over Hybrid All-Optical FSO/RF Link in Dusty Weather Conditions

5G wireless networks promise to provide massive bandwidth for various types of connections. In such networks, the backhaul/fronthaul sections should be easy to deploy and support the required high bandwidth. To improve the free space optic (FSO) link bandwidth so that it can replace fiber cables and support 5G networks, all-optical FSO systems were proposed which exploit advanced modulation formats in the transmitter side and coherent detection in the receiver side. However, such links will suffer much under harsh outdoor environment, especially under fog and dust conditions than traditional FSO links that have limited bandwidth. Effect of fog on such links has been investigated in the literature. However, the dust effect is not covered. In this paper, we first experimentally analyzed the effects of dust storms on the performance of an all-optical FSO link carrying a 1-Gbaud/16-quadrature amplitude modulation 5G signal. The results demonstrate that the all-optical FSO link is significantly affected by low visibility range, with severe bit-error-rate (BER), and error vector magnitude (EVM) limits appearing at a 50-m visibility range for a 2.7-m channel length. For a visibility range greater than 200-m, the BER and EVM were improved to 10−9 and 5.5% of the root mean square, respectively. Furthermore, the analysis showed that the dust storm condition introduces flat fading over the frequency range under study, i.e., 21–29 GHz. Second, a comparison between FSO and radio frequency (RF) channels under the same dusty conditions were performed. The results showed that the effects of the dust storm are negligible for the RF link which makes it suitable as a backup for FSO link under severe dust conditions. Finally, a hybrid cascaded FSO/RF link was installed and analyzed in terms of visibility range, BER, and EVM.

Response of GAFChromic® HD-V2 film dosimeter in 10-300 Gy dose range for radiation testing of electronic devices

The study reported in this paper aimed to investigate the response of a GAFChromic? HD-V2 film dosimeter in the dose range between 10 and 300 Gy, normally used to perform irradiation tests on electronic devices with a 60Co gamma-ray irradiator. The well-defined linearity of response in terms of absorbance as a function of absorbed dose, easiness of handling and data analysis of irradiated dosimeters, reproducibility, stability, and insensitivity to visible light and most of the environmental parameters, make HD-V2 film a flexible, inexpensive and reliable dose measurement device. The study has shown a fogging effect of the dosimeter response since its value changes over time. Strategies and adequate precautions to take into account changes on HD-V2 film physical properties for calibration and routine use in industrial applications, with a specific reference to radiation testing of electronic devices, have been discussed.

Multi-scale Retinex Algorithm to Evaluate the Fogging Effect in Different Color Space Images

Retinex; Defogging; YCbCr

Analyzing the effect of fog weather conditions on driver lane-keeping performance using the SHRP2 naturalistic driving study data

Introduction: Driving in foggy weather conditions has been recognized as a major safety concern for many years. Driver behavior and performance can be negatively affected by foggy weather conditions due to the low visibility in fog. A number of previous studies focused on driver performance and behavior in simulated environments. However, very few studies have examined the impact of foggy weather conditions on specific driver behavior in naturalistic settings. Method: This study utilized the second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS) dataset to evaluate driver lane-keeping behavior in clear and foggy weather conditions. Preliminary descriptive analysis was conducted and a lane-keeping model was developed using the ordered logistic regression approach to achieve the study goals. Results: This study found that individual variables such as visibility, traffic conditions, lane change, driver marital status, and geometric characteristics, as well as some interaction terms (i.e., weather and gender, surface condition and driving experience, speed limit and mileage last year) significantly affect lane-keeping ability. An important finding of this study illustrated that affected visibility caused by foggy weather conditions decreases lane-keeping ability significantly. More specifically, drivers in affected visibility conditions showed 1.37 times higher Standard Deviation of Lane Position (SDLP) in comparison with drivers who were driving in unaffected visibility conditions. Conclusions: These results provide a better understanding of driver lane-keeping behavior and driver perception of foggy weather conditions. Moreover, the results might be used to improve Lane Departure Warning (LDW) systems algorithm by allowing them to account for the effects of fog on visibility. Practical Applications: These results provide a better understanding of driver lane-keeping behavior and driver perception of foggy weather conditions. Moreover, the results might be used to improve Lane Departure Warning (LDW) systems algorithm by allowing them to account for the effects of fog on visibility.

The fog regime in a tropical montane cloud forest in Brazil and its effects on water, light and microclimate

Fog is a frequent phenomenon in tropical montane cloud forests (TMCFs). These ecosystems are important to the water supply of adjacent lowland regions which is largely determined by the effect of fog on TCMF evapotranspiration rates and hydrological balance. Understanding fog regimes at fine-grained temporal resolution is key to predict plant functioning and effects of climatic changes in TMCFs, especially on key hydrological services that these forests provide. Here, we combine a suite of micrometeorological and hydrological sensors with a visibilimeter, a reliable sensor of fog occurrence, to gather fine-grained information on fog frequency, duration and timing and its contribution to water inputs, light availability and microclimatic variability in a Brazilian TMCF. Despite occurring on 64% of days, fog was highly variable at daily and seasonal scales, occurring mostly at night and during the rainy season. Approximately 1200 liters of fog were intercepted per tree per year (259 mm or 10.7% of total net precipitation). Fog also increased net precipitation provided by concomitant fog-rain events. Monthly net precipitation to precipitation ratio, a measure of how much water arrives at the soil and how much evaporates or is intercepted by the canopy, was 0.96 - much higher than the 0.72 typical of lowland rainforest, due to the additional fog water input on TMCF. Cloudiness, and not fog, dominated light availability and inter-day microclimatic variability (air temperature and vapor pressure deficit). High fog regime variability indicates that understanding TMCFs functioning requires integration of plant function with fine-grained data of fog and cloud occurrence. We discuss possible consequences of our results to TMCFs plant functioning.

Study on the influence of fog and haze on solar radiation based on scattering-weakening effect

In the existing literature, there are many studies focused on the scattering-weakening effect of different atmospheric constituents (gas, aerosols, liquid particles, etc.) on solar radiation, but few quantitative studies on the scattering-weakening effect of solar radiation by fog and haze. In this paper, the scattering-weakening effect of fog and haze on daily global solar radiation is investigated based on principal component analysis (PCA). First, the influence of different fog and haze levels on daily global solar radiation is analyzed. For example, in Tianjin, China, the average weakening degree is as follows: they are 18.66%, 26.37%, 37.32%, and 45.58% in light, moderate, heavy, and serious pollution respectively. Second, 7 types of global solar radiation weakening models (GSRW models) based on air quality index (AQI) are proposed. The measured data indicates solar radiation is gradually weakened with the increase of AQI, but the weakening speed gradually slows down. Besides, GSRW models are applied to six Chinese regions with fog and haze, and the results show that these models have good applicability (the average R value is 0.730, RMSE is 0.059 and MAPE is 9.430), especially for heavy air pollution regions.

Contrasting effects of fog frequency on the radial growth of two tree species in a Mediterranean-temperate ecotone

The performance and persistence of rear-edge tree populations are relevant issues for conserving biodiversity because these stands harbor high intraspecific biodiversity and play a key role during periods of climate change. The occurrence of these populations is associated with the influence of heterogeneous topography, creating suitable refugia with regionally rare environmental conditions. Climate is changing at a global-scale, but little is known about the long-term impact on local climatic singularities and the associated taxa. We analyzed tree-ring growth chronologies of the two species (Fagus sylvatica and Quercus ilex) forming the evergreen-deciduous forest ecotone, constitutive of the rear-edge of F. sylvatica distribution. The study area is a coastal range with frequent fog immersion, which has been hypothesized to favor the persistence of F. sylvatica in Mediterranean peninsulas. We analyzed the long-term effect of fog on tree growth along a topographical gradient and the sensitivity of growth to rainfall and temperature. The annual number of foggy days has decreased by 62% over the last four decades, concomitant with increasing temperatures. Fog frequency was a relevant factor determining tree growth; fog during summer had positive effects on F. sylvatica growth mainly through a temperature buffering effect. The positive effect of fog on the growth of Q. ilex, however, was likely caused by a collinearity with rainfall. Q. ilex growth was less sensitive to climate than F. sylvatica, but growth of both species was enhanced by a positive early-summer water balance. Our results indicate that a decrease in fog frequency and an increase in temperature may generally benefit Q. ilex in this forest ecotone. Although future changes in rainfall and temperature matter most for the fate of rear-edge tree populations, local climatic singularities such as fog should also be considered. Those can have complementary effects that can swing the balance in ecotones and rear-edge tree populations such as those studied here.

Examining the effect of adverse weather on road transportation using weather and traffic sensors.

Adverse weather related to reduced visibility caused by fog and rain can seriously affect the mobility and safety of drivers. It is meaningful to develop effective intelligent transportation system (ITS) strategies to mitigate the negative effects of these different types of adverse weather related to reduced visibility by investigating the effect of rain and fog on traffic parameters. A number of previous researches focused on analyzing the effect of adverse weather related to reduced visibility by using simulated traffic and weather data. There are few researchers that addressed the impact of adverse weather instances using real-time data. Moreover, this paper conducts comprehensive investigation to clearly compare the changes of driving behavior and traffic parameters in adverse weather including fog and rain using real-time traffic and weather data collected by advanced vehicle-based traffic sensors and weather sensors. After some preliminary analysis, the analysis of variance method (ANOVA) was applied to further compare the significance of effects of these two kinds of adverse weather on traffic parameters. The conditional regression models were employed finally to explore the relationship between these two types of adverse weather and traffic parameters. The results would be beneficial to develop effective intelligent traffic control countermeasures under these different types of adverse weather conditions related to reduced visibility.

Fog Effect Generation from Approximated Image Depth

Fog Effect Generation from Approximated Image Depth

An opportunistic resource management model to overcome resource‐constraint in the Internet of Things

SummaryExperts believe that the Internet of Things (IoT) is a new revolution in technology and has brought many advantages for our society. However, there are serious challenges in terms of information security and privacy protection. Smart objects usually do not have malware detection due to resource limitations and their intrusion detection work on a particular network. Low computation power, low bandwidth, low battery, storage, and memory contribute to a resource‐constrained effect on information security and privacy protection in the domain of IoT. The capacity of fog and cloud computing such as efficient computing, data access, network and storage, supporting mobility, location awareness, heterogeneity, scalability, and low latency in secure communication positively influence information security and privacy protection in IoT. This study illustrates the positive effect of fog and cloud computing on the security of IoT systems and presents a decision‐making model based on the object's characteristics such as computational power, storage, memory, energy consumption, bandwidth, packet delivery, hop‐count, etc. This helps an IoT system choose the best nodes for creating the fog that we need in the IoT system. Our experiment shows that the proposed approach has less computational, communicational cost, and more productivity in compare with the situation that we choose the smart objects randomly to create a fog.

The influence of humidity on the performance of a low-cost air particle mass sensor and the effect of atmospheric fog

Abstract. While low-cost particle sensors are increasingly being used in numerous applications, most of them have no heater or dryer at the inlet to remove water from the sample before measurement. Deliquescent growth of particles and the formation of fog droplets in the atmosphere can lead to significant increases in particle number concentration (PNC) and mass concentrations reported by such sensors. We carried out a detailed study using a Plantower PMS1003 low-cost particle sensor, both in the laboratory and under actual ambient field conditions, to investigate its response to increasing humidity and the presence of fog in the air. We found significant increases in particle number and mass concentrations at relative humidity above about 75 %. During a period of fog, the total PNC increased by 28 %, while the PNC larger than 2.5 µm increased by over 50 %. The PM10 concentration reported by the PMS1003 was 46 % greater than that on the standard monitor with a charcoal dryer at the inlet. While there is a causal link between particle pollution and adverse health effects, the presence of water on the particles is not harmful to humans. Therefore, air quality standards for particles are specifically limited to solid particles and standard particle monitoring instruments are fitted with a heater or dryer at the inlet to remove all liquid material from the sample before the concentrations are measured. This study shows that it is important to understand that the results provided by low-cost particle sensors, such as the PMS1003, cannot be used to ascertain if air quality standards are being met.

Vision improvement system using image processing technique for adverse weather condition of opencast mines

This paper deals with a vision improvement system (VIS) developed using real-time image processing technique by CSIR-Central Institute of Mining and Fuel Research, Dhanbad aiming at providing comparatively clear vision to the operators of HEMM (Heavy Earth Moving Machinery) in foggy weather condition in opencast mines. It can also be used in deteriorated visibility situation due to mist, haze, smog, etc. while driving other vehicles also. In adverse weather, mining processes cannot be carried out during one-third of a day due to problem of perceptibility which reduces production rate of opencast mines. The developed system amplifies colour, sets the brightness and contrast to the input video to make objects more visible by reducing the effect of fog, mist, haze and smog. In order to enable quick real time operation, a fast CPU with dedicated graphics processing unit is used which is well suited for intensive data processing; because of its high computational efficiency and robustness, the developed system is able to operate at high frame rate and it is suitable for real-time driving assistance in adverse weather condition.