skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Explore Research Products in the PAR
It may take a few hours for recently added research products to appear in PAR search results.


Title: Water Level Detection in Adverse Weather Conditions Using Security Cameras
Various techniques in computer vision have been proposed for water level detection. However, existing methods face challenges during adverse conditions including snow, fog, rain, and nighttime. In this paper, we introduce a novel approach that analyzes images for water level detection by incorporating a deblurring process to increase image clarity. By employing real-time object detection technique YOLOv5, we show that the proposed approach can achieve significantly improved precision, during both daytime and nighttime under under challenging weather circumstances.  more » « less
Award ID(s):
2231557
PAR ID:
10525905
Author(s) / Creator(s):
; ; ; ; ;
Publisher / Repository:
IEEE
Date Published:
Edition / Version:
SoutheastCon 2024
ISBN:
979-8-3503-1710-7
Page Range / eLocation ID:
187 to 193
Format(s):
Medium: X
Location:
Atlanta, GA, USA
Sponsoring Org:
National Science Foundation
More Like this
  1. ; ; ; (, ACM)
    Nighttime sidewalk illumination has a significant and unequal influence on where and whether pedestrians walk at night. Despite the importance of pedestrian lighting, there is currently no approach for measuring and communicating how humans experience nighttime sidewalk light levels at scale. We introduce NightLight, a new sensing approach that leverages the ubiquity of smartphones by re-appropriating the built-in light sensor—traditionally used to adapt screen brightness—to sense pedestrian nighttime lighting conditions. We validated our technique through in-lab and street-based evaluations characterizing performance across phone orientation, phone model, and varying light levels demonstrating the ability to aggregate and map pedestrian-oriented light levels with unaltered smartphones. Additionally, to examine the impact of light level data on pedestrian route choice, we conducted a qualitative user study with 13 participants using a standard map vs. one with pedestrian lighting data from NightLight. Our findings demonstrate that people changed their routes in preference of well-light routes during nighttime walking. Our work has implications for improving personalized navigation, understanding pedestrian route choice, and expanding passive urban sensing. 
    more » « less
  2. ; ; ; ; ; ; (, Water Resources Research)
    Abstract Heat storage change (HSC) is a crucial component of lake's thermal energy budget. Conventional temperature profile based models of HSC require location specific parameters such as lakebed topography. Based on the half‐order time‐derivative formula of heat fluxes, an analytical model was formulated for estimating HSC from water surface temperature and solar radiation without using geography dependent parameters. The proposed model was tested against field measurements at Poyang Lake, a shallow inland lake, which has pronounced seasonal variations in water level and lake area. Our analysis indicates that the model accurately simulates diurnal HSC with a coefficient of determination of 0.94 and a root mean squared error (RMSE) of 77.5 ± 21.6 Wm−2for the study period. Larger nighttime RMSE (75.0 ± 26.8 Wm−2) than the daytime value (55.1 ± 19.7 W m−2) is attributable to larger measurement errors of nighttime turbulent fluxes. The estimation of HSC independent of temperature profile and lake‐specific parameters by the proposed model facilitates remote sensing monitoring the HSC of global water bodies. 
    more » « less
  3. ; ; (, Sustainability)
    Animal–vehicle collision is a common danger on highways, especially during nighttime driving. Its likelihood is affected not only by the low visibility during nighttime hours, but also by the unpredictability of animals’ actions when a vehicle is nearby. Extensive research has shown that the lack of visibility during nighttime hours can be addressed using thermal imaging. However, to our knowledge, little research has been undertaken on predicting animal action through an animal’s specific poses while a vehicle is moving. This paper proposes a new system that couples the use of a two-dimensional convolutional neural network (2D-CNN) and thermal image input, to determine the risk imposed by an animal in a specific pose to a passing automobile during nighttime hours. The proposed system was tested using a set of thermal images presenting real-life scenarios of animals in specific poses on the roadside and was found to classify animal poses accurately in 82% of cases. Overall, it provides a valuable basis for implementing an automotive tool to minimize animal–vehicle collisions during nighttime hours. 
    more » « less
  4. ; (, Atmospheric chemistry and physics discussion)
    The daytime oxidation of biogenic hydrocarbons is attributed to both OH radicals and O3, while nighttime chemistry is dominated by the reaction with O3 and NO3 radicals. Here, the diurnal pattern of Secondary Organic Aerosol (SOA) originating from biogenic hydrocarbons was intensively evaluated under varying environmental conditions (temperature, humidity, sunlight intensity, NOx levels, and seed conditions) by using the UNIfied Partitioning Aerosol phase Reaction (UNIPAR) model, which comprises multiphase gas-particle partitioning and in-particle chemistry. The oxidized products of three different hydrocarbons (isoprene, α-pinene, and β-caryophyllene) were predicted by using near explicit gas mechanisms for four different oxidation paths (OH, O3, NO3, and O(3P)) during day and night. The gas mechanisms implemented the Master Chemical Mechanism (MCM v3.3.1), the reactions that formed low volatility products via peroxy radical (RO2) autoxidation, and self- and cross-reactions of nitrate-origin RO2. In the model, oxygenated products were then classified into volatility-reactivity base lumping species, which were dynamically constructed under varying NOx levels and aging scales. To increase feasibility, the UNIPAR model that equipped mathematical equations for stoichiometric coefficients and physicochemical parameters of lumping species was integrated with the SAPRC gas mechanism. The predictability of the UNIPAR model was demonstrated by simulating chamber-generated SOA data under varying environments day and night. Overall, the SOA simulation decoupled to each oxidation path indicated that the nighttime isoprene SOA formation was dominated by the NO3-driven oxidation, regardless of NOx levels. However, the oxidation path to produce the nighttime α-pinene SOA gradually transited from the NO3-initiated reaction to ozonolysis as NOx levels decreased. For daytime SOA formation, both isoprene and α-pinene were dominated by the OH-radical initiated oxidation. The contribution of the O(3P) path to all biogenic SOA formation was negligible in daytime. Sunlight during daytime promotes the decomposition of oxidized products via photolysis and thus, reduces SOA yields. Nighttime α-pinene SOA yields were significantly higher than daytime SOA yields, although the nighttime α-pinene SOA yields gradually decreased with decreasing NOx levels. For isoprene, nighttime chemistry yielded higher SOA mass than daytime at the higher NOx level (isoprene/NOx > 5 ppbC/ppb). The daytime isoprene oxidation at the low NOx level formed epoxy-diols that significantly contributed SOA formation via heterogeneous chemistry. For isoprene and α-pinene, daytime SOA yields gradually increased with decreasing NOx levels. The daytime SOA produced more highly oxidized multifunctional products and thus, it was generally more sensitive to the aqueous reactions than the nighttime SOA. β-Caryophyllene, which rapidly oxidized and produced SOA with high yields, showed a relatively small variation in SOA yields from changes in environmental conditions (i.e., NOx levels, seed conditions, and diurnal pattern), and its SOA formation was mainly attributed to ozonolysis day and night. To mimic the nighttime α-pinene SOA formation under the polluted urban atmosphere, α-pinene SOA formation was simulated in the presence of gasoline fuel. The simulation suggested the growth of α-pinene SOA in the presence of gasoline fuel gas by the enhancement of the ozonolysis path under the excess amount of ozone, which is typical in urban air. We concluded that the oxidation of the biogenic hydrocarbon with O3 or NO3 radicals is a source to produce a sizable amount of nocturnal SOA, despite of the low emission at night. 
    more » « less
  5. ; ; ; ; ; ; ; ; ; ; et al (, Proceedings of the National Academy of Sciences)
    A radiative vapor condenser sheds heat in the form of infrared radiation and cools itself to below the ambient air temperature to produce liquid water from vapor. This effect has been known for centuries, and is exploited by some insects to survive in dry deserts. Humans have also been using radiative condensation for dew collection. However, all existing radiative vapor condensers must operate during the nighttime. Here, we develop daytime radiative condensers that continue to operate 24 h a day. These daytime radiative condensers can produce water from vapor under direct sunlight, without active consumption of energy. Combined with traditional passive cooling via convection and conduction, radiative cooling can substantially increase the performance of passive vapor condensation, which can be used for passive water extraction and purification technologies. 
    more » « less
  • Citation Formats
  • MLA
  • APA
  • Chicago
  • BibTeX
  • Save / Share this Record
  • Send to Email