UAV-borne LiDAR and morphological filtering for automatic monitoring of alpine protective infrastructure

2021 ◽  
Author(s):  
Philip Taupe ◽  
Alexander Preinerstorfer ◽  
Philipp Amon
Keyword(s):  
Automatic Monitoring ◽  
Morphological Filtering

AUTOMATED SYSTEM FOR MONITORING THE VEGETATIVE STATE OF PLANTS

2020 ◽  
Author(s):  
S.B. Kudryashev ◽  
◽  
V.A. Naumenko ◽  
K.V. Lamanova ◽  
R.D. Belashov ◽  
...  
Keyword(s):  
Infrared Spectrum ◽  
Vegetative State ◽  
Automatic Monitoring ◽  
Automated System

The article presents a system for automatic monitoring of plant conditions, which is based on a specially developed method for processing photographs in the infrared spectrum. The paper substantiates the choice of a quadrocopter as a transport platform, which provides mobility to the system.

In-situ automatic observations of ice thickness of seas

2012 ◽  
Vol 19 (3) ◽  
pp. 583-592 ◽  
Author(s):  
Yinke Dou ◽  
Xiaomin Chang
Keyword(s):  
Sea Ice ◽  
New Technologies ◽  
Capacitive Sensor ◽  
Automatic Monitoring ◽  
Ice Thickness ◽  
In Situ Observation ◽  
Glacier Surface ◽  
Sea Ice Thickness ◽  
Surface Ice

Abstract Ice thickness is one of the most critical physical indicators in the ice science and engineering. It is therefore very necessary to develop in-situ automatic observation technologies of ice thickness. This paper proposes the principle of three new technologies of in-situ automatic observations of sea ice thickness and provides the findings of laboratory applications. The results show that the in-situ observation accuracy of the monitor apparatus based on the Magnetostrictive Delay Line (MDL) principle can reach ±2 mm, which has solved the “bottleneck” problem of restricting the fine development of a sea ice thermodynamic model, and the resistance accuracy of monitor apparatus with temperature gradient can reach the centimeter level and research the ice and snow substance balance by automatically measuring the glacier surface ice and snow change. The measurement accuracy of the capacitive sensor for ice thickness can also reach ±4 mm and the capacitive sensor is of the potential for automatic monitoring the water level under the ice and the ice formation and development process in water. Such three new technologies can meet different needs of fixed-point ice thickness observation and realize the simultaneous measurement in order to accurately judge the ice thickness.

Automatic monitoring of denitrification rates and capacities in activated sludge processes using fluorescence or redox potential

1998 ◽  
Vol 37 (12) ◽  
pp. 121-129 ◽  
Author(s):  
S. Isaacs ◽  
Terry Mah ◽  
S. K. Maneshin
Keyword(s):  
Biological Activity ◽  
Activated Sludge ◽  
Redox Potential ◽  
Treatment Plant ◽  
Automatic Monitoring ◽  
Organic Substrate ◽  
Anoxic Zone ◽  
Optimal Dosing ◽  
Denitrifying Microorganisms ◽  
Activated Sludge Processes

A novel method is described to automatically estimate several key parameters affecting denitrification in activated sludge processes: the nitrate concentration, the denitrification capacity, and the maximum (substrate unlimited) and actual denitrification rates. From these, the concentration of active denitrifying microorganisms and the quality of available organic substrate pool can be estimated. Additionally, a modification of the method allows the determination of the efficacy of various carbon substrates to enhance denitrification, and this can be used to determine optimal dosing rates of an external carbon source. The method is based on measurements of either fluorescence or redox potential (ORP) in an isolated mini-reactor, the Biological Activity Meter (BAM), situated in the anoxic zone of the wastewater treatment plant. Advantages of the method are that it is in situ, operating at the same temperature as in the measured anoxic zone, requires no pumps or pipes for mixed liquor sampling, consumes little or no reagents, and uses measurement signals which are instantaneous and low maintenance, one of which provides a direct measure of biological activity.

scholarly journals Assessment of Automatically Monitored Water Levels and Water Quality Indicators in Rivers with Different Hydromorphological Conditions and Pollution Levels in Greece

Hydrology ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 86
Author(s):  
Angeliki Mentzafou ◽  
George Varlas ◽  
Anastasios Papadopoulos ◽  
Georgios Poulis ◽  
Elias Dimitriou
Keyword(s):  
Water Quality ◽  
Time Series ◽  
Quality Indicators ◽  
High Frequency ◽  
Automatic Monitoring ◽  
Water Levels ◽  
High Temporal Resolution ◽  
Water Quality Indicators ◽  
Pollution Levels ◽  
Riverine Ecosystems

Water resources, especially riverine ecosystems, are globally under qualitative and quantitative degradation due to human-imposed pressures. High-temporal-resolution data obtained from automatic stations can provide insights into the processes that link catchment hydrology and streamwater chemistry. The scope of this paper was to investigate the statistical behavior of high-frequency measurements at sites with known hydromorphological and pollution pressures. For this purpose, hourly time series of water levels and key water quality indicators (temperature, electric conductivity, and dissolved oxygen concentrations) collected from four automatic monitoring stations under different hydromorphological conditions and pollution pressures were statistically elaborated. Based on the results, the hydromorphological conditions and pollution pressures of each station were confirmed to be reflected in the results of the statistical analysis performed. It was proven that the comparative use of the statistics and patterns of the water level and quality high-frequency time series could be used in the interpretation of the current site status as well as allowing the detection of possible changes. This approach can be used as a tool for the definition of thresholds, and will contribute to the design of management and restoration measures for the most impacted areas.

scholarly journals An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 343
Author(s):  
Kim Bjerge ◽  
Jakob Bonde Nielsen ◽  
Martin Videbæk Sepstrup ◽  
Flemming Helsing-Nielsen ◽  
Toke Thomas Høye
Keyword(s):  
Computer Vision ◽  
Deep Learning ◽  
Vision System ◽  
Low Cost ◽  
Light Trap ◽  
Automatic Monitoring ◽  
Light Sources ◽  
Monitoring Methods ◽  
Computer Vision System ◽  
Substantial Investment

Insect monitoring methods are typically very time-consuming and involve substantial investment in species identification following manual trapping in the field. Insect traps are often only serviced weekly, resulting in low temporal resolution of the monitoring data, which hampers the ecological interpretation. This paper presents a portable computer vision system capable of attracting and detecting live insects. More specifically, the paper proposes detection and classification of species by recording images of live individuals attracted to a light trap. An Automated Moth Trap (AMT) with multiple light sources and a camera was designed to attract and monitor live insects during twilight and night hours. A computer vision algorithm referred to as Moth Classification and Counting (MCC), based on deep learning analysis of the captured images, tracked and counted the number of insects and identified moth species. Observations over 48 nights resulted in the capture of more than 250,000 images with an average of 5675 images per night. A customized convolutional neural network was trained on 2000 labeled images of live moths represented by eight different classes, achieving a high validation F1-score of 0.93. The algorithm measured an average classification and tracking F1-score of 0.71 and a tracking detection rate of 0.79. Overall, the proposed computer vision system and algorithm showed promising results as a low-cost solution for non-destructive and automatic monitoring of moths.

scholarly journals Soft morphological filtering using hypergraphs

2021 ◽  
Vol 1085 (1) ◽  
pp. 012038
Author(s):  
Nuja M Unnikrishnan ◽  
Mini Tom ◽  
V Bino Sebastian ◽  
K V Thomas
Keyword(s):  
Morphological Filtering

scholarly journals Study on Fault Diagnosis Method of Planetary Gearbox Based on Turn Domain Resampling and Variable Multi-Scale Morphological Filtering

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 52
Author(s):  
Tongtong Liu ◽  
Lingli Cui ◽  
Chao Zhang
Keyword(s):  
Frequency Conversion ◽  
Interpolation Method ◽  
Spline Interpolation ◽  
Operating Efficiency ◽  
Planetary Gearbox ◽  
Noise Interference ◽  
Multi Scale ◽  
Morphological Filtering ◽  
Diagnosis Method ◽  
Simulation Signal

The turn domain resampling (TDR) method is proposed in the paper on the basis of the existing angle domain resampling for solving the problem of non-fixed fault frequency under variable working conditions. TDR can select the appropriate sampling order according to the influence of frequency conversion, which avoided the error caused by the spline interpolation method. It can provide accurate parameters for the subsequent calculation of the equivalent frequency order. Variable multi-scale morphological filtering (VMSMF) method is proposed for the purpose of further reducing the interference of noise in resampling signal to feature extraction. VMSMF adaptively selects structural elements according to the parameter change of impact signal to make its scale more targeted. It only needs to calculate once using the optimal structural unit for a particular impact, and the filtering accuracy and operating efficiency have been greatly improved. The main steps of this article are as follows. First, the TDR is used to resample the original signal as to get the resampling signal which is still submerged by the strong noise. In the second step, VMSMF is used to filter the resampling signal to obtain the signal with less noise interference. Finally, the fault characteristics of the filtering signal was extracted and compared with the possible fault frequency calculated by the sampling parameters provided by resampling, so as to determine the fault type of the planetary gearbox. By analyzing the simulation signal and the experimental signal respectively, this method can find out the corresponding fault characteristics effectively.

A performance enhanced time-varying morphological filtering method for bearing fault diagnosis

Measurement ◽  
2021 ◽  
Vol 176 ◽  
pp. 109163
Author(s):  
Bingyan Chen ◽  
Dongli Song ◽  
Weihua Zhang ◽  
Yao Cheng ◽  
Zhiwei Wang
Keyword(s):  
Fault Diagnosis ◽  
Time Varying ◽  
Filtering Method ◽  
Bearing Fault ◽  
Bearing Fault Diagnosis ◽  
Morphological Filtering ◽  
A Performance

scholarly journals A Knowledge-Based Algorithm for Automatic Monitoring of Orthodontic Treatment: The Dental Monitoring System. Two Cases

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1856
Author(s):  
Silvia Caruso ◽  
Sara Caruso ◽  
Marianna Pellegrino ◽  
Rayan Skafi ◽  
Alessandro Nota ◽  
...  
Keyword(s):  
Adult Patient ◽  
Remote Monitoring ◽  
Digital Technology ◽  
Orthodontic Treatment ◽  
Dental Treatment ◽  
Automatic Monitoring ◽  
Software As A Service ◽  
Knowledge Based ◽  
First Case ◽  
Service Application

Background: In the dental field, digital technology has created new opportunities for orthodontists to integrate their clinical practice, and for patients to collect information about orthodontics and their treatment, which is called “teledentistry.” Dental monitoring (DM) is a recently introduced orthodontic application that combines safe teledentistry with artificial intelligence (AI) using a knowledge-based algorithm, allowing an accurate semi-automatic monitoring of the treatment. Dental Monitoring is the world’s first SaaS (Software as a Service) application designed for remote monitoring of dental treatment, developed in Paris, France, with Philippe Salah as the Co-founder and CEO. Cases presentation: This report describes two cases in which DM system was essential to achieve the control of certain movements: it was possible to follow the movement, even if complex, such as the anterior cross of an adult patient and a lack of space in the canine of the growing patient. The software analyzed the fit and retention of the aligner, thus ensuring correct biomechanics. They were treated during the COVID-19 pandemic lockdown with aligners. The first case is a growing patient who was monitored during an interceptive orthodontic treatment to manage a retained upper canine. The second case is an adult patient forced to finalize his treatment of upper lateral incisor crossbite. The software analyzed the fit and retention of the aligner, thus ensuring correct biomechanics. Conclusions: DM system appears to be a promising method, useful for improving the interaction between doctor and patient, generally acceptable and useful to patients, even in critical clinical situations, at least in cases with optimal compliance and ability to use the tool properly.

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