scholarly journals Experimental Flight Patterns Evaluation for a UAV-Based Air Pollutant Sensor

Micromachines ◽  
2020 ◽  
Vol 11 (8) ◽  
pp. 768 ◽  
Author(s):  
João Otávio Araujo ◽  
João Valente ◽  
Lammert Kooistra ◽  
Sandra Munniks ◽  
Ruud J. B. Peters
Keyword(s):  
Electrochemical Sensors ◽  
Field Tests ◽  
Air Pollutant ◽  
Automate Monitoring ◽  
Remote Sensors ◽  
Novel Approach ◽  
Wilcoxon Rank Sum Test ◽  
Significant Difference ◽  
Aerial Vehicle ◽  
And Performance

The use of drones in combination with remote sensors have displayed increasing interest over the last years due to its potential to automate monitoring processes. In this study, a novel approach of a small flying e-nose is proposed by assembling a set of AlphaSense electrochemical-sensors to a DJI Matrix 100 unmanned aerial vehicle (UAV). The system was tested on an outdoor field with a source of NO2. Field tests were conducted in a 100 m2 area on two dates with different wind speed levels varying from low (0.0–2.9m/s) to high (2.1–5.3m/s), two flight patterns zigzag and spiral and at three altitudes (3, 6 and 9 m). The objective of this study is to evaluate the sensors responsiveness and performance when subject to distinct flying conditions. A Wilcoxon rank-sum test showed significant difference between flight patterns only under High Wind conditions, with Spiral flights being slightly superior than Zigzag. With the aim of contributing to other studies in the same field, the data used in this analysis will be shared with the scientific community.

scholarly journals Airborne System for Pipeline Surveillance Using an Unmanned Aerial Vehicle

2020 ◽  
Vol 5 (2) ◽  
pp. 178-182
Author(s):  
Mbadiwe Samuel Benyeogor ◽  
Adeboye Olatunbosun ◽  
Sushant Kumar
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Oil And Gas ◽  
Field Tests ◽  
Oil Industry ◽  
Leakage Detection ◽  
Liquefied Petroleum Gas ◽  
Gas Leakage ◽  
Remote Sensors ◽  
Aerial Vehicle ◽  
Asset Monitoring

Our work involves the development of a quadcopter Unmanned Aerial Vehicle (UAV) system with remote sensors onboard for monitoring oil and gas pipelines. Two Liquefied Petroleum Gas (LPG) sensors were used for LPG gas leakage detection. The Multiwii software is used to control, track and simulate the 3D motion of the UAV in flight. Using this device, experimental data from field tests were analyzed with MATLAB. Results reveal that the developed system has performed as expected. Thus, our device can be used to enhance asset monitoring and operational safety in the oil industry.

scholarly journals A UAV-Based Framework for Semi-Automated Thermographic Inspection of Belt Conveyors in the Mining Industry

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2243 ◽  
Author(s):  
Regivaldo Carvalho ◽  
Richardson Nascimento ◽  
Thiago D’Angelo ◽  
Saul Delabrida ◽  
Andrea G. C. Bianchi ◽  
...  
Keyword(s):  
Mining Industry ◽  
Field Tests ◽  
Processing Technique ◽  
Signal Processing Technique ◽  
Novel Approach ◽  
Extensive Field ◽  
Aerial Vehicle ◽  
Future Experimentation ◽  
Critical Components ◽  
Belt Conveyors

Frequent and accurate inspections of industrial components and equipment are essential because failures can cause unscheduled downtimes, massive material, and financial losses or even endanger workers. In the mining industry, belt idlers or rollers are examples of such critical components. Although there are many precise laboratory techniques to assess the condition of a roller, companies still have trouble implementing a reliable and scalable procedure to inspect their field assets. This article enumerates and discusses the existing roller inspection techniques and presents a novel approach based on an Unmanned Aerial Vehicle (UAV) integrated with a thermal imaging camera. Our preliminary results indicate that using a signal processing technique, we are able to identify roller failures automatically. We also proposed and implemented a back-end platform that enables field and cloud connectivity with enterprise systems. Finally, we have also cataloged the anomalies detected during the extensive field tests in order to build a structured dataset that will allow for future experimentation.

Exploring The Effect of Visual Information Degradation on Human Perception and Performance In A Human-Telerobot System

2020 ◽  
Vol 64 (1) ◽  
pp. 1302-1307
Author(s):  
Richard Stone ◽  
Minglu Wang ◽  
Thomas Schnieders ◽  
Esraa Abdelall
Keyword(s):  
Visual Information ◽  
Human Perception ◽  
Low Level ◽  
Hit Rate ◽  
Word Level ◽  
Level Of Automation ◽  
Significant Difference ◽  
Human Operators ◽  
And Performance ◽  
High Level

Human-robotic interaction system are increasingly becoming integrated into industrial, commercial and emergency service agencies. It is critical that human operators understand and trust automation when these systems support and even make important decisions. The following study focused on human-in-loop telerobotic system performing a reconnaissance operation. Twenty-four subjects were divided into groups based on level of automation (Low-Level Automation (LLA), and High-Level Automation (HLA)). Results indicated a significant difference between low and high word level of control in hit rate when permanent error occurred. In the LLA group, the type of error had a significant effect on the hit rate. In general, the high level of automation was better than the low level of automation, especially if it was more reliable, suggesting that subjects in the HLA group could rely on the automatic implementation to perform the task more effectively and more accurately.

scholarly journals Prospective study to assess the tissue response to HPC-coated p48 flow diverter stents compared to uncoated devices in the rabbit carotid artery model

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Tim Lenz-Habijan ◽  
Pervinder Bhogal ◽  
Catrin Bannewitz ◽  
Ralf Hannes ◽  
Hermann Monstadt ◽  
...  
Keyword(s):  
Foreign Body ◽  
Flow Diverter ◽  
Foreign Body Response ◽  
Tissue Response ◽  
Acute Setting ◽  
Significant Difference ◽  
And Performance ◽  
Surface Modified ◽  
Common Carotid Arteries

Abstract Background Flow diverters (FDs) are widely used in the treatment of intracranial aneurysms, but the required medication increases the risk of haemorrhagic complications and limits their use in the acute setting. Surface modified FDs may limit the need for dual antiplatelet therapy (DAPT). Hydrophilic polymer coating (HPC) may reduce the need of medication. Methods This explorative study, approved by the local authorities and the local welfare committee, compared stent behaviour and overall tissue response between HPC-coated FDs and uncoated FDs, both implanted into the common carotid arteries of eight New Zealand white rabbits. Endothelialisation, inflammatory response, and performance during implantation were assessed. Angiographic follow-up was performed to observe the patency of the devices after implantation and after 30 days. Histological examinations were performed at 30 days to assess foreign body reaction and endothelialisation. Kruskal-Wallis and Wilcoxon tests were used to compare non-parametric variables. Results Angiography showed that both coated and uncoated FDs performed well during implantation. All devices remained patent during immediate follow-up and after 30 days. Histopathology showed no significant difference in inflammation within the vessel wall between the two cohorts (2.12 ± 0.75 vs. 1.96 ± 0.79, p = 0.7072). Complete endothelialisation of the stent struts was seen with very similar (0.04 ± 0.02 mm vs. 0.04 ± 0.03 mm, p = 0.892) neoendothelial thickness between the two cohorts after 30 days. Conclusion Taking into account the limitation in sample size, non-significant differences between the HPC-coated and uncoated FDs regarding implantation, foreign body response, and endothelialisation were found.

scholarly journals Towards a contemporary player learning in development framework for sports practitioners

2021 ◽  
pp. 174795412110023
Author(s):  
Mark O Sullivan ◽  
Carl T Woods ◽  
James Vaughan ◽  
Keith Davids
Keyword(s):  
Linear Process ◽  
Task Environment ◽  
Coach Education ◽  
Development Framework ◽  
Novel Approach ◽  
Non Linear ◽  
And Performance ◽  
Learning Development ◽  
High Level ◽  
User Friendly

As it is appreciated that learning is a non-linear process – implying that coaching methodologies in sport should be accommodative – it is reasonable to suggest that player development pathways should also account for this non-linearity. A constraints-led approach (CLA), predicated on the theory of ecological dynamics, has been suggested as a viable framework for capturing the non-linearity of learning, development and performance in sport. The CLA articulates how skills emerge through the interaction of different constraints (task-environment-performer). However, despite its well-established theoretical roots, there are challenges to implementing it in practice. Accordingly, to help practitioners navigate such challenges, this paper proposes a user-friendly framework that demonstrates the benefits of a CLA. Specifically, to conceptualize the non-linear and individualized nature of learning, and how it can inform player development, we apply Adolph’s notion of learning IN development to explain the fundamental ideas of a CLA. We then exemplify a learning IN development framework, based on a CLA, brought to life in a high-level youth football organization. We contend that this framework can provide a novel approach for presenting the key ideas of a CLA and its powerful pedagogic concepts to practitioners at all levels, informing coach education programs, player development frameworks and learning environment designs in sport.

scholarly journals Awareness and Performance towards Proper Use of Disinfectants to Prevent COVID-19: The Case of Iran

2021 ◽  
Vol 18 (4) ◽  
pp. 2099 ◽  
Author(s):  
Zahra Safari ◽  
Reza Fouladi-Fard ◽  
Razieh Vahidmoghadam ◽  
Mohammad Raza Hosseini ◽  
Abolfazl Mohammadbeigi ◽  
...  
Keyword(s):  
Training Programs ◽  
Health Department ◽  
Public Places ◽  
Incidence Data ◽  
Significant Difference ◽  
And Performance ◽  
Arcview Gis ◽  
Spearman’S Correlation ◽  
Good Range ◽  
Awareness Level

This study aimed to assess the awareness and performance of Qom citizens towards using disinfectants and compared its relationship with geographical distribution of COVID-19 outbreak in Qom, Iran. The study was conducted by a researcher-made questionnaire during April and May, 2020. COVID-19 incidence data for each district of city was obtained from health department of Qom province. Data were analyzed using Excel, SPSS and ArcView (GIS) softwares. It was found that the highest level of citizens’ awareness (52%) was in the weak range while their performance (56%) was in the good range. According to Spearman’s correlation analysis, there was a strong correlation (rho 0.95) between the total mean of awareness and performance (p < 0.01). The highest incidence rate of COVID-19 was in district 7 which had the lowest mean score in both awareness and performance. In addition, the results of ANOVA (LSD—least significant difference) showed that there was a significant difference (p < 0.05) between district 7—with lower mean scores in awareness and performance—and other districts. Overall, it is concluded that citizens’ awareness level was lower than that of their performance. This conclusion not only calls for more training programs to be implemented in public places, schools, universities and governmental offices, but it also necessitates maintaining a proper and timely training about using disinfectants.

scholarly journals Unmanned Aerial Vehicle Operating Mode Classification Using Deep Residual Learning Feature Extraction

Aerospace ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 79
Author(s):  
Carolyn J. Swinney ◽  
John C. Woods
Keyword(s):  
Feature Extraction ◽  
Transfer Learning ◽  
Operating Mode ◽  
Classification Problem ◽  
Large Signal ◽  
Signal Representations ◽  
Novel Approach ◽  
Power Spectral ◽  
Aerial Vehicle ◽  
Deep Convolution Neural Network

Unmanned Aerial Vehicles (UAVs) undoubtedly pose many security challenges. We need only look to the December 2018 Gatwick Airport incident for an example of the disruption UAVs can cause. In total, 1000 flights were grounded for 36 h over the Christmas period which was estimated to cost over 50 million pounds. In this paper, we introduce a novel approach which considers UAV detection as an imagery classification problem. We consider signal representations Power Spectral Density (PSD); Spectrogram, Histogram and raw IQ constellation as graphical images presented to a deep Convolution Neural Network (CNN) ResNet50 for feature extraction. Pre-trained on ImageNet, transfer learning is utilised to mitigate the requirement for a large signal dataset. We evaluate performance through machine learning classifier Logistic Regression. Three popular UAVs are classified in different modes; switched on; hovering; flying; flying with video; and no UAV present, creating a total of 10 classes. Our results, validated with 5-fold cross validation and an independent dataset, show PSD representation to produce over 91% accuracy for 10 classifications. Our paper treats UAV detection as an imagery classification problem by presenting signal representations as images to a ResNet50, utilising the benefits of transfer learning and outperforming previous work in the field.

scholarly journals Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2534
Author(s):  
Oualid Doukhi ◽  
Deok-Jin Lee
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Control Technique ◽  
Local Motion ◽  
Aerial Robots ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

scholarly journals Effect of Engaging Trainees by Assessing Peer Performance: A Randomised Controlled Trial Using Simulated Patient Scenarios

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Charlotte Loumann Krogh ◽  
Charlotte Ringsted ◽  
Charles B. Kromann ◽  
Maria Birkvad Rasmussen ◽  
Tobias Todsen ◽  
...  
Keyword(s):  
Controlled Trial ◽  
Intervention Group ◽  
Control Group ◽  
Global Rating ◽  
Training Performance ◽  
Significant Difference ◽  
Training Format ◽  
Peer Performance ◽  
And Performance ◽  
Randomised Controlled

Introduction. The aim of this study was to explore the learning effect of engaging trainees by assessing peer performance during simulation-based training.Methods. Eighty-four final year medical students participated in the study. The intervention involved trainees assessing peer performance during training. Outcome measures were in-training performance and performance, both of which were measured two weeks after the course. Trainees’ performances were videotaped and assessed by two expert raters using a checklist that included a global rating. Trainees’ satisfaction with the training was also evaluated.Results. The intervention group obtained a significantly higher overall in-training performance score than the control group: mean checklist score 20.87 (SD 2.51) versus 19.14 (SD 2.65)P=0.003and mean global rating 3.25 SD (0.99) versus 2.95 (SD 1.09)P=0.014. Postcourse performance did not show any significant difference between the two groups. Trainees who assessed peer performance were more satisfied with the training than those who did not: mean 6.36 (SD 1.00) versus 5.74 (SD 1.33)P=0.025.Conclusion. Engaging trainees in the assessment of peer performance had an immediate effect on in-training performance, but not on the learning outcome measured two weeks later. Trainees had a positive attitude towards the training format.

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