Near Real-Time Orthorectification and Mosaic of Small UAV Video Flow for Time-Critical Event Response

2009 ◽  
Vol 47 (3) ◽  
pp. 739-747 ◽  
Author(s):  
Guoqing Zhou
Keyword(s):  
Real Time ◽  
Critical Event ◽  
Small Uav ◽  
Event Response ◽  
Time Critical

Creating adaptive predictions for packaging-critical quality parameters using advanced analytics and machine learning

TAPPI Journal ◽  
2019 ◽  
Vol 18 (11) ◽  
pp. 679-689
Author(s):  
CYDNEY RECHTIN ◽  
CHITTA RANJAN ◽  
ANTHONY LEWIS ◽  
BETH ANN ZARKO
Keyword(s):  
Machine Learning ◽  
Real Time ◽  
Predictive Analytics ◽  
Paper Industry ◽  
Quality Parameters ◽  
Fast Change ◽  
The Face ◽  
Model Tuning ◽  
Reducing Costs ◽  
Time Critical

Packaging manufacturers are challenged to achieve consistent strength targets and maximize production while reducing costs through smarter fiber utilization, chemical optimization, energy reduction, and more. With innovative instrumentation readily accessible, mills are collecting vast amounts of data that provide them with ever increasing visibility into their processes. Turning this visibility into actionable insight is key to successfully exceeding customer expectations and reducing costs. Predictive analytics supported by machine learning can provide real-time quality measures that remain robust and accurate in the face of changing machine conditions. These adaptive quality “soft sensors” allow for more informed, on-the-fly process changes; fast change detection; and process control optimization without requiring periodic model tuning. The use of predictive modeling in the paper industry has increased in recent years; however, little attention has been given to packaging finished quality. The use of machine learning to maintain prediction relevancy under everchanging machine conditions is novel. In this paper, we demonstrate the process of establishing real-time, adaptive quality predictions in an industry focused on reel-to-reel quality control, and we discuss the value created through the availability and use of real-time critical quality.

Design and development of a backstepping controller autopilot for fixed-wing UAVs

2021 ◽  
pp. 1-27
Author(s):  
D. Sartori ◽  
F. Quagliotti ◽  
M.J. Rutherford ◽  
K.P. Valavanis
Keyword(s):  
Real Time ◽  
Control Law ◽  
Parametric Uncertainties ◽  
Hardware In The Loop ◽  
Aircraft Control ◽  
Backstepping Approach ◽  
Small Uav ◽  
Backstepping Controller ◽  
Definition Of ◽  
Performance Results

Abstract Backstepping represents a promising control law for fixed-wing Unmanned Aerial Vehicles (UAVs). Its non-linearity and its adaptation capabilities guarantee adequate control performance over the whole flight envelope, even when the aircraft model is affected by parametric uncertainties. In the literature, several works apply backstepping controllers to various aspects of fixed-wing UAV flight. Unfortunately, many of them have not been implemented in a real-time controller, and only few attempt simultaneous longitudinal and lateral–directional aircraft control. In this paper, an existing backstepping approach able to control longitudinal and lateral–directional motions is adapted for the definition of a control strategy suitable for small UAV autopilots. Rapidly changing inner-loop variables are controlled with non-adaptive backstepping, while slower outer loop navigation variables are Proportional–Integral–Derivative (PID) controlled. The controller is evaluated through numerical simulations for two very diverse fixed-wing aircraft performing complex manoeuvres. The controller behaviour with model parametric uncertainties or in presence of noise is also tested. The performance results of a real-time implementation on a microcontroller are evaluated through hardware-in-the-loop simulation.

scholarly journals A Survey on Vulnerabilities and Countermeasures in the Communications of the Smart Grid

Electronics ◽  
2021 ◽  
Vol 10 (16) ◽  
pp. 1881
Author(s):  
Jesús Lázaro ◽  
Armando Astarloa ◽  
Mikel Rodríguez ◽  
Unai Bidarte ◽  
Jaime Jiménez
Keyword(s):  
Smart Grid ◽  
Real Time ◽  
International Electrotechnical Commission ◽  
Communication Infrastructure ◽  
Iec 61850 ◽  
Best Effort ◽  
Electrical Grid ◽  
Informational Technology ◽  
Iec 62351 ◽  
Time Critical

Since the 1990s, the digitalization process has transformed the communication infrastructure within the electrical grid: proprietary infrastructures and protocols have been replaced by the IEC 61850 approach, which realizes interoperability among vendors. Furthermore, the latest networking solutions merge operational technologies (OTs) and informational technology (IT) traffics in the same media, such as time-sensitive networking (TSN)—standard, interoperable, deterministic, and Ethernet-based. It merges OT and IT worlds by defining three basic traffic types: scheduled, best-effort, and reserved traffic. However, TSN demands security against potential new cyberattacks, primarily, to protect real-time critical messages. Consequently, security in the smart grid has turned into a hot topic under regulation, standardization, and business. This survey collects vulnerabilities of the communication in the smart grid and reveals security mechanisms introduced by international electrotechnical commission (IEC) 62351-6 and how to apply them to time-sensitive networking.

Geologic Modelling Using Augmented Reality

2021 ◽  
Author(s):  
Phathompat Boonyasaknanon ◽  
Raymond Pols ◽  
Katja Schulze ◽  
Robert Rundle
Keyword(s):  
Augmented Reality ◽  
Real Time ◽  
3D Models ◽  
New Approach ◽  
Domain Experts ◽  
3D Objects ◽  
Track Record ◽  
Initial Work ◽  
Geologic Model ◽  
Time Critical

Abstract An augmented reality (AR) system is presented which enhances the real-time collaboration of domain experts involved in the geologic modeling of complex reservoirs. An evaluation of traditional techniques is compared with this new approach. The objective of geologic modeling is to describe the subsurface as accurately and in as much detail as possible given the available data. This is necessarily an iterative process since as new wells are drilled more data becomes available which either validates current assumptions or forces a re-evaluation of the model. As the speed of reservoir development increases there is a need for expeditious updates of the subsurface model as working with an outdated model can lead to costly mistakes. Common practice is for a geologist to maintain the geologic model while working closely with other domain experts who are frequently not co-located with the geologist. Time-critical analysis can be hampered by the fact that reservoirs, which are inherently 3D objects, are traditionally viewed with 2D screens. The system presented here allows the geologic model to be rendered as a hologram in multiple locations to allow domain experts to collaborate and analyze the reservoir in real-time. Collaboration on 3D models has not changed significantly in a generation. For co-located personnel the approach is to gather around a 2D screen. For remote personnel the approach has been sharing a model through a 2D screen along with video chat. These approaches are not optimal for many reasons. Over the years various attempts have been tried to enhance the collaboration experience and have all fallen short. In particular virtual reality (VR) has been seen as a solution to this problem. However, we have found that augmented reality (AR) is a much better solution for many subtle reasons which are explored in the paper. AR has already acquired an impressive track record in various industries. AR will have applications in nearly all industries. For various historical reasons, the uptake for AR is much faster in some industries than others. It is too early to tell whether the use of augmented reality in geological applications will be transformative, however the results of this initial work are promising.

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