scholarly journals Development of Low-Resolution, Low-Power and Low-Cost Infrared System

2021 ◽  
Vol 25 (2) ◽  
pp. 47-52
Author(s):  
Bogusław Więcek ◽  
Sebastian Urbaś
Keyword(s):  
Low Power ◽  
Unmanned Aerial Vehicles ◽  
Thermal Imaging ◽  
Electronic Circuit ◽  
Low Cost ◽  
Low Power Consumption ◽  
Aerial Vehicles ◽  
Imaging Camera ◽  
Fpga Chip ◽  
Infrared Wave

The article presents the construction of a thermal imaging camera with low power consumption. The 80 × 80 Micro80Gen2 microbolometric array of detectors records infrared radiation in the LWIR spectral range (long infrared wave, 8–12 µm). The entire digital part of the electronic circuit has been integrated within the reprogrammable FPGA chip from the Spartan 6 family. In order to read and display thermograms, an application for the .NetFremework 3.1 platform, which implements non-uniformity correction (NUC) and image processing, is written. Due to its low cost, small size and weight, the camera can be used in various applications, e.g. in unmanned aerial vehicles (UAV) known as drones.

scholarly journals Analysis of the Possibility of Using Unmanned Aerial Vehicles and Thermovision for the Stocktaking of Big Game

2021 ◽  
Vol 4 (1) ◽  
pp. 317-329
Author(s):  
Arkadiusz Boczkowski ◽  
Artur Kuboszek ◽  
Adam Mańka ◽  
Karolina Dutkiewicz ◽  
Wiktoria Gramatyka ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Thermal Imaging ◽  
Weather Conditions ◽  
Aerial Vehicles ◽  
University Of Technology ◽  
Imaging Camera ◽  
Thermal Cameras ◽  
Wave Range ◽  
The Cost ◽  
Infrared Wave

Abstract Classic methods of stocktaking big game living in a given area have many disadvantages. The main result is the need to ensure appropriate terrain and weather conditions and also require the involvement of a large number of people, so-called observers. The development of technology makes it possible to create new stocktaking methods that will not have as many of the above-mentioned disadvantages, while reducing the cost of stocktaking and increasing its accuracy. This paper presents an analysis of the possibility of using unmanned aerial vehicles, so-called drones, in combination with the observation of game in the infrared wave range with the use of a thermal imaging camera. The paper presents the concept of such a solution, which will of course be further developed. Raids are planned with the use of thermal cameras over areas according to strictly defined transects and subjecting the obtained images to analysis, also with the use of artificial intelligence methods. This article was written as part of the PBL project carried out by a group of students from the Silesian University of Technology under the supervision of dr inż. Arkadiusz Boczkowski.

Important Parameters and Settings in Unmanned Aerial Vehicles

2021 ◽  
Vol 58 (2) ◽  
pp. 92-118
Author(s):  
Maciej Zawistowski
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Thermal Imaging ◽  
Fire Service ◽  
On Certainty ◽  
Fire Brigade ◽  
Aerial Vehicles ◽  
Imaging Camera ◽  
The Moment ◽  
The Impact

Aim: The article presents a set of parameters and settings for unmanned aerial vehicles (UAV), which is crucial in the operational work of the fire brigade and its importance for the quality of the final material obtained from an RGB camera or a thermal imaging camera. Introduction: Unmanned aerial vehicles (UAVs) are more often and more boldly used by various uniformed formations, including pilots of the State Fire Service and Volunteer Fire Brigades. Currently, they are used to perform recognition of situations and coordination of activities with the use of RGB and thermal imaging cameras. There are also other applications of UAV, including firefighting, but at the moment they are only conceptual solutions, as they have not been tested during an actual firefighting operation. According to the authors, a drone is currently only a carrier of additional devices and its functionality during the operation depends largely on certainty and reliability of a given UAV structure, as well as on the type and quality of the elements and sensors mounted on it. Methodology: A review of literature and press reports, as well as the authors’ experience in working with UAVs and the results of their research were used to analyse the topic. Conclusions: Indicating a set of key parameters for the UAVs used by fire brigade users is only possible to define its application. Therefore, in this study, the authors presented the most common use of unmanned aerial vehicles, for which key parameters were indicated and the impact of these factors on the obtained results of drones was described. Due to the frequent neglect of camera operation and the importance of their parameters, the authors described the most frequently set parameters of photographs and their impact on the final result, which is of key importance for the usefulness of the collected material.

scholarly journals Eyes in the Sky: Assessing the Feasibility of Low-Cost, Ready-to-Use Unmanned Aerial Vehicles to Monitor Primate Populations Directly

2019 ◽  
Vol 91 (1) ◽  
pp. 69-82
Author(s):  
Brandon P. Semel ◽  
Sarah M. Karpanty ◽  
Faramalala Francette Vololonirina ◽  
Ando Nantenaina Rakotonanahary
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Low Cost ◽  
Aerial Vehicles

scholarly journals Model-Based Autonomous Navigation with Moment of Inertia Estimation for Unmanned Aerial Vehicles

Sensors ◽  
2019 ◽  
Vol 19 (11) ◽  
pp. 2467 ◽  
Author(s):  
Hery Mwenegoha ◽  
Terry Moore ◽  
James Pinchin ◽  
Mark Jabbal
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Navigation System ◽  
Process Model ◽  
Unscented Kalman Filter ◽  
Low Cost ◽  
Moment Of Inertia ◽  
Model Parameters ◽  
Main Process ◽  
Model Based ◽  
Aerial Vehicles

The dominant navigation system for low-cost, mass-market Unmanned Aerial Vehicles (UAVs) is based on an Inertial Navigation System (INS) coupled with a Global Navigation Satellite System (GNSS). However, problems tend to arise during periods of GNSS outage where the navigation solution degrades rapidly. Therefore, this paper details a model-based integration approach for fixed wing UAVs, using the Vehicle Dynamics Model (VDM) as the main process model aided by low-cost Micro-Electro-Mechanical Systems (MEMS) inertial sensors and GNSS measurements with moment of inertia calibration using an Unscented Kalman Filter (UKF). Results show that the position error does not exceed 14.5 m in all directions after 140 s of GNSS outage. Roll and pitch errors are bounded to 0.06 degrees and the error in yaw grows slowly to 0.65 degrees after 140 s of GNSS outage. The filter is able to estimate model parameters and even the moment of inertia terms even with significant coupling between them. Pitch and yaw moment coefficient terms present significant cross coupling while roll moment terms seem to be decorrelated from all of the other terms, whilst more dynamic manoeuvres could help to improve the overall observability of the parameters.

scholarly journals Accurate Landing of Unmanned Aerial Vehicles Using Ground Pattern Recognition

Electronics ◽  
2019 ◽  
Vol 8 (12) ◽  
pp. 1532 ◽  
Author(s):  
Jamie Wubben ◽  
Francisco Fabra ◽  
Carlos T. Calafate ◽  
Tomasz Krzeszowski ◽  
Johann M. Marquez-Barja ◽  
...  
Keyword(s):  
Pattern Recognition ◽  
Unmanned Aerial Vehicles ◽  
High Precision ◽  
Low Cost ◽  
Target Position ◽  
Flight Behavior ◽  
Ground Pattern ◽  
Aerial Vehicles ◽  
Exact Position ◽  
Precision Landing

Over the last few years, several researchers have been developing protocols and applications in order to autonomously land unmanned aerial vehicles (UAVs). However, most of the proposed protocols rely on expensive equipment or do not satisfy the high precision needs of some UAV applications such as package retrieval and delivery or the compact landing of UAV swarms. Therefore, in this work, a solution for high precision landing based on the use of ArUco markers is presented. In the proposed solution, a UAV equipped with a low-cost camera is able to detect ArUco markers sized 56 × 56 cm from an altitude of up to 30 m. Once the marker is detected, the UAV changes its flight behavior in order to land on the exact position where the marker is located. The proposal was evaluated and validated using both the ArduSim simulation platform and real UAV flights. The results show an average offset of only 11 cm from the target position, which vastly improves the landing accuracy compared to the traditional GPS-based landing, which typically deviates from the intended target by 1 to 3 m.

scholarly journals Integration of highly anisotropic multiferroic BaTiO3–Fe nanocomposite thin films on Si towards device applications

2020 ◽  
Vol 2 (9) ◽  
pp. 4172-4178
Author(s):  
Matias Kalaswad ◽  
Bruce Zhang ◽  
Xuejing Wang ◽  
Han Wang ◽  
Xingyao Gao ◽  
...  
Keyword(s):  
Thin Films ◽  
Power Consumption ◽  
Low Power ◽  
High Speed ◽  
Low Cost ◽  
Low Power Consumption ◽  
Silicon Substrates ◽  
Critical Step ◽  
Nanocomposite Thin Films ◽  
Device Applications

Integration of highly anisotropic multiferroic thin films on silicon substrates is a critical step towards low-cost devices, especially high-speed and low-power consumption memories.

scholarly journals Thermal Imaging of Beach-Nesting Bird Habitat with Unmanned Aerial Vehicles: Considerations for Reducing Disturbance and Enhanced Image Accuracy

Drones ◽  
2020 ◽  
Vol 4 (2) ◽  
pp. 12
Author(s):  
Kerry L. Mapes ◽  
Narcisa G. Pricope ◽  
J. Britton Baxley ◽  
Lauren E. Schaale ◽  
Raymond M. Danner
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Thermal Imaging ◽  
Habitat Restoration ◽  
Current Knowledge ◽  
Breeding Habitat ◽  
The Novel ◽  
Thermal Indices ◽  
Ground Control Points ◽  
Aerial Vehicles ◽  
Bird Habitat

Knowledge of temperature variation within and across beach-nesting bird habitat, and how such variation may affect the nesting success and survival of these species, is currently lacking. This type of data is furthermore needed to refine predictions of population changes due to climate change, identify important breeding habitat, and guide habitat restoration efforts. Thermal imagery collected with unmanned aerial vehicles (UAVs) provides a potential approach to fill current knowledge gaps and accomplish these goals. Our research outlines a novel methodology for collecting and implementing active thermal ground control points (GCPs) and assess the accuracy of the resulting imagery using an off-the-shelf commercial fixed-wing UAV that allows for the reconstruction of thermal landscapes at high spatial, temporal, and radiometric resolutions. Additionally, we observed and documented the behavioral responses of beach-nesting birds to UAV flights and modifications made to flight plans or the physical appearance of the UAV to minimize disturbance. We found strong evidence that flying on cloudless days and using sky-blue camouflage greatly reduced disturbance to nesting birds. The incorporation of the novel active thermal GCPs into the processing workflow increased image spatial accuracy an average of 12 m horizontally (mean root mean square error of checkpoints in imagery with and without GCPs was 0.59 m and 23.75 m, respectively). The final thermal indices generated had a ground sampling distance of 25.10 cm and a thermal accuracy of less than 1 °C. This practical approach to collecting highly accurate thermal data for beach-nesting bird habitat while avoiding disturbance is a crucial step towards the continued monitoring and modeling of beach-nesting birds and their habitat.

scholarly journals Operational Framework for Rapid, Very-high Resolution Mapping of Glacial Geomorphology Using Low-cost Unmanned Aerial Vehicles and Structure-from-Motion Approach

2019 ◽  
Vol 11 (1) ◽  
pp. 65 ◽  
Author(s):  
Marek W. Ewertowski ◽  
Aleksandra M. Tomczyk ◽  
David J. A. Evans ◽  
David H. Roberts ◽  
Wojciech Ewertowski
Keyword(s):  
High Resolution ◽  
Unmanned Aerial Vehicles ◽  
Structure From Motion ◽  
Low Cost ◽  
Control Point ◽  
Glacial Geomorphology ◽  
High Resolution Mapping ◽  
Aerial Vehicles ◽  
Resolution Mapping ◽  
Very High

This study presents the operational framework for rapid, very-high resolution mapping of glacial geomorphology, with the use of budget Unmanned Aerial Vehicles and a structure-from-motion approach. The proposed workflow comprises seven stages: (1) Preparation and selection of the appropriate platform; (2) transport; (3) preliminary on-site activities (including optional ground-control-point collection); (4) pre-flight setup and checks; (5) conducting the mission; (6) data processing; and (7) mapping and change detection. The application of the proposed framework has been illustrated by a mapping case study on the glacial foreland of Hørbyebreen, Svalbard, Norway. A consumer-grade quadcopter (DJI Phantom) was used to collect the data, while images were processed using the structure-from-motion approach. The resultant orthomosaic (1.9 cm ground sampling distance—GSD) and digital elevation model (7.9 cm GSD) were used to map the glacial-related landforms in detail. It demonstrated the applicability of the proposed framework to map and potentially monitor detailed changes in a rapidly evolving proglacial environment, using a low-cost approach. Its coverage of multiple aspects ensures that the proposed framework is universal and can be applied in a broader range of settings.

scholarly journals Method for Estimating Solar Energy Potential Based on Photogrammetry from Unmanned Aerial Vehicles

Electronics ◽  
2020 ◽  
Vol 9 (12) ◽  
pp. 2144
Author(s):  
Jose Eduardo Fuentes ◽  
Francisco David Moya ◽  
Oscar Danilo Montoya
Keyword(s):  
Solar Energy ◽  
Unmanned Aerial Vehicles ◽  
3D Model ◽  
Low Cost ◽  
Atmospheric Conditions ◽  
Solar Panels ◽  
Energy Potential ◽  
Aerial Vehicles ◽  
3D Data ◽  
Surface Models

This study presents a method to estimate the solar energy potential based on 3D data taken from unmanned aerial devices. The solar energy potential on the roof of a building was estimated before the placement of solar panels using photogrammetric data analyzed in a geographic information system, and the predictions were compared with the data recorded after installation. The areas of the roofs were chosen using digital surface models and the hemispherical viewshed algorithm, considering how the solar radiation on the roof surface would be affected by the orientation of the surface with respect to the sun, the shade of trees, surrounding objects, topography, and the atmospheric conditions. The results show that the efficiency percentages of the panels and the data modeled by the proposed method from surface models are very similar to the theoretical efficiency of the panels. Radiation potential can be estimated from photogrammetric data and a 3D model in great detail and at low cost. This method allows the estimation of solar potential as well as the optimization of the location and orientation of solar panels.

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