A novel approach for securing data against intrusion attacks in unmanned aerial vehicles integrated heterogeneous network using functional encryption technique

2020 ◽  
Author(s):  
Diwankshi Sharma ◽  
Sachin Kumar Gupta ◽  
Aabid Rashid ◽  
Sumeet Gupta ◽  
Mamoon Rashid ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Heterogeneous Network ◽  
Functional Encryption ◽  
Aerial Vehicles ◽  
Novel Approach

scholarly journals A UAV-Based Thermal-Imaging Approach for the Monitoring of Urban Landfills

Inventions ◽  
2020 ◽  
Vol 5 (4) ◽  
pp. 55
Author(s):  
Giovanni Tanda ◽  
Marco Balsi ◽  
Paolo Fallavollita ◽  
Valter Chiarabini
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Thermal Imaging ◽  
Preliminary Evaluation ◽  
Production Potential ◽  
Thermal Anomalies ◽  
Aerial Vehicles ◽  
Innovative Method ◽  
Novel Approach ◽  
Imaging Approach ◽  
Methane Production Potential

The monitoring of waste disposal sites is important in order to minimize leakages of biogas, produced by anaerobic digestion and potentially explosive and detrimental to the environment. In this research, thermal imaging from unmanned aerial vehicles (UAVs) has been proposed as a diagnostic tool to monitor urban landfills. Since the anaerobic decomposition produces heat along with biogas, thermal anomalies recorded over the soil are likely to be associated with local biogas escaping from the landfill terrain and leaving a local thermal print. A simple and novel approach, based only on the processing of thermal maps gathered by the remote sensing surveys, has been proposed for the estimation of the fugitive methane emissions from landfills. Two case studies, concerning two Italian landfills, have been presented. For one of them (Mount Scarpino, Genoa), significant thermal anomalies were identified during several UAV flights and the relevant thermal images processed to obtain a rough estimation of the associated methane leakages. For the second landfill (Scala Erre, Sassari), the thermal map did not reveal any anomaly attributable to local biogas emission. Despite some limitations outlined in the paper, the present approach is proposed as an innovative method to identify significant biogas leakages from an urban landfill and to provide a preliminary evaluation of the methane production potential.

scholarly journals Seed and Seedling Detection Using Unmanned Aerial Vehicles and Automated Image Classification in the Monitoring of Ecological Recovery

Drones ◽  
2019 ◽  
Vol 3 (3) ◽  
pp. 53 ◽  
Author(s):  
Buters ◽  
Belton ◽  
Cross
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Substrate Surface ◽  
Morphological Characteristics ◽  
Ecological Monitoring ◽  
Image Resolution ◽  
Automated Classification ◽  
Aerial Vehicles ◽  
Novel Approach ◽  
Plant Life Cycle ◽  
Ecological Recovery

Monitoring is a crucial component of ecological recovery projects, yet it can be challenging to achieve at scale and during the formative stages of plant establishment. The monitoring of seeds and seedlings, which represent extremely vulnerable stages in the plant life cycle, is particularly challenging due to their diminutive size and lack of distinctive morphological characteristics. Counting and classifying seedlings to species level can be time-consuming and extremely difficult, and there is a need for technological approaches offering restoration practitioners with fine-resolution, rapid and scalable plant-based monitoring solutions. Unmanned aerial vehicles (UAVs) offer a novel approach to seed and seedling monitoring, as the combination of high-resolution sensors and low flight altitudes allow for the detection and monitoring of small objects, even in challenging terrain and in remote areas. This study utilized low-altitude UAV imagery and an automated object-based image analysis software to detect and count target seeds and seedlings from a matrix of non-target grasses across a variety of substrates reflective of local restoration substrates. Automated classification of target seeds and target seedlings was achieved at accuracies exceeding 90% and 80%, respectively, although the classification accuracy decreased with increasing flight altitude (i.e., decreasing image resolution) and increasing background surface complexity (increasing percentage cover of non-target grasses and substrate surface texture). Results represent the first empirical evidence that small objects such as seeds and seedlings can be classified from complex ecological backgrounds using automated processes from UAV-imagery with high levels of accuracy. We suggest that this novel application of UAV use in ecological monitoring offers restoration practitioners an excellent tool for rapid, reliable and non-destructive early restoration trajectory assessment.

scholarly journals Unmanned aerial vehicles (UAVs)‐based thermal infrared (TIR) mapping, a novel approach to assess groundwater discharge into the coastal zone

2016 ◽  
Vol 14 (11) ◽  
pp. 725-735 ◽  
Author(s):  
Eunhee Lee ◽  
Heesung Yoon ◽  
Sung Pil Hyun ◽  
William C. Burnett ◽  
Dong‐Chan Koh ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Coastal Zone ◽  
Groundwater Discharge ◽  
Thermal Infrared ◽  
Aerial Vehicles ◽  
Novel Approach

scholarly journals Feature-Based Stereo Vision Relative Positioning Strategy for Formation Control of Unmanned Aerial Vehicles

2020 ◽  
Vol 9 (2) ◽  
pp. 1613-1617
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Formation Control ◽  
Vision System ◽  
Ground Truth ◽  
Flight Test ◽  
Relative Positioning ◽  
Ground Truth Data ◽  
Aerial Vehicles ◽  
Novel Approach ◽  
Positioning Strategy

As inspired by birds flying in flocks, their vision is one of the most critical components to enable them to respond to their neighbor’s motion. In this paper, a novel approach in developing a Vision System as the primary sensor for relative positioning in flight formation of a Leader-Follower scenario is introduced. To use the system in real-time and on-board of the unmanned aerial vehicles (UAVs) with up to 1.5 kilograms of payload capacity, few computing platforms are reviewed and evaluated. The study shows that the NVIDIA Jetson TX1 is the most suited platform for this project. In addition, several different techniques and approaches for developing the algorithm is discussed as well. As per system requirements and conducted study, the algorithm that is developed for this Vision System is based on Tracking and On-Line Machine Learning approach. Flight test has been performed to check the accuracy and reliability of the system, and the results indicate the minimum accuracy of 83% of the vision system against ground truth data.

Development of thickened semi-synthetic engine oil M-5z / 20 AERO for four-stroke gasoline engines aircraft piston of unmanned aerial vehicles (UAVs)

2020 ◽  
Vol 06 ◽  
pp. 44-47
Author(s):  
A.A. Moykin ◽  
◽  
A.S. Medzhibovsky ◽  
S.A. Kriushin ◽  
M.V. Seleznev ◽  
...  
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Engine Oil ◽  
Motor Oil ◽  
Gasoline Engines ◽  
State Research Institute ◽  
Technical Requirements ◽  
Aerial Vehicles ◽  
State Research ◽  
Industrial Batch ◽  
The Russian Federation

Nowadays, the creation of remotely-piloted aerial vehicles for various purposes is regarded as one of the most relevant and promising trends of aircraft development. FAU "25 State Research Institute of Chemmotology of the Ministry of Defense of the Russian Federation" have studied the operation features of aircraft piston engines and developed technical requirements for motor oil for piston four-stroke UAV engines, as well as a new engine oil M-5z/20 AERO in cooperation with NPP KVALITET, LLC. Based on the complex of qualification tests, the stated operational properties of the experimental-industrial batch of M-5z/20 AERO oil are generally confirmed.

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