scholarly journals Autonomous long-range drone detection system for critical infrastructure safety

2021 ◽  
Author(s):  
Xindi Zhang ◽  
Kusrini Kusrini
Keyword(s):  
Long Range ◽  
Situation Awareness ◽  
Critical Infrastructure ◽  
Detection System ◽  
Focal Length ◽  
Low Cost ◽  
System Logs ◽  
Continuous Stream ◽  
Hardware Component ◽  
Fully Connected

AbstractThe development of unmanned aerial vehicles has been identified as a potential source of a weapon for causing operational disruptions against critical infrastructures. To mitigate and neutralise the threat posed by the misuse of drones against malicious and terrorist activity, this paper presents a holistic design of a long-range autonomous drone detection platform. The novelty of the proposed system lies in the confluence between the design of hardware and software components to effective and efficient localisation of the intruder objects. The research presented in the paper proposes the design and validation of a situation awareness component which is interfaced with the hardware component for controlling the focal length of the camera. The continuous stream of media data obtained from the region of vulnerability is processed using the object detection that is built on region based fully connected neural network. The novelty of the proposed system relies on the processing of multi-threaded dual-media input streams that are evaluated to mitigate the latency of the system. Upon the successful detection of malicious drones, the system logs the occurrence of intruders that consists of both event description and the associated media evidence for the deployment of the mitigation strategy. The analytics platform that controls the signalling of the low-cost sensing equipment contains the NVIDIA GeForce GTX 1080 for detecting drones. The experimental testbeds developed for the validation of the proposed system has been constructed to include environments and situations that are commonly faced by critical infrastructure operators such as the area of protection, drone flight path, tradeoff between the angle of coverage against the distance of coverage. The validation of the proposed system has resulted in yielding a range of intruder drone detection by 250m with an accuracy of 95.5%.

scholarly journals High-Precision Low-Cost Gimballing Platform for Long-Range Railway Obstacle Detection

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 474
Author(s):  
Elio Hajj Assaf ◽  
Cornelius von von Einem ◽  
Cesar Cadena ◽  
Roland Siegwart ◽  
Florian Tschopp
Keyword(s):  
Long Range ◽  
High Precision ◽  
High Speed ◽  
Detection System ◽  
Low Cost ◽  
Obstacle Detection ◽  
Numerical Control ◽  
Railway Network ◽  
Lever System ◽  
Novel Approach

Increasing demand for rail transportation results transportation by rail, resulting in denser and more high-speed usage of the existing railway network, making makes new and more advanced vehicle safety systems necessary. Furthermore, high traveling speeds and the greatlarge weights of trains lead to long braking distances—all of which necessitates Long braking distances, due to high travelling speeds and the massive weight of trains, necessitate a Long-Range Obstacle Detection (LROD) system, capable of detecting humans and other objects more than 1000 m in advance. According to current research, only a few sensor modalities are capable of reaching this far and recording sufficiently accurate enoughdata to distinguish individual objects. The limitation of these sensors, such as a 1D-Light Detection and Ranging (LiDAR), is however a very narrow Field of View (FoV), making it necessary to use ahigh-precision means of orienting to target them at possible areas of interest. To close this research gap, this paper presents a novel approach to detecting railway obstacles by developinga high-precision pointing mechanism, for the use in a future novel railway obstacle detection system In this work such a high-precision pointing mechanism is developed, capable of targeting aiming a 1D-LiDAR at humans or objects at the required distance. This approach addresses To address the challenges of a low target pricelimited budget, restricted access to high-precision machinery and equipment as well as unique requirements of our target application., a novel pointing mechanism has been designed and developed. By combining established elements from 3D printers and Computer Numerical Control (CNC) machines with a double-hinged lever system, simple and cheaplow-cost components are capable of precisely orienting an arbitrary sensor platform. The system’s actual pointing accuracy has been evaluated using a controlled, in-door, long-range experiment. The device was able to demonstrate a precision of 6.179 mdeg, which is at the limit of the measurable precision of the designed experiment.

Study of the film formation process in liquid-liquid extraction flow injection analysis

1991 ◽  
Vol 56 (6) ◽  
pp. 1228-1237 ◽  
Author(s):  
Vlastimil Kubáň
Keyword(s):  
Flow System ◽  
Detection System ◽  
Film Formation ◽  
Liquid Extraction ◽  
Photometric Detection ◽  
Liquid Liquid Extraction ◽  
Teflon Tube ◽  
Continuous Stream ◽  
Computer Controlled ◽  
Segmented Volume

The behaviour of a thin film of an organic solvent on the walls of the extraction coil in a continuous liquid-liquid extraction flow system was studied using a computer-controlled fast-recording on-tube photometric detection system (approx. 3 ms time resolution). A single-loop injector was employed to introduce precise, reproducible volumes (Sr < 2%) of one phase into the continuous stream of the other as a segmented volume standard. The film thickness Df, ranging from 1 to 20 μm for a 0.7 mm teflon tube, was calculated from the segment lengthening at a different chloroform flow rates and was found to obey a polynominal dependence on the linear flow rate, df = f(uα), where α < 1.

Face recognition in an intelligent door lock with ResNet model based on deep learning

2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen
Keyword(s):  
Face Recognition ◽  
Detection System ◽  
Low Cost ◽  
Ease Of Use ◽  
Raspberry Pi ◽  
Training Methods ◽  
Graphics Recognition ◽  
Face Images ◽  
The Face ◽  
Door Lock

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.

scholarly journals Genome-wide integration site detection using Cas9 enriched amplification-free long-range sequencing

2020 ◽  
Author(s):  
Joost van Haasteren ◽  
Altar M Munis ◽  
Deborah R Gill ◽  
Stephen C Hyde
Keyword(s):  
Long Range ◽  
Insertional Mutagenesis ◽  
Lentiviral Vector ◽  
Integration Site ◽  
Low Cost ◽  
Safety Evaluation ◽  
Read Length ◽  
Chromosomal Dna ◽  
Wide Range

Abstract The gene and cell therapy fields are advancing rapidly, with a potential to treat and cure a wide range of diseases, and lentivirus-based gene transfer agents are the vector of choice for many investigators. Early cases of insertional mutagenesis caused by gammaretroviral vectors highlighted that integration site (IS) analysis was a major safety and quality control checkpoint for lentiviral applications. The methods established to detect lentiviral integrations using next-generation sequencing (NGS) are limited by short read length, inadvertent PCR bias, low yield, or lengthy protocols. Here, we describe a new method to sequence IS using Amplification-free Integration Site sequencing (AFIS-Seq). AFIS-Seq is based on amplification-free, Cas9-mediated enrichment of high-molecular-weight chromosomal DNA suitable for long-range Nanopore MinION sequencing. This accessible and low-cost approach generates long reads enabling IS mapping with high certainty within a single day. We demonstrate proof-of-concept by mapping IS of lentiviral vectors in a variety of cell models and report up to 1600-fold enrichment of the signal. This method can be further extended to sequencing of Cas9-mediated integration of genes and to in vivo analysis of IS. AFIS-Seq uses long-read sequencing to facilitate safety evaluation of preclinical lentiviral vector gene therapies by providing IS analysis with improved confidence.

Development of a method for detecting trace metals in aqueous solutions based on the coordination chemistry of hexahydrotriazines

The Analyst ◽  
2015 ◽  
Vol 140 (15) ◽  
pp. 5184-5189 ◽  
Author(s):  
Rudy J. Wojtecki ◽  
Alexander Y. Yuen ◽  
Thomas G. Zimmerman ◽  
Gavin O. Jones ◽  
Hans W. Horn ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Coordination Chemistry ◽  
Trace Metals ◽  
Aqueous Solutions ◽  
Detection System ◽  
Low Cost ◽  
System P ◽  
Chemical Indicator

The detection of trace amounts (<10 ppb) of heavy metals in aqueous solutions is described using hexahydrotriazines as a chemical indicator and a low cost fluorimeter-based detection system.

Design of a low-cost detection system for laser-induced plasma spectroscopy

1999 ◽  
Vol 70 (9) ◽  
pp. 3519-3522 ◽  
Author(s):  
R. E. Neuhauser ◽  
B. Ferstl ◽  
C. Haisch ◽  
U. Panne ◽  
R. Niessner
Keyword(s):  
Detection System ◽  
Low Cost ◽  
Plasma Spectroscopy ◽  
Laser Induced Plasma
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