Geo-registration and Geo-location Using Two Airborne Video Sensors

2020 ◽  
Vol 56 (4) ◽  
pp. 2910-2921
Author(s):  
Ehsan Taghavi ◽  
Dan Song ◽  
Ratnasingham Tharmarasa ◽  
Thiagalingam Kirubarajan ◽  
Mike McDonald ◽  
...  
Keyword(s):  
Video Sensors

scholarly journals Car2Car Communication Using a Modulated Backscatter and Automotive FMCW Radar

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3656
Author(s):  
Antonio Lazaro ◽  
Marc Lazaro ◽  
Ramon Villarino ◽  
David Girbau ◽  
Pedro de Paco
Keyword(s):  
Power Supply ◽  
Communication Systems ◽  
Microwave Frequency ◽  
Proof Of Concept ◽  
Driver Assistance ◽  
Switching Rate ◽  
Fmcw Radar ◽  
Time Signals ◽  
Video Sensors ◽  
24 Ghz

This work proposes the use of a modulated tag for direct communication between two vehicles using as a carrier the wave emitted by an FMCW radar installed in the vehicle for advanced driver assistance. The system allows for real-time signals detection and classification, such as stop signal, turn signals and emergency lights, adding redundancy to computer video sensors and without incorporating additional communication systems. A proof-of-concept tag has been designed at the microwave frequency of 24 GHz, consisting of an amplifier connected between receiving and transmitting antennas. The modulation is performed by switching the power supply of the amplifier. The tag is installed on the rear of the car and it answers when it is illuminated by the radar by modulating the backscattered field. The information is encoded in the modulation switching rate used. Simulated and experimental results are given showing the feasibility of the proposed solution.

A scale-up field experiment for the monitoring of a burning process using chemical, audio, and video sensors

2013 ◽  
Vol 21 (2) ◽  
pp. 891-900 ◽  
Author(s):  
P. Stavrakakis ◽  
A. Agapiou ◽  
K. Mikedi ◽  
S. Karma ◽  
M. Statheropoulos ◽  
...  
Keyword(s):  
Field Experiment ◽  
Scale Up ◽  
Burning Process ◽  
Video Sensors

Measure of the effiency of CCD realized in CMOS technology: application to snapshot video sensors

1997 ◽  
Author(s):  
Mourad Elloumi ◽  
Eric Fauvet ◽  
Frederic Truchetet ◽  
Guy Cathebras
Keyword(s):  
Cmos Technology ◽  
Technology Application ◽  
Video Sensors

scholarly journals Machine Learning and Prediction-Based Resource Management in IoT Considering Qos

2019 ◽  
Vol 8 (2) ◽  
pp. 687-694
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Short Term Memory ◽  
Real Data ◽  
Computing Methods ◽  
Energy Utilization ◽  
Real Field ◽  
Proposed Model ◽  
Improved Performance ◽  
Video Sensors

Internet of Things (IoT) is one of the fast-growing technology paradigms used in every sectors, where in the Quality of Service (QoS) is a critical component in such systems and usage perspective with respect to ProSumers (producer and consumers). Most of the recent research works on QoS in IoT have used Machine Learning (ML) techniques as one of the computing methods for improved performance and solutions. The adoption of Machine Learning and its methodologies have become a common trend and need in every technologies and domain areas, such as open source frameworks, task specific algorithms and using AI and ML techniques. In this work we propose an ML based prediction model for resource optimization in the IoT environment for QoS provisioning. The proposed methodology is implemented by using a multi-layer neural network (MNN) for Long Short Term Memory (LSTM) learning in layered IoT environment. Here the model considers the resources like bandwidth and energy as QoS parameters and provides the required QoS by efficient utilization of the resources in the IoT environment. The performance of the proposed model is evaluated in a real field implementation by considering a civil construction project, where in the real data is collected by using video sensors and mobile devices as edge nodes. Performance of the prediction model is observed that there is an improved bandwidth and energy utilization in turn providing the required QoS in the IoT environment.

Intelligent Surveillance and Image Transmission Based on Wireless Video Sensor Network

2012 ◽  
Vol 457-458 ◽  
pp. 690-695
Author(s):  
Cheng Bo Yu ◽  
Yu Xuan Liu ◽  
Yi Meng Zhang ◽  
Hong Bing Li
Keyword(s):  
Assisted Living ◽  
Image Transmission ◽  
Image Sensor ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Processing Unit ◽  
Wireless Video ◽  
Central Processing ◽  
Video Sensors ◽  
Video Sensor

Design and implement an energy-efficient smart camera mote architecture to be used as surveillance device for assisted living. Add the Passive Infrared Sensor (PIR) to WVSN, PIR detect the human or animal’s moving, then it triggers the camera to wake up. The image captured will be grayscale processing by the central processing unit. Camera sensor nodes transmit a grayscale image over wireless channel to master control station. It offers reduced complexity, response time, and power consumption over conventional solutions. By experimental results from the test illustrate that performance of the designed wireless image sensor is better than the exiting ones in the market in terms of received signal strength intensity (RSSI) and packet rate ratio (PRR) with respect to the distance. This scheme is less complicated than other wireless video sensor surveillance techniques, allowing resource-constrained video sensors to operate more reliably and longer.

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