Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Department of Instrumentation

This paper proposes a very novel approach to implement the automatic toll tax collection system on the toll plazas using radio frequency identification (RFID) and global system for mobile (GSM). Nowadays, the cities and highways are bursting with traffic, and very often long queues of vehicles can be seen at various toll plazas so that they can pay the toll and then able to use the road or highway. So a system is proposed wherein the toll tax could be paid via cashless transactions and people wouldn’t have to wait for a long time for the cash payment of the toll tax. This would save people’s money and time simultaneously. It would also eliminate errors in cash transactions and further ease the job of the toll plaza companies. It would definitely bring down any of the corruptions occurring at the toll plazas. Finally, it would make the existing toll tax collection more efficient and ease our lives a bit more. © Springer Nature Singapore Pte Ltd 2019.

VIT Unitversity

School of Electrical Engineering

Vellore Campus

Emerging Research in Computing, Information, Communication and Applications Advances in Intelligent Systems and Computing

Automatic Toll Tax Collection Using GSM

Edges are one of the most important features in images and their analysis and detection in computer vision and image processing is an essential goal. Indeed, a variety of applications such as 3-D reconstruction, shape recognition, image compression, enhancement, and restoration identifying and localizing edges are a low level tasks. This paper presents a Hybrid approach to Infrared image edge detection which becomes a vital point in pattern recognition. The acquired image which is in RGB colour space by satellite are near infrared images which can be used as subject of interest based on the radiation. Edge detection becomes a bottleneck for infrared images as it constitutes with lesser properties in terms of color. A hybrid edge detection algorithm is required to accomplish a better edge detection. Two algorithms are proposed in this process, Firs the edge detection is done in RGB colour space and the significant features extracted are fused. The second method proposed is based on YCbCr image edge detection and fusing the Luminance and R component of the image which shows better edge detection results. © 2019 SERSC.

Department of Electrical Engineering

World University root node

International Journal of Advanced Science and Technology

Hybrid colour infrared image edge detection using RGB-YCbCr image fusion

In this paper, a protection scheme for the microgrid system on low voltage side is proposed as a dc system’s protection techniques are relatively unexplored as compared to the ac systems, whereas the ac systems face numerous problems like frequency matching, reactive power violation and instability. The core objective of the project is to eliminate the faulty section (in the event of occurrence of a fault) promptly while keeping the healthy sections functioning unaltered. In this work, a segment controller exists in the loop type. This has master and slave controllers continually monitoring the segments of grid comprising of semiconductor bidirectional switches and snubber circuits. A master controller is used for all the three segments that monitors the difference between the input and output currents and in the event of the difference being greater than the acceptable limit, instructs the slave controllers to take the required action and eliminate the section under fault. Both line as well as ground faults have been tested on all the sections separately as well as together and perspicuous analysis has been done. It is inferred that the protection scheme is able to isolate the faulty section in a short time and after the faulty section has been eliminated other sections regain their stable voltage and current limits. The protection scheme can identify faults of the grid irrespective of the fault current’s amplitude or the power supply’s feeding capacity. The simulations are designed and verified using MATLAB Simulink 2015a software. © BEIESP.

International Journal of Innovative Technology and Exploring Engineering

Protection of Dc-micro grid from multiple line and ground faults

Detection of suspicious human actions in automated video surveillance applications, is of great practical importance. Those kind of unusual activities in human is very difficult to acquire and classify to predict. In our proposed work, automatic tracking and detecting unusual movement's problems in closed circuit videos was resolved. Firstly, the videos are converted into frames. Then from the obtained frames, humans are detected from the video using a background subtraction method. Then the features are extracted using a convolutional neural network (CNN). The features thus extracted are fed to a Discriminative Deep Belief Network (DDBN). Labeled videos of some suspicious activities are also fed to the DDBN and their features are also extracted. Then the features extracted using Convolutional Neural Network (CNN) are compared against these features extracted from the labeled sample video of classified suspicious actions using a Discriminative Deep Belief Network (DDBN) and various suspicious activities are detected from the given video and results shows increase accuracy of 90% for the proposed framework for classification. © 2019 IEEE.

2019 Innovations in Power and Advanced Computing Technologies (i-PACT)

Detection of Suspicious Human Activity based on CNN-DBNN Algorithm for Video Surveillance Applications

High intensity beams enable the drivers to survey a large portion of the road ahead of them at night. These beams are meant for use when there aren't many vehicles around. However, a lot of drivers make use of these beams while driving because of the convenience of having a larger field of view. These beams often result in momentary partial blindness for drivers in the oncoming lane, causing them to become floundered. In such a state, they tend to lose control and cause accidents. In this paper, we propose a novel method to curb such happenings by automating the high beam and low beam settings of a vehicle. For the purpose of this study, we used a custom prototype, which is also discussed in detail. The solution we propose, if developed into a product, would be available as an add-on module, and if implemented appropriately, will reduce the accidents due to headlight glare by an exponential factor. © 2019 Authors.

Fulltext

International Journal on Smart Sensing and Intelligent Systems

Design of a Modular Beam Control System for Vehicles

In areas where robbery and theft are a major issue, home security becomes a matter of prime importance to the residents of that area. Everyone in the locality is forced to take security measures to prevent their precious belongings from being stolen. It is therefore invincible that a technological solution has to be formulated to ensure the safety of the house. Hence, a security device has been designed to send an alert message to the owner of the house and to the security forces nearby in an attempt to void the theft taking place. The system is designed by interfacing sensor modules with a microcontroller to detect the motion in the house and a GSM module to send alert message to the owner of the house when the house is locked. This system uses low-cost sensors for motion detection and proves to be affordable. The installation of the system is easy and also the sensors and modules require very less space and consume low power when installed. © Springer Nature Singapore Pte Ltd 2019.

Department of Control and Automation

Home Security System Using GSM

In this paper, Auto Regressive eXogenous input (ARX), Auto Regressive Moving Average eXogenous input (ARMAX), Output error and BJ models of class D voltage-source half-bridge series-resonant inverter used for induction heating are identified and studied based on prior knowledge and measured data from PSIM simulation Environment. The output data are generated by applying Pseudo-Random-Binary-sequence (PRBS) as an input through the inverter MOSFET gate in the PSIM software. PRBS signal is generated using standard components such as flip-flops or XOR gates to approximate the white noise in the PSIM software. The generated output and input data are loaded in the MATLAB to identify the unknown system parameters of induction heating inverter by using MATLAB system identification toolbox. Estimation of models with pre-selected structures can be performed using system identification toolbox. To validate the models and their limitations, the fitness properties of the models based on percentage best fit and their resonant frequencies are examined. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019 Published by Springer Nature Switzerland AG 2019. All Rights Reserved.

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST

Modeling of induction heating inverter using system identification

In this paper, combine a Euclidian distance restricted auto encoder foreground extraction techniques to develop a real-time object detection algorithm. The pixels in the initial frames are used to model a zero mean unit variance Gaussian distribution. The new pixels are tested against these models and classified as foreground and background based on their variance ranges. The extracted foreground is then recognized with help of a multilayered auto encoder which gives better efficiency with lesser training data because of the Euclidian distance based restriction and dropout step to avoid over fitting. The efficiency of the method and the neural network are tabulated. © 2006-2019 Asian Research Publishing Network (ARPN).

Department of Information Security

School of Computer Science and Engineering

ARPN Journal of Engineering and Applied Sciences

Automatic object recognition based on Euclidean distance restricted auto encoder

This article gives an algorithm for the calculation of frequency using the morphological prediction of Clarke components (MPCC) given by αβ-transformation. It uses four operators’ dilation, erosion, opening and closing for different types of frequency varying conditions. It also presents the comparison of two algorithms, MPCC and PLL, in real time signal by creating a grid in MATLAB Simulink. The algorithms were tested with two types of faults, symmetrical and unsymmetrical faults, at the same time the later algorithms will be compared with two types of loads such as linear and non-linear loads. These demonstrations show us, how accurate the MPCC is when compared to PLL in estimating frequency. © 2019 SERSC.

Accurate frequency tracking using morphological predication of clarke components

This paper proposes a standalone singe stage PV fed air cooler which consists of two motors (fan blower and water pump). The proposed system comprises of PV source, reduced switch inverter and two PMSM drive. The proposed system aims at reducing the switching losses and overall cost by using reduced switch inverter. The reduced switch inverter uses only eight switches whereas the conventional VSI utilizes twelve switches. In the proposed scheme, blower and pump are independently controlled using field oriented control scheme where speed reference is obtained using Perturb and Observe (PO) technique. Simulation studies for the proposed PV fed two 400 W PMSM driven blower and pump is performed using MATLAB platform and respective results are presented to show the efficacy of the system. © 2018 IEEE.