Enhanced fingerprint recognition and OTP to improve ATM Security
In the previous few years’ robberies of ATM is increasing and becoming a problem for Banks. In the current system, we operating ATM using a PIN number which can be stolen or guessed and can be hacked during the transaction. That raises a question on the present security and demands something new in the system which can provide the second level of security. So for that in this paper, there is added some extra security to the current ATM Systems. We use the fingerprint system and One Time Password (OTP) which is sent to the user registration mobile number through GSM Module system. After that, the user will be able to complete the transaction securely. The working of this ATM machine is when the customer places his finger on the fingerprint module when access it automatically generates different 4-digit code as a message every time to the mobile of the authorized customer through GSM modem which is connected to the microcontroller [1]. The code received by the customer should be entered by pressing the keys on the keypad provided. This proposal will go a long way to resolve the problem of bank account safety and transaction.
Published by: Shivam Kumar Rajput, Aniket R. Patne, Amit Varma, Girish Vishe
Author: Shivam Kumar Rajput
Paper ID: V5I2-1815
Paper Status: published
Published: April 10, 2019
Prediction of Pneumonia using deep learning
The project is to classify pneumonia by processing the image of chest X-ray using diverse deep learning algorithms. For classification purpose, we have to develop an algorithm which can most accurately predict on a validation set of chest X-rays. Deep learning is very helpful in automatically discovering chest diseases at the experts level, providing the two Liberian radiologists with some respite and used for saving countless lives potentially worldwide. The problem is solved using Convolution neural networks[9]. Convoluted neural networks are used to classify where each neuron is tightly connected to other neurons. Inception network was used in the development of CNN classifiers. Inception network was heavily engineered. It used a lot of tricks to improve performance in terms of speed and accuracy. With much more robust and large dataset our project can intervene in all domains.
Published by: A. Raghavendra Reddy, G. Sai Ravi Teja, D. Sai Tej, P. Vinod Babu
Author: A. Raghavendra Reddy
Paper ID: V5I2-1546
Paper Status: published
Published: April 10, 2019
The future of food preservation: Nanotechnology
Nanotechnology has been used to treat illnesses for a long time. It has been successfully employed as a means of drug discovery. However, it's used in food preservation is yet to become commonplace. Through this review paper, the authors wish to throw light on the application of nanoparticles in the preservation of food, to improve food color, texture as well as flavor. We also explore the use of nanotechnology in the encapsulation of the foodstuffs as a means of preservation. The article includes details about the usage of nanoparticles in the nutraceutical industry as well as its usefulness as a nanosensor. The purpose of the paper is to make use of nanotechnology in the food industry a well-known application of nanoparticles. It will be useful for professionals working in the food industry or entrepreneurs who wish to venture into the field of food preservation. Scientists may use the information and data provided in the paper to further their research.
Published by: Pragati Gupta, Anjika Shukla, Ujjawal Sharan, Anand Prem Rajan
Author: Pragati Gupta
Paper ID: V5I2-1823
Paper Status: published
Published: April 9, 2019
An energy efficient approach for data aggregation in wireless sensor networks based on sink mobility
A network that does not include any central controller and allows nodes to enter or leave the network at any time is known as a wireless sensor network. There are very small sized nodes deployed in these networks in large areas. The energy consumption of the nodes in these networks is a major concern since it directly affects the lifetime of the network. These dead node cause several problems. To enhance the network lifetime mobile sink is introduced which improve network performance. But mobile also leads to another challenge such as mobile sink scheduling and (re)routing. The complete network is divided into fixed size clusters and based on the energy and distance, cluster heads are chosen from the clusters. The remaining nodes of the cluster are considered to be individual. Several clustering algorithms have been designed by researchers which can be broadly categorized based on the manner in which clusters are formed and the kinds of parameters included during the selection of cluster heads. This research focuses on aggregating the data from cluster heads by deploying multiple mobile sinks. The bee colony algorithm is used to make the base station mobile. The simulation of the proposed technique is performed in MATLAB and results are analyzed in terms of various parameters.
Published by: Baljinder Singh, Amit Verma, Manit Kapoor, Dr. Naveen Dhillon
Author: Baljinder Singh
Paper ID: V5I2-1755
Paper Status: published
Published: April 9, 2019
Geofencing for disaster information system
Due to the lack of effective and coordinated disaster management system which consists of the stages like disaster mitigation, preparedness, response, and recovery has led to both the increase in the loss of both life and property. The paper proposes an effective disaster information system which uses the geofencing technique so as to detect the movement of users. This technique creates a geofence around the user and thus monitors the user’s entry and exit from the fence. This model uses a K-Nearest Neighbour (KNN) algorithm along with real-time data collected from smartphones. For crowd disaster mitigation and real-time alert to avoid an occurrence of a stampede, this android application is an easily deployable context-awareness mobile Android Application Package. The application provides high accuracy when the user is in the fence.
Published by: Diksha Kewat, Vaishnavi Tonpe, Kiran Baxani, Dr. Sanjay Sharma
Author: Diksha Kewat
Paper ID: V5I2-1813
Paper Status: published
Published: April 9, 2019
A novel approach for active safety system
In this modern day automotive world, the occurrence of accidents is much more due to several factors. This can be avoided when the driver is alert. So a system has to be developed which gives the driver the information about the nearby vehicles whether it is a danger, no danger, potential danger. This paper presents you how to classify the vehicles in its ROI and categorize their stage of danger. Specifically, stereo cameras and Millimeter Wave (MMW)-radar are fused to help the driving ego-vehicle. Cameras are used to identify near lateral dynamic objects and MMW radar to detect far longitudinal objects. This process is simulated using python using CV2 library, numpy library.
Published by: Devaharsha Meesarapu, V. V. Sai Rama Datta, G. Sai Krishna Chaitanya
Author: Devaharsha Meesarapu
Paper ID: V5I2-1799
Paper Status: published
Published: April 9, 2019
