COVID-19 pandemic has rapidly affected our day-to-day life disrupting the world trade and movements. Wearing a protective face mask has become a new normal. In the near future, many public service providers will ask the customers to wear masks correctly to avail of their services. Therefore,face mask detection has become a crucial task to help global society. This paper presents a simplified approach to achieve this purpose using some basic Machine Learning packages like Tensor Flow,Keras, OpenCV and Scikit-Learn. The proposed method detects the face from the image correctly and then identifies if it has a mask on it or not. As a surveillance task performer, it can also detect a face along with a mask in motion. The method attains accuracy up to 95.77% and 94.58% respectively on two different datasets. We explore optimized values of parameters using the Sequential Convolutional Neural Network model to detect the presence of masks correctly without causing over-fitting.

Keywords : Masked face detection,Facemask classification and recognition.

Author : D. NIKHITHA SRI, P. CHANDANA, N. JAHNAVI, RESHMA SULTANA, Dr.S.M.ROY CHOUDRI

Title : REAL-TIME FACE MASK PREDICTION AND BODY TEMPERATURE IDENTIFICATION

Volume/Issue : 2021;03(4)

Page No : 1-4

Machine learning is an important decision support tool for crop yield prediction, including supporting decisions on what crops to grow and what to do during the growing season of the crops. Agriculture depends on the various soil properties.Production of crops is a difficult task since it involves various factors like soil type, temperature, humidity etc. If it is possible to find the crop before sowing it, would be of great help to the farmers. Machine learning in agriculture is used to improve the productivity and quality of the crops in the agriculture sector. Use of appropriate algorithms on the sensed data can help in recommendation of suitable crop. This system thus reduces the financial losses faced by the farmers caused by planting the wrong crops and also it helps the farmers to find new types of crops that can be cultivated in their area. To predict the crop yield in future accurately Random Forest, a most powerful and popular supervised machine learning algorithm is used.

Keywords : Crop Analysis; Crop Yield; Machine learning; Prediction; Supervised algorithms.

Author : M.Samba SivaRao, K.Jyothi , K.Giridhar , P.Baby Anitha , M.Abdul Rahim

Title : CROP PREDICTION SYSTEM USING MACHINE LEARNING

Volume/Issue : 2021;03(4)

Page No : 5-9

Machine Learning techniques have been used to predict whether patients are infected by the virus based on symptoms defined by WHO and CDC. Machine Learning is also used to diagnose the disease based on x-ray images. For instance, chest images of patients can be used to detect whether a patient is infected with COVID-19. Covid 19 symptoms prediction using machine learning through chatbot is the project implemented. Basically the chatbot considered works under the technique called Natural Language Processing (NLP).Natural Language Processing is the field in Artificial Intelligence which helps to understand the human language by the chatbot. The chatbot created in the project is using Amazon Alexa. This does not any training data sets, as the bots has the datasets itself

Keywords : Machine learning, Natural Language Processing,Chatbot,Amazon Alexa.

Author : G.Balaiah S.Yagnya Deepika,P.Sri Krishna Chaitanya,S.Sai Teja,K.Hari Narayana

Title : Covid-19 Symptoms Prediction Using Chatbot (Machine Learning)

Volume/Issue : 2021;03(4)

Page No : 10-13

n the current time of drastic and revolutionary changes, it is imperative to radically rethink business models and archetypes in general. Traditional financial services providers, banks in particular, are lagging behind the pace of technology development. According to one report from Accenture, most large banks use systems from the 1970s or even the 1960s, and newer computing technologies are simply laid on top of this foundation to support providing banking services online or via mobile devices. Currently, the global financial system is enormous, but it is very cumbersome to transfer money. Financial middlemen are required to transfer any sum of money, each of which takes a service charge. During the transfer of money, the frauds may occur and there will be a huge loss in the economy. Blockchain reduces the number of middlemen while increasing the security, both of which will reduce costs.

Keywords : Blockchain, distributed systems, money transfer, security

Author : B.S.Vara Prasad, G.Mahathi, P.Sree Sai Deeksha, G.Keerthi Reddy, G.Vamsi Krishna

Title : An Invulnerable Money Transfer using Block chain

Volume/Issue : 2021;03(4)

Page No : 14-17

Diabetes is a chronic disease with the potential to cause a worldwide health care crisis. According to International Diabetes Federation 382 million people are living with diabetes across the whole world. By 2035, this will be doubled as 592 million COVID-19 pandemic has rapidly affected our day-to-day life disrupting the world trade and movements. In this situation diabetic patient standing in the queue is a critical issue. Diabetes mellitus or simply diabetes is a disease caused due to the increase level of blood glucose. Various traditional methods, based on physical and chemical tests,are available for diagnosing diabetes. However, early prediction of diabetes is quite challenging task for medical practitioners due to complex interdependence on various factors as diabetes affects human organs such as kidney, eye, heart,nerves, foot etc. Data science methods have the potential to benefit other scientific fields by shedding new light on common questions. One such task is to help make predictions on medical data. Machine learning is an emerging scientific field in data science dealing with the ways in which machines learn from experience. The aim of this project is to develop a system which can perform early prediction of diabetes for a patient with a higher accuracy by combining the results of different machine learning techniques. This project aims to predict diabetes via four different supervised machine learning methods including: KNN, Logistic regression, Decision Tree, Random Forest. This project also aims to propose an effective technique for earlier detection of the diabetes disease.

Keywords : Machine Learning, Supervised, Knn, Decision tree, Random forest, Logistic Regression

Author : Ch.Niharika, A.Hima Bindu, A.Mounika, G.Kiranmai

Title : Prediction of Diabetes Using Machine Learning

Volume/Issue : 2021;03(4)

Page No : 18-21

Walmart gross sales forecasting using machine learning analysis and predicting the future sales in this information age is indeed a breath taking task. One such way to deal with the scenario by using machine learning; analyze the data set of Walmart and predicting the future sales which is most important aspect of strategic planning. Here machine learning algorithms are used which take the historical data as input to predict new output. So, in our projects future sales are predicted using these algorithms by choosing the algorithm which gives best accuracy and analyzed by adding the new features which in turn predicts the future sales.

Keywords : Walmart, machine learning analysis, information age

Author : S.Mounika, Y.Sahithi, D.Grishmi, M.Sindhu, P.Ganesh

Title : Walmart Gross Sales Forecasting Using Machine Learning

Volume/Issue : 2021;03(4)

Page No : 22-27

The Block chain technology is new technology in digital platform for making transactions in decentralized manner.Blockchain is uses from last some year for bitcoin. over the last ten years, the record-keeping technology behind the Bit coin network is blockchain. In blockchain Each block contains a cryptographic hash of the previous block, a timestamp, and transaction data. So, for identity card it is noticeable for security. If we implement blockchain technology for digital identity card it is very secure for the user. Identity card has personal information and some important information included. The identity card like Aadhar card, pan card, etc. have lot personal and important information, if we are not using securely then it will use for any illegal work which is harmful. Now these identity cards are stored in file with encryption method which will hacked by hackers. So we propose our system for e-identity card using blockchain technology. In our proposed system we are using blockchain and IPFS server which is immutable server which helps us to system will more secure. Once one transaction will done before the transaction the block will be created which is hash of information like date, time etc. and this block send toblockchain which will maintain all block. For implement the blockchain we will use Ethereum platform. This solution is secure and more trusted than traditional models.

Keywords : Blockchain, Identity card, IPFS server, Ethereum.

Author : V.V.Bhavani, K.Saisri, K.Naveen, M.Lalitha

Title : PERSONALISED SECURE E-IDENTITY CARD

Volume/Issue : 2021;03(4)

Page No : 28-32

This project is to develop an integrated application based on visual positioning service (VPS)using augmented reality which is applicable on IOS applications. This can be deployed in any other IOS based applications and can be integrated like part of their applications. When the user access this part in the application, it enables the camera automatically and projects on to the environment in which it shows the real world to the user. And the application enable the user to choose the best path direction to reach the destination that which will be determined by the algorithms we used in our project .This application has no time limit, the reason behind not using time limit is, the user like to see the surroundings, textures and objects which are present inside a building. The application allows the user to start accessing the location at any initial point and ends at the final destination which has chosen by the user.

Keywords : Augmented Reality, Visual Positioning Service, Destination, AR Kit, Unity.

Author : Dr.K.P.N.V.SATYA SREE, M.SHANMUKHA SAI KAVYA, SYED RESHMA SULTHANA, S.GEETHANJALI, CH.SOMA SAI MANIKANTA

Title : INDOOR NAVIGATION USING AUGMENTED REALITY

Volume/Issue : 2021;03(4)

Page No : 33-37

It is very difficult to secure a job in a company. People manipulate their documents with fake information to find a job. Multinational National Companies are investing heavily to verify the background details of the job applicants. But, the background verification process implemented by these companies is extremely costly, time-consuming, and inefficient. To resolve this problem, we present a working prototype of a solution using Block chain technology where the hash values of all the original documents of a job applicant provided by various organizations are saved on a consortium block chain. The job applicant’s details can be verified during the hiring process by comparing the hash value of the given document with the hash value of the document present on the block chain.

Keywords : Block chain, Hash Value, Background Verification prose.

Author : B.V. Praveen Kumar, K. Varshini, D. Manasa, V. Ramya,N. Mohith Kumar

Title : EMPLOYEE BACKGROUND CHECK USING BLOCKCHAIN

Volume/Issue : 2021;03(4)

Page No : 38-42

This project deals with the analysis, or prediction of pacing COVID cases by using machine learning algorithms. The goal is to provide the users with the information about cases in and around withthe help of a web application.so whenever someone needs to travel, they would know-how safe or unsafe the desired place could possibly be to make a way to dexterity.The spread of covid-19 in the whole world has put the humanity at risk. the resources of some of the largest economies are stressed out due to the large Infectivity and transmissibility of this disease. Due to the growing magnitude of number of cases and its subsequent stress on the administration and health professionals, sum prediction methods would be required to predict the number of cases in future.The highly infectious corona virus disease covid-19 was first detected in Wuhan, China in December 2019 and subsequently spread to 212 countries and Territories around the world, infecting millions of people.in India, a large country about 1.3 Billion people, the disease was first detected on January 30,2020, in a student returning from Wuhan .the total number of confirmed infections in India.

Keywords : COVID-19, prognosis of cases, prediction.

Author : P.BhagyaSri, D. JessyMercedes, H.ChaitanyaReddy, A.LasyaPriyaReddy,P.Y.M.NaveenKumar

Title : COVID-19 CASES PREDICTION FOR NEXT 30 DAYS USING MACHINE LEARNING

Volume/Issue : 2021;03(4)

Page No : 43-46

Our Project is to develop the technique for fingerprint authentication and facial recognition in ATMs. This target can be mainly decomposed into image pre-processing, feature extraction and feature match. For each sub-task, some classical and up-to-date methods in literature are analyzed. Based on the analysis, an integrated solution for fingerprint recognition, facial recognition and authentication is developed for demonstration. For the program, some optimization at the coding level and algorithm level are proposed to improve the performance of my fingerprint and facial authentication system. These performance enhancements are shown by experiments conducted upon a variety of fingerprint and facial images. Also, the experiments illustrate the key issues of fingerprint recognition and facial recognition that are consistent with what the available literature says "The underlying principle is the phenomenon of biometric and facial “AUTHENTICATION”. In this project we propose a method for fingerprint matching and face matching based on minutiae matching."

Keywords : Fingerprint, Face, Authentication, detection, recognition

Author : B. Siva Ganga, D. Akhila, K. Dhanush, M. Lalitha, P. Ramurthy

Title : FINGERPRINT AUTHENTICATION AND FACIAL RECOGNITION FOR ATM

Volume/Issue : 2021;03(4)

Page No : 47-50

As the human life is heading towards busy schedule it becomes necessary to automate our home appliances.Human error is something that cannot be completely erased. With the busy schedule in hand there is defiantly a possibility of missing something that may be trivial to us but can result into a catastrophe. For these reasons Our Project home automation can increase efficiency, security and reliability. AR which has recently evolved for the automation of various electricalappliances by popping virtual objects into real world.

Keywords : Augmented Reality, Automation, Microcontroller, web interface.

Author : Subramani Roy Choudri, A. Divija, G. V V N Vijayalakshmi, P. Vamsi

Title : TOUCHLESS HOME AUTOMATION USING AUGMENTED REALITY

Volume/Issue : 2021;03(4)

Page No : 51-55

Entity recognition plays an important role in many natural language processing tasks, such as relation detection and information extraction. This paper presents a novel method to recognize entities in financial news. Investment named entity recognition helps the investors by validating the start-up in which they can invest by predicting the profit they get. Investment named entity help to know how much profit investors get by spending how much money in a start-up. The prediction of profit is made by using a machine learning method that is multiple linear regression.

Keywords : Multiple linear regression, Machine learning, Profit.

Author : G. Baleswari, K. Alekya, N. Bhavani, G. Yamini Durga, D. Mahitha

Title : INVESTMENT NAMED ENTITY RECOGNITION

Volume/Issue : 2021;03(4)

Page No : 56-60

In our country we have government bodies (Municipal Corporation) which are responsible for maintaining and running cities. It’s all their responsibilities to address the complaint of citizens. For this Municipal Corporation has 2 ways, in first cameras or other surveillance devices have to be installed and second way is that citizens could report their problem to the municipal corporation. The second way is mostly used because it is cheaper as compared to first one.GRIEVANCE MONITORING AND ANALYSIS SYSTEM will help officers at Municipal Corporation to solve/reject and analyze complaint with reasons and monitor the status of complaint. The Aim for creating this Application is to simplify the process of lodging complaint to respective Municipal Corporation and make it quick and cheaper.The citizen can easily register his/her grievance to the Municipal Corporation using this system through online. The citizen can himself check the status of the grievance from the system rather going to the MC. He/she may also give suggestions to respective persons of MC through this system. He can also check the status of the suggestion whether it is being taken into consideration or not.

Keywords : Grievance,Municipal Corportion,Citizen,Officer,Operator,Supervisor.

Author : G.Balaiah, M.Chandrika, P.Rambabu, B.Chandana, R.Hima bindu

Title : GRIEVANCE MONITORING AND ANALYSIS SYSTEM

Volume/Issue : 2021;03(4)

Page No : 61-63

Blockchain have been an interesting research area for a long time and the benefits it provides have been used by a number of various industries. Similarly, the healthcare sector stands to benefit immensely from the blockchain technology due to security, privacy, confidentiality and decentralization. Nevertheless, the Electronic Health Record (EHR) systems face problems regarding data security, integrity and management. In this paper, we discuss how the blockchain technology can be used to transform the EHR systems and could be a solution of these issues. We present a framework that could be used for the implementation of blockchain technology in healthcare sector for EHR. The aim of our proposed framework is firstly to implement blockchain technology for EHR and secondly to provide secure storage of electronic records by defining granular access rules for the users of the proposed framework. Moreover, this framework also discusses the scalability problem faced by the blockchain technology in general via use of chain storage of the records. This framework provides the EHR system with the benefits of having a scalable, secure and integral blockchain -based solution.

Keywords : Block Chain, Distributed Systems, Electronic Health Records, Medical Informatics

Author : M.Samba SivaRao , B.Pujitha , B.Hemanth , K.Jayasree

Title : Electronic Health Record Management Using Blockchain Approach

Volume/Issue : 2021;03(4)

Page No : 64-67

Activity recognition is one of the most important technology behind many applications such as medical research, human survey system and it is an active research topic in health care and smart homes. Smart phones are equipped with various built-in sensing platforms like accelerometer, gyroscope,GPS, compass sensor and barometer. We can design a system to capture the state of the user. Activity recognition system takes the raw sensor reading from mobile sensors as inputs and estimates a human motion activities and users usually carry their smartphone with them. These facts make HUMAN ACTIVITY RECOGNITION more important and popular. This work focuses on recognition of human activity using smartphone sensors using deep learning approaches like Recurrent Neural Network (RNN). This paper presents a human activity recognition (HAR) system that uses accelerometer and gyroscope data obtained from a smartphone as inputs to a bidirectional long short-term memory (LSTM) model of the RNN model network. Six human activities were recognized: sitting, standing, laying, walking, walking upstairs, and walking downstairs. Results of the approaches used are compared in terms of efficiency and precision.

Keywords : Smart phones, Accelerometer, Gyroscope, Activity Recognition, Long short term memory, deep learning

Author : Mr.G.Balaiah,G.Yamini,V.SatyaSimha,K.Hyndavi

Title : HUMAN ACTIVITY RECOGNITION USING SMART PHONE

Volume/Issue : 2021;03(4)

Page No : 68-71

This project deals with implementation and design of Smart Vision Security System using Raspberry. And is proposed along with the face detection technique. It uses wireless technology to provide essential security and captures information and transmits via a WIFI to a static IP, which is viewed through telegram. Telegram bot controls the video camera for survelliance. It receives images, 10 sec video from system as soon as intruder is detected. The camera automatically initiate recording when intruder is detected and Raspberry pi device stores it in a secured folder.

Keywords : Internet of things, Raspberry pi, pi camera.

Author : Dr.K.P.N.V.Satya Sree, U.V. Vaishnavi, S.N.V.Sindhu, P.Mohana Krishna, Y.Sree Archana

Title : IOT Based Smart Vision Security System

Volume/Issue : 2021;03(4)

Page No : 72-75

Research on Medical Image proposes an efficient platform for automatic analysis and detection of any Deformations in a given medical image data set especially in Spinal Cord for an effective and better understanding of diagnosis. The abnormality of the spinal cord may include Tumor,Disc a hernia, Fracture, swelling etc., which has been detected from any given modality of Medical images such as MRI, CT, and fMRI etc. In this work, Automated Decision support system is introduced for fast and accurate analysis which will help to confirm the existence of abnormality of the Spinal Cord MR image. Lower back pain can be caused by many complications with any parts of the body in the lumbar spine. The compilation of a medical diagnosis is crucial to the medical practitioners in order for them to give a convenient treatment for the low back pain.to solve this problem, we like to give a solution by finding the abnormality in Lumbar spine. ABNORMALITY FEATURE EXTRACTION IN SPINAL CORD MRI helps the patients or end users to find the abnormality in the spinal cord which can save the time for the doctors and also the end users.

Keywords : Medical Image like Magnetic Resonance Imaging(MRI), Deep learning, CNN,Tensor flow, Classification, Framework.

Author : M.Samba Siva Rao, K.Srujana, N.Srihari, G.Amulya, V.Rajesh

Title : ABNORMALITY FEATURE EXTRACTION IN SPINAL CORD MRI

Volume/Issue : 2021;03(4)

Page No : 76-81

All metropolitan cities face traffic congestion problems especially in the downtown areas. Normal cities can be transformed into “smart cities” by exploiting the information and communication technologies (ICT). The paradigm of Internet of Thing (IOT) can play an important role in realization of smart cities. This proposes an IOT based traffic signal solutions for smart cities. Now a days we are seeing and listening accidents near traffic signals due to over speed. Because they don’t know which signal light is currently there. So, to overcome this problem we want to design a mobile application. In that application it will show the colour of the signal and time limit of the signal with the help of this the driver can decrease the speed or increase the speed. So we can reduce the accidents and we can consume the fuel. This will display when a driver is 500mts away from the traffic signal. However the scheme proposed is general and can be used in any Metropolitan city without the loss of generality.

Keywords : Internet of things, traffic intimator, ESP32, IR sensor.

Author : S. Mounika A. Sandhya Lakshmi M. Bhavana K. Siva sai G.L.N. Suresh

Title : Traffic Signal Intimator using IOT

Volume/Issue : 2021;03(4)

Page No : 82-84

Technology is being advanced day by day. As we are tech enthusiasts, we are always keen to learn the updated once. Technology is used to solve many problems in modern world, and introducing new features into the world. Many remote areas are lack at hospitals, as doctors always have minute to minute cases. As doctors are busy at their cases, they are unable to attend or visit the remote areas where there is lack of transportation too. Due to these problems, people from remote areas are suffering from diseases which are known and unknown. This might also spread the unknown diseases to animals and plants too. Our project “Health Analyzer”, predicts the disease from input symptoms said by the patient, predicts the disease with prescribed medicines. We designed this for remote areas, where people unable to visit hospitals in the city and due to lack of transportation too. So, we help them in detecting the disease and prevent it from early stage.

Keywords : Pneumonia , Chest X-ray Images , Covolutional Neural Network

Author : Ch.Niharika ,K.Haneesha , K.Jyothsna , M.Esther Rani , G.Chaitanya Krishna Sai

Title : DETECTION OF PNEUMONIA FROM X-RAY IMAGES USING DEEP LEARNING

Volume/Issue : 2021;03(4)

Page No : 85-90

In the digitalized modern world in parallel to the new technological developments,information security has become the highest priority in the individual and institutional sense. In order to ensure the security of information systems, various systems are used techniques and technologies,including encryption, authorization, firewall, honeypot based systems. In this study, a honeypot based approach for intrusion detection/prevention systems (ID/PS) is proposed. The developed honeypot server application is combined with IDSs to analyze data in real-time and to operate effectively. Moreover, by associating the advantages of low and high-interaction honeypots, a superior hybrid honeypot system is performed. Therefore, in order to reduce the cost of configuration, maintenance, and management, after viewing the usage of honeypots on corporate networks, virtualization technologies are used. The developed system is a honeypot based intrusion detection and prevention system (IDPS) type and it is able to show the network traffic on servers visually in real-time animation. Thereby, it provides system information easily. Finally, the developed system can detect zero-day attack due to the configuration of intrusion detection, which makes it superior in performance compared to other IDSs. This system also helps in reducing the false positive level in IDSs.

Keywords : honeypots , anaconda , telegram , firewall

Author : V.V.Bhavani , K.Lakshmi Prasanna , N.Yaminidevi , S.Poorna Chandra rao

Title : INSIDER THREAT DETECTION USING HONEPOTS

Volume/Issue : 2021;03(4)

Page No : 91-96

In the real-estate field, it is very important for the land to have accurate records which identifies the current owner and as much of the ownership history as possible, which is not been perfectly existing in the current world. As land registration involves number of intermediaries to trust the system, a centralized one which is volatile and mostly tracking of the ownerships is highly tricky and leads to court battles. Rather, what if we have a system which could handle the property registrations and title transfer process? “Blockchain Technology using Smart contracts “ Using a Programmable Blockchain, Ethereum, developing a Land registration system which could handle the land registrations and title transfer process having real time track of previous ownerships of the land as well as immutable land insights.

Keywords : Ethereum, ledger, Smart contracts, ERC 20, MetaMask, Ganache, lite-server, truffle framework.

Author : Dr. K. P N V SATYA SREE , T. Teja Sri, K. Bhaskar Sai Varma, A. Mahesh , P. Anil

Title : Blockchain Based Land Registration System

Volume/Issue : 2021;03(4)

Page No : 97-100

Melanoma is considered as one of the fatal cancer in the world, this form of skin cancer may spread to other parts of the body in case that it has not been diagnosed in an early stage. Thus, the medical field has known a great evolution with the use of automated diagnosis systems that can help doctors and even normal people to determine a certain kind of disease. In this matter, we introduce a method for melanoma skin cancer detection that can be used to examine any suspicious skin. Our proposed system rely on the prediction of different methods: A convolutional neural network and trained with a set of features describing the borders, texture and the color of a skin lesion. This method is then combined to improve their performances using RESNET15v2. The experiments have shown that using the method together, gives the highest accuracy level. Melanoma remains the most harmful form of skin cancer. Convolutional neural network (CNN) based classifiers have become the best choice for melanoma detection in the recent era. The research has indicated that classifiers based on CNN classify skin cancer images equivalent to dermatologists, which has allowed a quick and life-saving diagnosis. Moreover, proposed taxonomy for melanoma detection has been presented that summarizes the broad variety of existing melanoma detection solutions. Lastly, proposed model, challenges and opportunities have been presented which helps the researchers in the domain of melanoma detection.

Keywords : Melanoma Image, Deep Learning, Convolutional Neural Network,Feature Extraction.

Author : B. V. Praveen Kumar, P.Supraja, G. Akhileswar, CH. Greeshma, D.Charan

Title : MELANOMA DETECTION USING DEEP LEARNING

Volume/Issue : 2021;03(4)

Page No : 101-106

Technology is being advanced day by day. As we are tech enthusiasts, we are always keen to learn the updated once. Technology is used to solve many problems in modern world, and introducing new features into the world.Many remote areas are lack at hospitals, as doctors always have minute to minute cases. As doctors are busy at their cases, they are unable to attend or visit the remote areas where there is lack of transportation too. Due to these problems, people from remote areas are suffering from diseases which are known and unknown.This might also spread the unknown diseases to animals and plants too.Our project “Health Analyzer”, predicts the disease from input symptoms said by the patient, predicts the disease with prescribed medicines. We designed this for remote areas, where people unable to visit hospitals in the city and due to lack of transportation too. So, we help them in detecting the disease and prevent it from early stage.

Keywords : Admin: login admin to the software and enter the patient details. Patient: Patient gives his/her details and symptoms he/she suffers from.

Author : P. Bhagyasri, CH. Devi, K. Yamini, D. Omkar Sai Prasad, K. Soma SekharaVaraPrasad

Title : HEALTH ANALYSER USING MACHINE LEARNING

Volume/Issue : 2021;03(4)

Page No : 107-113

Democratic voting is a crucial and serious event in any country, the current voting scheme in any country is through ballot paper or by use of EVM. These processes have many drawbacks such as transparency, low voter turn-out, tampering of votes, distrust in the election body, forging of unique Id (voter id card), delay in giving out results and the most important is security issues. Security of digital voting is always the biggest concern when considering to implement a digital electronic voting system. With such monumental decisions at stake, there can be no doubt about the systems ability to secure data and defend against potential attacks. One way the security issues can be potentially solved is through the use of blockchain technology. Blockchain technology offers infinite number of applications. Blockchain is a distributed ledger technology that allows digital assets to be transacted in a peer-to-peer decentralized network. A distributed ledger technology is an exciting advancement in this regard. Block is a collection of all the transactions. Blockchain possess salient features such as immutability, Decentralization, Security, Transparency and anonymity. Blockchain with smart contracts emerges as a promising candidate for building a safer, secure and transparent E-voting systems. In this paper we have implemented and tested a sample e-voting application as a smart contract for the Ethereum network using the blockchain technology through wallets and the Solidity language. Limited amount of token(gas) is given in the wallet which is exhausted when the user votes thus preventing duplicity of votes. This paper also highlights the pros and cons of using blockchain technology and also demonstrates a practical system by showcasing a web app for voting and its limitations.

Keywords : E-Voting , Smart contracts, Blockchain, Ethereum

Author : Dr. K.P N V SATYASREE, K.Dharani, J.Prasanna, A. S V R Seshu

Title : Electronic Voting Using Blockchain Technology

Volume/Issue : 2021;03(4)

Page No : 114-118