Online ISSN- 2457-0818



Vol 6, No 3 (2021): Discriminative Robust Local Binary Patterns for Effective Face Detection Using Machine Learning

Authors: M .Shalimar Sulthana, C. Naga Raju

Abstract: Machine learning makes the systems to find, capture, store and analyse the facial features automatically. Face recognition has a major role in interpretations of expressions for identifying human faces. In the area of machine learning facial recognition is a challenging problem and lots of attempts were made for identifying invariant features of face but they recognize the face when it is completely visible. In this paper some of the techniques are investigated and proposed discriminative robust local binary patterns technique (DRLBP) for classification of face images with different emotional expressions and rotation variant images. For database construction GLCM with six features is applied on the output of DRLBP and multi linear regression classifier is applied for classification. The accuracy is estimated by using confusion matrix. The experimental results are calculated it’s clearly observed that our proposed method shows better accuracy.

Keywords: LBP, PCA, DRLBP, MLRM and GLCM

Vol 6, No 3 (2021): Study on Customer Perceptions from Online Food Ordering Websites

Authors: Swati Terak, Neha bhardwaj

Abstract: In the present world everyone wants comfort in any work and technology is also developing fast. So, people are taking advantages of online technologies for doing their most of the work by comfort from their home. From one of these technologies online food ordering websites is also the best way to the food lovers/customers for order food online. This has been developed by looking on the convenience of the people. In this method of online food ordering through the web application, customers can do this process by following few methods by using the food ordering website from their home. It is the easiest way of order food online and provides comfort for food lovers without traveling anywhere. Customers can order their preferable food items from the available food items list on online food ordering websites. This way of online food ordering has many advantages so; most of the people prefer this way to order food online.

Keywords: Customer Perceptions, Online Food Ordering, Food ordering website

Vol 6, No 3 (2021): A Review on Artificial Neural Network and Sign Languages Detection Using Deep CNN

Authors: Al Mahmud Al Mamun, Md. Rakibul Hasan, Md. Mokhlesur Rahman, Md. Mahbubur Rahman, Sondip Poul Singha, Md. Yasin Khan

Abstract: Artificial Neural Networks is a computational model inspired by the structures and functions of biological neural networks. Artificial neural networks are used in all sectors of the recent world with its life-changing applications. In this paper, we review artificial neural networks. We specially focus on the history, architecture, learning technique of the artificial neural networks. Sign language is a visual communication system between hearing-impaired or hard of hearing people. The communication foundations are based on finger shapes, hand shapes, hand movements in space concerning the body, hand orientations, and facial expressions. In this paper, we have proposed a Deep Convolutional Neural Network to recognize the hand gestures. Our system uses the pre-processed images for training and is capable of extracting signs from video sequences under minimally cluttered and dynamic backgrounds using skin color segmentation. In our method, 44 signs of the five fingers are defined. The static images have been pre-processed as grayscale images and the model is trained with 100 numbers of images for each sign. Our proposed model has achieved an accuracy rate of 95.6 % for the five test images.

Keywords: Artificial Neural Networks, Deep Convolutional Neural Networks, Hand gestures, Sign language recognition

Vol 6, No 3 (2021): Online Voting System

Authors: Ashish Patil, Franklin Almeida, Abiyel Gaikwad, Shridhar Shiradwade, S.A Shinde

Abstract: The principle objective of the majority rules system is "vote" by which individuals can choose the contender for forming a proficient government to fulfil their requirements and demands to such an extent that their standard living can be improved. An internet casting a ballot framework for Indian political decision is proposed without precedent for this paper. The proposed model has a more noteworthy security as in citizen high security secret word is affirmed before the vote is acknowledged in the fundamental information base of Election Commission of India. The extra element of the model is that the citizen can affirm if his/her vote has gone to address up-and-comer/party. In this model an individual can likewise cast a ballot from outside of his/her apportioned body electorate or from his/her favored area.

Keywords: E-Voting machine, Online election system, Online voting system, E-Polling station, E-ballet.)

Vol 6, No 2 (2021): Different Approaches to Classify Melanoma and Cure Methods

Authors: Rashmi Patil, Sreepathi Bellary

Abstract: Melanoma is very harmful form of skin cancer and is accountable for over 70 percent of deaths from skin cancer, also known as the deadliest form. Melanomas arise from melanocytes which are malignant. Melanoma is an aggressive form of skin cancer that is rising rapidly. Because of this feature, one of the fastest-growing cancers worldwide remains malignant melanoma. It is important to detect it at an early stage in order to decrease the death rate due to malignant melanoma skin cancer. The price and the time taken for doctors to detect melanoma in all patients is more. Many cases of cancer are misdiagnosed early on as something else that leads to significant effects, like a patient's death. There are also cases where patients have other issues and doctors believe they may have skin cancer. Here, we have reviewed the problem of the classification of melanoma and its treatment. Hence presented a review on classification techniques used by different researchers and some cure approaches used by doctors. Because the wrong classification of skin cancer or melanoma leads to wrong cure method so needs to classify melanoma correctly for early diagnosis and treatment.

Keywords: Melanoma, Cure Methods, Fastest-Growing Cancers, Diagnosis and Treatment

Vol 6, No 2 (2021): Bird Species Classification Using Multi-Scale Convoluted Neural Network with Data Augmentation Techniques

Authors: Pankaj Prakash Patil, Atharva Dhananjay Kulkarni, Aakash Ajay Dhembare, Sarvesh Ramchandra Sankpal, Swaroop Vishwas Patil, Krishna Adar, Rahul Sonkamble

Abstract: Bird predation is a major problem in aquaculture. Nowadays bird Species is becoming rare, so we need to recognize them. Image recognition software can improve their efficiency in chasing birds. We proposed the System for Bird species Classification is a challenging problem due to the variation and different viewpoints of the camera. In the existing system, there are some disadvantages. We tried to overcome it by integrating the new feature into the multi-scale Convoluted Neural Network with Image Segmentation for Indian bird species classification, an algorithm is proposed to get the final classification result. Three recognition techniques were tested to identify birds i.e., image morphology, artificial neural networks, and template matching have been tested. We proposed a new feature that can improve the correct classification rate of the model as well as the accuracy of the model in the prediction of Birds classification. In this challenge, the bird image classification task, especially for Indian birds, is based on a limited but diverse set of crowd-sourced data. Especially, the present challenge involves a low amount of labelled data to build good classification approaches for effective classification. Up to now a lot of research has been done to identify bird species. Finally, we have proposed a methodology to improve accuracy in the identification of bird species.

Keywords: Data Augmentation, Dropout, TensorFlow, Keras, DT, CNN, Multiscale

Vol 6, No 2 (2021): Steering Angle Prediction Using Convolutional Neural Network

Authors:-Kumtale Aishwarya Bhausaheb , Rutuja Ramesh Madnaik , Navale Shruti Sudhir ,Dr. Muthusundar S.K.

Abstarct:-Most of the car accidents happen because of human errors while driving. Therefore, we think this is the serious real life problem and this needs to be solved. In this project, we focused on designing and implementing an efficient model using convolutional neural network for self-driving car module. Our project entirely focuses on predicting most accurate rotation angle for the cars based on the input image feed. The calculation supports both types of images taken on highway or on local roads. We implement the models for predicting steering angles on the Udacity dataset and visualize the results by using the dataset given by comma ai. For better performance, our system can run on the GPU using CUDA to process more and more frames to give accurate results quickly. CUDA enables increase in computing performance by harnessing power of GPU.

Keywords:-Machine Learning, Convolutional Neural Network, Steering Angle Prediction

Vol 6, No 2 (2021): Determining Peak and Machine Level Interest Utilizing Smart Meter Information

Authors:- J. Manikandan

Abstrcat:- The savvy network is a significant part of brilliant innovation. Savvy framework innovation empowers two-path correspondence between the energy purchaser and the energy merchant. Shrewd meters which are introduced at the shopper side goes about as the extension between the purchaser and the framework. Information investigation can be applied to the information gathered by the keen meter to estimate power utilization. The gauge will help the energy suppliers to oversee energy appropriation viably as the interest is known ahead of time. Apparatus level information investigation can foresee the utilization of power at the degree of machine utilization. With this forecast, clients can settle on the utilization of machines to oversee power utilization and henceforth diminish the bill. In this paper, an AI model utilizing the help vector machine is utilized to foresee shopper's power top interest use, and a half breed model including multi-facet perceptron with k-implies is worked to anticipate greatest power utilization at the apparatus level.

Keywords:-Smart meter, Machine level interest, Smart grid, MLP

Vol 6, No 2 (2021): Chatbot in Mental Healthcare

Authors: Vaishnobi Gogoi, Angel Silka, Swarnima Kahate, Dnyanda Akarte, Pratik Hepat

Abstract: To relieve mental tension, the greatest way is to talk about their feelings with someone they trust and unharness their inner agony. The greatest thing for someone who is depressed to do is to reach out and talk about it before acting on their feelings. Chatbots are unit special agents who answer to the user in the same language as a human would. Social chatbots, in particular, are those that develop a strong emotional bond with the user. The major goal of this chatbot was to provide emotional comfort to pupils who were under various levels of stress. Associate in nursing, which could be the beginning of a hostile depression. The text is distributed into feelings by an intelligent social therapy chatbot. Furthermore, it establishes the users' mental state, such as worried or depressed, by mistreating users' chat data, which is supported by the emotional label. Three popular deep learning classifiers will be used to detect feelings.  chatbot's planned methodology is domain specific, where the chatbot can strive to prevent bearish acts and reconstruct more constructive views through user engagement.

Vol 6, No 2 (2021): Grouping Controlling Routing Algorithm for Flooding in Delay Tolerant Network while Calculating the Energy

Authors: Ridhdhi Naik, Twinkle Ankleshwaria

Abstract: The Delay-Tolerant Networks (DTNs) are the type of emerging networks characterized by very long delay paths and frequent network partitions. For the distinct characteristics of DTNs, routing becoming one of the most challenging open source problems. Recently years numerous approach has been presented for addressing routing issues in DTNs. This paper mainly surveys DTN routing strategies and gives a comparison of them with respect to different performance metrics. In this especially, we summarize the cardinal mobility models and DTN simulators which are significantly important to evaluate the performance of the DTN routing protocols.

Vol 6, No 1 (2021): Smart Home Automation System for Internet of Everything

Authors:- Kashish Choudhary, Mahesh Shetty

Abstract:-With the rapid advancement of technology, people have become increasingly dependant on the internet. As a result, in order to stay up with the technological speed, everyone is eager to computerise their homes. With such rapid growth of variables like smart components like houses, hotels, smart urban areas, and smart things, the Internet of Everything (IOE) is a sphere of Grand impact, development, and promise. The Internet of Things (IOT) creates an environment in which everything is connected, digitalized, and intelligent. The majority of people rely significantly on their smartphones or laptops and wish to use them to carry out their daily tasks in an effective manner. Traditional or conventional houses are made up of a variety of electronic equipment that are managed or monitored by remote framework systems. As a result, using and controlling such discrete house portions becomes highly laborious. With the advancement of technology and innovation, computers now have access to virtually every aspect of the household. House Automation is an extension of IoT, in which IoT devices are used to provide smart functionality to specific home components. The suggested framework makes use of an Arduino Uno, which forms the foundation of the home robotization framework and can identify the number of occupants in the room using Passive Infrared (PIR) sensors and automatically turn the lights ON/OFF based on occupancy. It makes use of an ESP8266 module to connect Arduino to a Wi-Fi network and simplifies TCP/IP connections using Hayes commands. In addition, the system sends information to the ThingSpeak cloud for analysis. In the literature, several and diverse home automation systems with various findings and implementations have been presented. The goal is to offer a Node MCU and Thingspeak-based IOE-based technique for a productive home automation framework. The ThingSpeak cloud platform is used to coordinate the house segments, as well as to analyse and measure the data. In our suggested LAN communication system, MQTT is used. This article will provide IoT designers and specialists with a method for sensing, digitising, and controlling dwellings in the context of future IoT. Similarly, this project is demonstrating how IoT applications may make life easier.

Vol 6, No 1 (2021): Stock Market Analysis

Authors: Yadav Shubham Shivpratap, Yadav Rakhi Ramkripal, Prof. Rajesh Gaikwad

Abstract: Stock market prediction has always caught the attention of many analysts and researchers. Popular theories suggest that stock markets are essentially a random walk and it is a fool’s game to try and predict them as they have a number of variables involved. In the short term, they behave like a voting machine but in the long term, it acts like a weighing machine and hence there is scope for predicting the market movements for a longer timeframe.


In recent years, many companies have successfully used ml and various in house and other algorithms to predict market trends. In this project, we are applying various time-series algorithms like Arima, LSTM, etc to successfully make predictions for future stock market trends. We first analyze the data and find trends and relations between them and see if they are suitable for predictions. We have also made an suitable API to make use in any user interface available. For this project we will demonstrate our predictions using android or web interface. The algorithms used show promising results for analyzing different time-series data.

Vol 6, No 1 (2021): Analysis of Student Attentiveness Using Machine Learning

Authors: Anita Mishra, Chaitali Londhe, Nikita Mandlik, Nikita Dambhare, Prof. Harshwardhan Kharpate

Abstract: Educational data has become an important resource in this modern era. Our approach is based on applying the machine learning algorithm to analyze the student data that can help understand the student learning process. In this work, we are trying to analyze the students according to a few important factors. By analyzing this data, we can get an all-rounded view. A different experiment was done while the collection of data to help us understand the process. After gathering the data, we applied the Logistic Regression algorithm on the data to get the output as the analysis and understanding of the student is attentive or non-attentive. The dataset is composed of factors like exam scores, extracurricular activities, projects, etc. This will help the institute get a personalized and effective report about the attentiveness and efficiency of a student so that required measures can be taken into that consideration to improve the performance of the students.

Vol 6, No 1 (2021): Experimental Facts about Face Emotion Recognition System

Author: Md Rakibul Hasan

Abstract: Technological know-how and generation have advanced so properly that artificial intelligence (AI) is no longer a term in technological know-how fiction. The standard definition of artificial intelligence is the capability of a system to "assume or act humanly or rationally (intelligence confirmed by machines, rather than natural intelligence proven by humans and animals)." Machines are actually capable of the procedure the sizable facts of quantity in actual-time and consequently reply. But, those enormously clever machines were usually missing Emotional Intelligence (EI). As generation progresses and the world turns into extra digital, there's a worry that we are able to lose human connection to come to be verbal exchange; but what if our gadgets could update those interactions? Developers and researchers had been advancing AI to not only create structures that suppose and act like people, however, additionally discover and react to human feelings. Humans show frequent consistency in recognizing feelings; however, they also show a notable deal of variability among individuals of their capabilities. Allowing the gadgets around us to understand our feelings can simplest decorate our interaction with machines, as well as the various family of humanity. The point of this research is to expand customized person studies that can assist improve lives.

Vol 6, No 1 (2021): A Comprehensive Survey on Study of Big data and its Challenges

Author: Md. Rakibul Hasan

Abstract: With the advent of the Internet of Things (IoT) and Web 5.0 technologies, there has been a huge repository of terabytes (TB) of data is generated each day. Analysis of these massive data requires a lot of effort at multiple levels to extract knowledge for decision making. Therefore, big data analysis is a current area of research and development. This article emphasizes the need for big data, technological advancements, and various tools associated with it, and techniques being used to process big data are discussed. This article provides a platform to explore big data at numerous stages and it opens a new horizon for researchers to develop the solution based on the challenges and open research issues.


Vol 5, No 3 (2020): Development of an Electric Vehicle (EV) Powered by Solar Energy

Authors: Al Mahmud Al Mamun, Md. Enamul Kabir, Mst. Mahfuza Sharmin, Md. Ashik Iqbal, A.B.M. Ashikur Rahman, Abul Bas Rr

Abstract: The conventional fuel run vehicle is the biggest reason for the hazardous particles emitted in our modern world. For that we are trying to shift into a renewable source of energy for running the vehicles. Fuel cell electric vehicles, hybrid electric vehicles, and electric vehicles are some of the alternatives. An electric vehicle (EV) develops with one or more electric motors for running and powered by an electrical energy source. This paper represents the usage of a solar energy system to power up the electric vehicle. Solar energy is the energy from radiant light and heat of the Sun converted to electric energy. Electric vehicles are not a new concept the first time introduced within the middle of the 19th century. In this project, a fast and power-efficient charger has been designed for a BLDC motor-driven electric vehicle where a dc battery is a feed by both conventional power source as MES and PV cells as RES. The feature components are - charge controller, rechargeable battery, power converter system, solar panel system, and Brushless DC Motor, and the circuits designed severally applying PSIM software. In this paper, we mainly focus on two things, shift into a renewable source of energy for the vehicle, and usage of solar energy to power up the electric vehicle.


Vol 5, No 3 (2020): Development of Guideway for the Electromagnetic Vehicles

Authors:-Al Mahmud Al Mamun, Md. Kamrul Hassan, Mst. Mahfuza Sharmin, Md. Shaleh Palvy, Md. Enamul Kabir, Md. Ashik Iqbal

Abstract:-The magnetic vehicle will move objects at precise distances while not in contact between surfaces and while not friction that reduces vibration. These forms of vehicles will be used in harsh environments, wherever ancient vehicles may not survive. This technology has two active elements; one is that the vehicle or moving the body and another is the guide-way for the vehicle. The main advantage is that those two-parts don't bite one another, as magnetism implies here. To determine this, conditioned power is required to energize the vehicle and guide-way. Magnetism could be a development, happens once a moving charge exerts a force on different moving charges, the magnetic-force created by these moving charges. With the advanced materials, low-cost, high-speed computing systems make it possible to build levitation as a commonplace and integral part of our life. In this project, we are going to focus on developing a Guide-way mistreatment Microcontroller. To control electronically, the levitation magnets are put in on either side with the full vehicle that keeps it on the required vertical distance over magnetic-attractive-forces, and also the steering magnets keep It supports the vehicles suspended on the guide-way while not in contact. The driving element is put in on the Guide-way of stator coil packs. The main reason for this project is to know the dynamic characteristics of the Guide-way and to develop a sturdy numerical methodology for simulating the coupled system. 

Vol 5, No 3 (2020): A Secure Multi Cloud Data Sharing for Supporting Inter- Organizational Aspects

Authors:-Dr. F. Leo John 

Abstract:-Secure sharing of data in multi-Cloud storage is not an easy task for Cloud service providers. Many Cloud services provide generic or data specific Cloud storage (e.g., Google Picasa or sound Cloud). However, both Cloud storage types have data storage in common. In the existing scheme, the architecture features attribute-based encryption for selective access authorization and cryptographic secret sharing in order to disperse data across multiple Clouds and, the security of key distribution is based on the secure communication Cloud provider, however, to have such a Cloud provider is a strong assumption and is difficult for data sharing. We tried to propose a novel architecture for the multi-Cloud provider by describing a key aggregate crypto system scheme that produces a constant size aggregate key for flexible choices of cipher text set in Cloud storage, but the other encrypted files outside the set remain confidential. This scheme provides a secure and easy way of data sharing in multi-Cloud storage within an organization authorities as well as non-organizational users.


Vol 5, No 3 (2020): Proposed Methodology for Scientific Automatic Text Summarization Using K-Means

Authors: Nitesh Pandey, Nidhi Singh

Abstract: A method is proposed for automatic text summarization by extractive method which further goes with the utilization of sentence embedding where we bring together the relatable Text together and creates sentence and further use k-mean clustering to find out the relatable words we need accordance with our centroid where summary size also comes as a factor, Text which are embedded together contains similar information but most appropriate one which comes under text selection as we select the suited one to be added in summary, ridge regression pushes the estimated coefficient towards zero so that most relevant words would be added to the sentences; therefore the relevancy of different embedded Text which is turned to sentences now can be checked by ROGUE-2 score which contain dataset of DUC-2001 and can also be checked while having a summary of different length as an outcome, this also shows the effectiveness of the approach we used.

Vol 5, No 3 (2020): Optimal Assignment of Inventory Items to Drones

Author: Vedant Atmaram Sakhardande

Abstract: An optimal assignment of inventory items to Drones is something which is of utmost importance. As we go into the future considering the current market, most of the deliveries would happen with drones' help and each of the delivery would be in different sectors. An autonomous system is going to be used in every sector. Drones are the very costly and optimal use of drones is very important so that more deliveries and more items can be delivered with the least number of drones. Optimal assignment of inventory items to drones can be used for all applications wherein there should be the assignment of items in the most effective way such that it occupies the least space.

Vol 5, No 2 (2020): Random Forest and ARIMA model for Crime Prediction and Analysis

Authors: Anushka Sancheti, Shambhavi Shete, Pranati Thakare, Saloni Goya, Sandhya Arora

Abstract: Crime is one of the biggest and dominating problems of our society and the whole world is struggling to fight against crime. The police department, cyber cell and other crime control agencies face problems in surveillance action for crime prevention. Processing, capturing and analyzing security-related data is increasingly difficult. That's why much of the scattered crime data is not being used. In this work, the technique of machine learning and data science for crime prediction is used and for testing the Toronto crime data set is used. The crime data is extracted from the official portal of Toronto police. Data preprocessing, data modelling is done and many machine learning algorithms are applied for crime prediction. The random forest algorithm and ARIMA model worked on crime data with good accuracy. Results are analyzed and visualized in terms of graphical representation of many cases, for example, at which time the crime rates are high or at which month, area and location the criminal activities are high. The sole purpose of this work is to explain how machine learning can be used by law enforcement agencies to detect, predict, and solve crimes faster and thus reduce the crime rate.

Vol 5, No 2 (2020): Air Pollution Analysis using Linear Regression

Authors: Dr.R.V.S.Lalitha, Dr.K.Kavitha, M.Sai Kiran, D.La Selene, M.Pratyusha

Abstract: Pollution occurs due to the undesirable presence of pollutants such as CO2, NO2 and other gases that make the environment unhealthy. Pollutants cause imbalance and damage to air either directly or indirectly by making it dirty. Air pollution is a pressing concern as it causes harm to human beings, animals and plants. In this paper, the impact of pollution caused due to the mixing of one gas with the other and the quantum of air pollutants present in the air is measured using linear regression analysis. The correlation among pollutants is analyzed to observe the impact of one gas with the other. This analysis gives information about the level of pollutants in the air.

Vol 5, No 2 (2020): Crop Prognosis in Machine Learning Using Multi Linear Regression Algorithm

Authors: Gondi Yasoda Devi, S. Sairam, S. Kalyani Utpala

Abstract: In India, agriculture is largely influenced by rainwater, which is highly unpredictable. Agriculture growth also depends on diverse soil parameters, namely Nitrogen, Phosphorus, Potassium, Crop rotation, Soil moisture, pH, surface temperature and weather aspects like temperature, rainfall, etc. The technology will be beneficial to agriculture, which will increase crop productivity resulting in better yields to the farmer. The project provides a solution for Smart Agriculture by monitoring the agricultural field, which can help the farmers increase productivity to a great extent. This work presents a system that uses Machine learning techniques to predict the most profitable crop in the current weather and soil conditions. A prediction of the most suitable crops according to current environmental conditions is made. This provides a farmer with a variety of options for crops that can be cultivated. Thus, the project develops a system by integrating data from various sources, data analytics, and prediction analysis, which can improve crop yield productivity and increase farmers' profit margins over a longer run.


Vol 5, No 2 (2020): Internet of Things

Authors:-Mrunal Rajesh Omanna, Aditi Avinash Magdum, Prashant.B.Patil

Abstract:-IoT i.e. Internet of Things is now fast becoming a disruptive technology in business opportunity, with the  standards in emerging primarily for wireless communication between sensors, actuators and gadgets in today’s  human  being life, which is all generally referred to as nothing but  the “Things”. This technology has capability of measures and understands the indicators of environment. As the main enabling factor of promising paradigm for integration and comprehensive of several technologies for communication solution, Identification and integrating for tracking of technologies as wireless sensor and actuators this paper addresses the internet of things (IoT). IoT is the network of all this above mentioned things embedded with electronics, software, sensors, and many more, which allows to enables these things to collect and exchange data. Internet of Things (IoT) is billions of sensors connected to the internet via the sensors which will be generate a large amount of data that need to properly collected, analyzed, interpreted and utilized. It is context aware capturing enables modeling, interpreting and storing of sensors collected  data which will be  linked to dynamically to appropriate context variable. IoT has given all of us a promising and a better way to build up a powerful and innovative industrial systems and applications with the help of wireless devices, Android, and sensors etc. Buildings or home automation, social smart communication, business applications, security for enhancement of better and quality of life, which  could be considered as the application of  internet of things (IoT),where the sensors, actuator, gadgets and controllers can be connected to internet and  it will be properly controlled. This paper introduces or addresses the concept of application for IoT i.e. internet of things.

Vol 5, No 2 (2020): A Review Paper on Wi-Vi Technology

Authors:-P. B. Patil,  Aditi. A. Magdum

Abstract:-Technology is making very fast progress and is making many things too much easier and simple. Out of wireless networking methods which have been evolved, my current topic is Wi-Vi. Wi-Fi is the most accepted and popular technology. Wi-Fi is a wireless networking technology which facilitates to connect computers, Smartphone’s, laptops and other devices to internet or communicate with each other through wireless network. Wi-Fi has no any physical medium for transmission, although it uses radio frequency waves for transmission. Similarly, Wi-Vi i.e. Wireless Vision is a newest technology having the same concept of Wi-Fi with additional feature that it enables us to seeing through walls and behind the closed doors by using Wi-Fi signals. By using Wi-Vi we can get identification of objects in closed rooms and their locations. With the help of Wi-Fi signals and MIMO communication Wi-Vi device can get the human motion beyond the walls, doors or closed rooms.

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