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DJ ASCII-17

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Preface

We are pleased to present the proceedings of the State Level Project Competition DJ ASCII.

The competition was organized by department of Computer Engineering and Information Technology

of SVKM’s Dwarkadas J. Sanghvi College of Engineering on 1st April, 2017 in Mumbai, India.

The main aim of DJ ASCII was to provide a platform for budding engineering students and

researchers from all over Maharashtra to share and demonstrate their innovative ideas in the field of

latest technology.

We are very happy to say that DJ ASCII has achieved what it had aimed for by receiving an

overwhelming response of total 124 participations, out of which 73 were selected after a rigorous

review by our panel of expert reviewers. 61 project groups registered for the competition.

The competition received projects primarily in the domains, which were not limited to,

Artificial Intelligence, Computing, Human Computer Interactions, Data Mining and Analytics and

Network & Security. The projects were presented and demonstrated by students from various

engineering institutes in parallel sessions. Students also had presented their project ideas with

technical paper and abstract of those papers are published with ISSN number.

We thank our patrons Shri. Amrish R. Patel (President, SVKM), Shri. Bhupesh R. Patel (Join

president, SVKM), Shri. Pravin V. Gandhi (Vice President, SVKM), Shri. Sunandan R. Divatia (Hon.

Secretary, SVKM), Shri. Jayant P. Gandhi (Hon. Joint Secretary, SVKM), Shri. Shalin S. Divatia

(Hon. Joint Secretary, SVKM), Shri. Utpal H. Bhayani (Hon. Treasurer, SVKM), Shri. Harshad H.

Shah (Hon. Joint treasurer, SVKM), Shri. Harit H. Chitalia (Hon. Joint Treasurer, SVKM) and Shri.

Bharat M. Sanghvi (In-charge, DJSCE) for their valuable guidance and support. We are extremely

grateful to our Management SVKM for their wholehearted support in organizing DJ ASCII.

We thank the advisory committee for their guidance and inputs throughout the organization

of the competition. The review committee was very helpful in providing timely and constructive

reviews of the papers. We would also like to thank all the students, who participated and showed

active interest throughout the competition.

Finally, we thank our fellow members of Technical and Organizing Committee and our

student volunteers for the smooth conduct of the competition. Their sincere efforts and contribution

have certainly made a huge impact on the success of this event.

We hope you will have a wonderful experience going through the proceedings.

Thank you very much.

Warm regards and good wishes!

Dr. A. R. Joshi Dr. Hari Vasudevan

Dr. N.M. Shekokar Convenor, DJ ASCII

Co-convenor, DJ ASCII

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Committee

Convener

Dr. Hari Vasudevan

Principal

Co-Conveners

Dr. A. R. Joshi

Vice-Principal (Acad.) & Head, Department of Information Technology

Dr. N. M. Shekokar

Head, Department of Computer Engineering

Advisory Committee

Dr. A. C. Daptardar

Vice-Principal (Admin.)

Dr. Manali J. Godse

Professor and Head, Department of Biomedical Engineering

Dr. V. Ramesh

Professor and Head, Department of Chemical Engineering

Dr. A. A. Deshmukh

Professor and Head, department of Electronics and Telecommunication Engineering

Dr. K. N. Vijay Kumar

Professor and Head, Department of Mechanical Engineering

Prof P. S. Joshi

Head, department of Electronics

Prof. R. S. Khavekar

Training and Placement Officer

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Technical and Organizing Committee

Project Reviewers’ Committee

Mr. Nimish Somaiya

Dr. Amiya Tripathi

Ms. Rajashri Rajadhakshya

Mr. Sachin Kadam

Dr. Meera Narvekar Dr. Jyoti Joglekar Dr. Ram Mangrulkar

Prof. Neepa K. Shah Prof. Vinaya N. Sawant Prof. Aruna U. Gawade

Prof. Kiran Bhoumick Prof. Harish G. Narula Prof. Kriti Srivastava

Prof. Purva P. Raut Prof. Khushali P. Deulkar Prof. Neha A. Katre

Prof. Lakshmi D. Kurup Prof. Harshal D. Dalvi Prof. Ashok P. Patade

Prof. Arjun K. Jaiswal Prof. Chetashri S. Bhadane Prof. Ruhina B. Karani

Prof. Anusha Vegesna Prof. Pranjali S. Thakre Prof. Sindhu S. nir

Prof. Abhijit Patil Prof. Stevina Correia Prof. Mitchell R. D’silva

Prof. Lynette R. D’mello Prof. Pranit Bari Prof. Deepika Dongre

Prof. Sudhir Bagul Prof. Pankaj Sonawane Prof. Pratik Kanani

Prof. Ameyaa Biwalkar Prof. Priya Lande Prof. Nancy Nadar

Prof. Chirag Desai Prof. Jennifer Selvaraj Prof. Dinesh Tharwani

Prof. Suchita Rane Prof. Amruta patil

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Contents

Preface

Committees

1. AEGIS (An Efficient Generic Intelligent System) 1

Harsh Maheshwari, Bansari Kothari, Hardik Jain, Prof. Sindhu Nair

2. Probability of Plant’s Water Requirement 1

Krusha Doshi, Meghna Jai, Twinkle Pandya, Prof. Harish Narula

3. A Retrieval Based Neural Conversational Model 2

Chirag Jain, Monik Pamecha

and Prof. Kiran Bhowmick

4. Classification of Accents of English Speakers 2

Kejal Jhaveri, Bhavin Baxi, Karan Nisar, Dr. Prof. Meera Narvekar

5. Object Recognition in an Image Machine Learning 3

Bhavya Shah, Akash Shah, Bhaveen Patel

6. Playing Atari Games using Deep Reinforcement Learning 3

Bansi Shah, Drashti Turakhia

7. Analyzing Behavioral Attributes of Drivers and Implementing

Safe Driving Model 4 Vaibhav Dave, Aditya B., Yash Panchamia

8. Enhanced Sentiment Analysis of Twitter Data 4

Akash Parekh, Sagar Parekh, Kinjal Sanghavi

9. Anaphora Resolution in English Text 5

Malabika Sen, Neeti Shah, Prof. Lakshmi Kurup

10. Solving Medicine Delivery Problems using Blockchain with IoT 5

Fatema Olia, Ilina Gupta, Rachel Menezes, Prof. Aruna Gawade

11. Segregation of Plastics and Metals from Waste Sample 6

Raj Sadaye, Venkatesh Wagh, Yash Vora

12. WALKMATE- A Navigation and Obstacle Detection Aid for the Blind 6 Shivani Bhat, L. Sowmyasree, Chirag Dixit, Harishkandan Somasundaram

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13. Standalone Device for Home Automation and

Personalized Recommendation 7

Sameer Korlahalli, Harsh Parmar, Akshay More, Prof. Pranjali Thakre

14. A Synopsis Of Analytics for a Search Engine

DOMAIN: Artificial Intelligence - Natural Language Processing 7

Aishwarya Sadasivan, Komal Dhuri, Manaswini Muralidaran, Meghna Mohan

15. Providing Personalized Study Material for

Learning Disability using Machine Learning 8

Mohit Shah, Meet Shah

Ameya Shirke, Prof. Khushali Deulkar (Assistant Professor)

16. Document Classification Using NLP 9

Payal Jain, Divya Panchal, Abhishek Pandey

17. Intelligent Travel Bot using Machine Learning 9

Danish Ali Furniturewala, Sagar Raulo, Siddhant Rele

18. Categorization of Wheat

Domain: Artificial Intelligence (Neural Networks) 10

Prachi Patel, Aditya Ramnathkar, Hetashavi Shah, Prof. Purva Raut

19. Automatic Question Generation for E-learning Systems 10

Riken Shah, Deesha Shah, Prof. Lakshmi Kurup

20. Interview Bolt

Domain: Artificial Intelligence (Natural Language Processing,

Intelligent System), Human Computer Interaction 11

Vikash Salvi, Adnan Vasanwalla, Niriksha Aute

21. Personality Identification using Social Media and its Applications 11

Ria Echhpal, Najeeb Qazi, Rohil Shah

22. Sarcasmometer

Measuring sarcasm using sentiment analysis and topic modeling 12

Namrata Bhan, Janki Joshi, Kena Mehta and Prof. Mitchell D’silva

23. Object Recognition and Classification by Image Data Analysis

Using Machine Learning algorithm 13

Siddhi Thakkar, Sanket Shah, Niyati Shah and Raj Mehta

24. Street Lighting Intensity Controller Using

Density Mapping Mechanism 13

Rajas Walvalkar, Yogesh Yadav, Abhishek Yedurkar, Sagar Suchak, Swapnil Gharat

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25. Video Annotation for Active E-Learning 14

Sneha Baviskar, Shamli Dangare, Shruti Gaikwad, Shradhha Gosavi

26. Design and Fabrication of Prototype for Automatic

Car Parking System using RFID tagging for Modern Cities (ACPS) 14

Saloji Mohammed, Shaikh Alif, Singh Sudhirkumar, NabanitaNath Chowdhury

27. Treal: Virtual Trial Room using Virtual Reality 15

Rajat Rao, Jinesh Shah, Mayur Chawada

28. Smart Cloud Phone

Domain: Cloud Computing 15

Karan A. Shah, Jinay Mehta, Omkar V. Sawant, Prof. Lakshmi Kurup

29. Consumer Credit Default Predictor 16

Yash Poddar, Sanat Shah, Anmol Sheth, Prof. Chetashri Bhadane

30. Dipriori 16

Yadynesh Desai, Mrunal Medhekar, Disha Mehta, Prof. Vinaya Sawant

31. Smart Question Paper Generator 17

Jagruti Malani, Shreya Managute, Khushboo Jain, Prof. Khushali Deulkar

32. Drought Prediction and Management System

Using Big Data Analytics 17

Benita Jeyakumar, Vinita Rane, Himani Shah, Jayesh Nainani, Nupur Giri

33. Prediction and Optimization of Products for Online Sales 18

Shweta Sohani, Neel Shah, Aneri Shah

34. Teacher Guardian Log System 18

Abhishek Tiwari

35. Duplication Avoidance in Big Data 19

Pravina Vyawahare, Bhavin Bhoi, Pratik Avhad

36. Weather Prediction Model: A Data Mining Approach 19

Sudhir Kuwar, Pratiksha Gudme, Manali Band

37. Web based Code Testing and Monitoring Engine 20

Adit Shinde, Sushilkumar Takkekar, Ratnesh Dubey

38. Graduate Application Evaluation

Using Machine Learning 21

Varun Kasbekar, Hiral Rayani, Ami Sangani, Prof. Neepa Shah

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39. Hybrid Approach to Distributed Document Clustering 22

Varun Kasbekar, Hiral Rayani, Ami Sangani, Prof. Neepa Shah

40. Agro Analytics: Drought Prediction and

Suggestions for Optimal Agricultural Practices 22

Manan Shah, Mihin Sumaria, Mohit Shah

41. Portable Book Reader for Visually Impaired 23

Nishi Jain, Mandar Kanade, Harsh R Mehta, Prof. Khushali Deulkar

42. VidMute

Silence Those Annoying Loud Ads 23

Rushabh Dharia, Chirag Jain

43. Multiple Object Tracking & Monitoring 24

Shreya Redekar, Nishita Sheth, Nisha Shah, Prof. Khushali Deulkar

44. MonVoix – an Android Application for

Acoustically Challenged People 24

Aishwarya Danoji, Aishwarya Dhage, Rachana Kamat,

Priya Puranik , Prof Sharmila Sengupta

45. Interpretation of Music Scoresheet to Generate Audio File 25

Bhakti Raichura, Karan Shah, Ronak Thakkar

46. Structured Light 3D Scanner

(Point Cloud Generation using Triangulation) 25

Kushal Vyas, Prof. Ruhina Karani

47. Prevention Of Accidents While Drunken Driving 26

Kevin Maru, Prathamesh Dongre, Purvi Udhwani, Neha Mundra

48. Virtual Try-On Of Clothes 26

Aashni Savani, Raj Vastani, Harshal Vora, Prof. Ruhina Karani

49. Baby Mentor: Learning through Images 27

Jeremy Samuel, Sanket Solanki, Saurabh Patil, Prof. Ruhina Karani

50. 3D Facial Reconstruction Using Skull of a Deceased Person 27

Priya Singh, Lilavati Swamy, Aishwarya Tate, Anam Shah

51. Measuring Length of an Infant from Its Image using Reference

Object and Monitoring Growth 28

Dimpi Dedhia, Nidhi Patel, Kavita Soni, Prof. Stevina Correia,

Prof. Pratik Kanani

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52. Interactive Learning using Augmented Reality Books 28

Aayushi Vora, Soham Mehta, Pratish Jain

53. Reflective Intelligence-an Odroid Based Approach 29

Priti Nalawade, Shraddha Upadhyay, Navin Das, Vijal Jain

54. Novel Encryption Technique to Secure Document Data Store 29

Elita Dsouza, Dimpal Jayani, Anuja Patil, Prof. Pratik Kanani,

Prof. Kriti Srivastava

55. Prevention of Parallel Active Dictionary Attack on

WPA2-PSK Wi-Fi Networks 30

Drishti Kakar, Nagendra Kamath, Aneek Guha, Dr. Prof. N. M. Shekokar

56. Design and Overview of a Navigation Application for the Blind 31

Sanjana Panicker, Maitreyi KV, Merrill Gonsalves, Kane Gonsalves, Sandhya Patil

57. Enhancement of Security Using

Three Level Graphical Authentication 31

Prashant Chiplunkar, Tejal Patil, Sunil Dewoolkar

58. Smart Network for Fire Control 32

Heena Tailor, Kashmeera Sawant, Niel Vaishya, Shivani Sherekar

59. Puppet Attack and Its Detection 32

Manasi Deshmukh, Jash Nichani, Komal Mehta, Prof.Aruna Gawde

60. Intelligent Ambulance Fleet Management System 33

Monica Chhabria, Latika Wadhwa, Shruti Dhumale, Omkar Patinge

61. An Access Control Model for an E-Commerce

Business Model using Mongo-DB 33

Khushali Shah, Priyal Shah, Kriti Srivastava

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PAPER ID: AI02

AEGIS

(An Efficient Generic Intelligent System) Harsh Maheshwari1, Bansari Kothari2, Hardik Jain3, Prof. Mrs. Sindhu Nair4

1,2,3,4Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India.

E-mail: [email protected], [email protected], [email protected]

AEGIS is an intelligent system that will interactively 1) solve the users query 2) search a piece of

information and 3) summarize the most significant information from it. AEGIS has two main

components Scrapper and Summarizer. The main concern of extracting information from the web is

its structure, thus there is a need for semantic or a systematic way to retrieve and represent relevant

data. For finding meaningful information from the discovery patterns in the server web mining is a

crucial tool. Web scraping is another method for processing of extracted useful information from

HTML pages. It is usually implemented by using a scripting language. The extracted information will

then be checked for relevancy. For a text based single document summarization is done on the basis

of important information within the document and not generative summarized information. AEGIS

will help the user to interact with the PC through voice; also the user will be able to manipulate some

hardware settings using voice.

PAPER ID: AI05

Probability of Plant’s Water Requirement

Krusha Doshi1, Meghna Jai 2, Twinkle Pandya3, Prof. Harish Narula4 1,2,3,4Department of Computer Engineering



There have been times of acute drought in various regions where agriculture and farming are the main

occupations. However, amount of water efficiently used is still questionable. The farmers agree that

the plants do not need to be watered on a daily basis. Once in two-three days is the average frequency.

However, the exact amount of time required before watering again cannot be properly judged. They

need to look for subtle cues and estimate the amount of water required by the plant at that particular

stage. This can be fairly inaccurate and can lead to tremendous wastage of water and/or soil erosion.

Our main aim is to identify when the plant would require water. This would help novice farmers to

make a better estimate and use water judiciously by studying behavioral pattern of the plant to various

stimuli such as external temperature, humidity, luminosity, etc. to determine when the plant would

need water.

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PAPER ID: AI06

A Retrieval Based Neural Conversational Model

Chirag Jain1, Monik Pamecha2, Prof. Kiran Bhowmick3 1,2,3Department of Computer Engineering


Haptik Infotech Pvt. Ltd., Mumbai, India.


In this paper we present an end-to-end retrieval based neural conversational model. Our model

replaces the existing rule based approaches used in building conversational bots. We train our network

on a large corpus of conversation between users of a personal assistant application and trained agents.

Using semantic information from word clusters, we train the conversational model to predict the best

match responses from automated cluster messages of responses that have been manually refined.

PAPER ID: AI08

Classification of Accents of English Speakers

Kejal Jhaveri1, Bhavin Baxi2, Karan Nisar3, Dr. Meera Narvekar4

Department of Computer Engineering

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India

E-mail: [email protected], [email protected], [email protected], [email protected]

One of the most significant topics in automatic speaker and speaker-independent speech recognition

systems in recent years is Accent recognition. The growth of voice-controlled technologies has

become part of our day to day life, nevertheless variability in speech makes these spoken language

technologies relatively difficult. One of the profound variability is accent. By classifying accent types,

different models could be developed to handle SI-ASR. Accents can also reveal a lot about a person’s

background, such as their native language, place of origin, or ethnic background. Speaker identity

verification is also a useful biometric recognition approach. Being able to recognize different type of

accents can also improve the quality of speech to text transcription by allowing for specific pre-

processing of recordings based on the type of accent. Our goal is to classify various types of accents,

specifically foreign accents, according to the native language of the speaker. When a recording of a

speaker speaking a known script of English words is given, we would like to predict the speaker’s

native language.

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PAPER ID: AI09

Object Recognition in an Image

Bhavya Shah1, Akash Shah2, Bhaveen Patel3

1,2,3Department of Information Technology

D. J. Sanghvi College of Engineering, Mumbai, India.


The purpose of this project is to build an image classification system that can accurately classify

images. For the classification of images, we are using Cifar-10 dataset is a benchmark dataset in

image recognition. Particularly we investigated KNN, SVM and CNN of which CNN yields the best

result.

PAPER ID: AI10

Playing Atari Games Using Deep Reinforcement

Learning Bansi Shah1, Drashti Turakhia2

1,2Department of Computer Engineering


Email: [email protected]

Teaching computers to play video games is a complex learning problem that has recently seen

increased attention. The project aims to replicate a system that combines deep learning methods and

reinforcement learning in order to create a system that is able to learn how to play Atari games on its

own. A model free reinforcement methodology named ‘Q-Learning’ is used. Therefore the core

algorithm of Deep Reinforcement Learning used is ‘DQN’. DQN incorporated several key features

that enabled the power of Deep Neural Networks (DNN) to be combined in a scalable fashion with

Reinforcement Learning (RL)—a machine learning framework that prescribes how agents should act

in an environment in order to maximize future cumulative reward (e.g., a game score). Foremost

among these was a neurobiologically inspired mechanism, termed ‘experience replay’, whereby

during the learning phase DQN was trained on samples drawn from a pool of stored episodes. This

work offers the demonstration of a general purpose learning agent that can be trained end-to-end to

handle a wide variety of challenging tasks, taking in only raw pixels as inputs and transforming these

into actions that can be executed in real-time. The system has access only to the visual information

i.e. the screen of the game and the scores. Based on these two inputs the system learns to understand

which moves are good and which are bad depending on the situation on the screen. The system can

be implemented to master several different games and play some of them better than a human player.

This result can be seen as a step towards truly intelligent machines and thus it fascinates us. The future

goal is to continue to improve the capabilities of these agents to give researchers new ways to make

sense of complex large-scale data creating the potential for exciting discoveries.

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PAPER ID: AI15

Analyzing Behavioral Attributes of Drivers and

Implementing Safe Driving Model

Vaibhav Dave1, Aditya B.2, Yash Panchamia3




We have created an embedded system to get the live data stream from the car. The data will highlight

the following parameters: (1) Speed of the driver, (2) Proximity with other cars during driving, (3)

Turning radius, (4) Acceleration and deceleration values. These parameters are critical to judge the

driver for his/ her driving skills and if he/she crosses the permitted limit can be warned or punished

for violating the basic rules and regulation of the driving. We propose a solution wherein Hidden

Markov Models (HMM) are used to categorize and rate a driver's performance based on these

parameters. This will help the driver understand and improve his driving technique and will prompt

drivers to be more vigilant. Additionally, the solution can be used to detect accidents and collisions

by observing the changes in the values of speed and the overall orientation of the vehicle and can then

alert nearby authorities to send emergency assistance

PAPER ID: AI16

Enhanced Sentiment Analysis of Twitter Data

Akash Parekh1, Sagar Parekh2 and Kinjal Sanghavi3

Fr.Agnel Technical Education, Vashi, Navi Mumbai, India. [email protected]

The advent of the internet and social networking sites such as Facebook, Twitter and Tumblr, has

brought a new way of expressing the sentiments of individuals. Global sentiment is a powerful

weapon that can be harnessed by the use of Sentiment Analysis techniques. Knowing how the general

populace perceives a product or an idea is crucial to the survival of any business. This paper

contributes to the sentiment analysis for customers’ review classification which is helpful to analyze

the information in the form of the number of tweets where opinions are highly unstructured and are

classified into different sentiment classes. This paper aims to perform sentiment analysis beyond the

traditional approach of using keywords to determine sentiment polarity and inculcate new techniques

for enhancing the accuracy of sentiment analysis like use of emoticons, emotional vectors, popularity

of sentence using retweets.

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PAPER ID: AI18

Anaphora Resolution in English Text

Malabika Sen1, Neeti Shah2, Lakshmi Kurup3

UG student, Assistant Professor, 1,2,3 4Department of Computer Engineering



Chat bots and other interactive applications are not only very trending but also have other important

implementations in most of the fields of Natural Language (NLP). Information Extraction from a text,

Machine Translation and text summarizations are very complex problems. The system first needs to

understand the context in most of these cases. Just like one would wonder what ‘these’ meant by in

the previous sentence, many such references are used in everyday language that might cause few

words to refer to some other word or phrase. It is easy for humans to interpret what they mean or

whom they refer to. But it is not the same case with computers. This problem is known as Anaphora

Resolution. We hereby present the proposed methodology in order to solve this problem for an

ambiguous language of English.

PAPER ID: AI20

Solving Medicine Delivery Problems using Blockchain

with IoT

Fatema Olia1, Ilina Gupta2, Rachel Menezes3, Prof. Aruna Gawade4 1,2,3,4Department of Computer Engineering

Dwarkadas J. Sanghvi College of Engineering,Mumbai, India.

Email: [email protected],4 [email protected]

This paper describes a safe alternative for monitoring the medicine delivery supply chain. It combines

IoT with blockchain networks to ensure secure transfer of medicines from manufacturers up to the

medicine distributes (e.g.: chemists). It utilises the decentralised nature of the blockchain to make

sure the data generated cannot be tampered or deleted. It employs a ‘trust-less’ distributed network

instead of the existing ‘trust-based’ systems that rely on a central authority to store and validate the

data.

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PAPER ID: AI22

Segregation of Plastics and Metals from Waste Sample

Raj Sadaye1, Venkatesh Wagh2, Yash Vora3 1,2,3Department of Computer Engineering


Email: [email protected], [email protected], [email protected]

Waste Disposal has always been a problem in India. By separating wastes into different types we can

reuse or recycle some of the waste contents. This project aims at providing an efficacious solution to

the problem of segregation of waste. The separation of waste is done based on the output received

through various sensors. The proposed system will separate waste into 3 categories Metallic (Re-

usable), Plastics and Glass (Recyclable) and other (Passed through without identification) types of

waste. Infra-Red sensors can be used to detect the presence of an object within the system.

Transparent materials will pass-through this type of light. Inductive sensors can used to detect metallic

objects within the waste. Capacitive sensors can be used to detect opaque plastics as well as glass.

The system will have a single outlet for dropping the objects. A motor control logic is implemented

using the outputs of the sensors the combination of rotation of two motors can be used to separate the

waste into different containers. Bipolar stepper motor has been used to implement the separation part.

Thus it is a low-cost solution for waste disposal problem.

PAPER ID: AI23

WALKMATE- A Navigation and Obstacle Detection Aid

for the Blind Shivani Bhat1, L. Sowmyasree2, Chirag Dixit3, Harishkandan Somasundaram4

1,2,3,4Department of Computer Engineering

Vivekanand Education Society's Institute of Technology, Chembur, Mumbai.


In an ever growing fast paced world, a disability can be a major setback in a person’s path of progress.

Blindness in particular turns even the most rudimentary day to day tasks difficult. While the existing

practice of using the white cane or walking stick is commonplace for detection of obstacles/objects

in front of the user, it does not offer any aid in navigation through unknown or new places. On the

other hand, devices which aid the visually impaired to navigate do not offer any aid to detect obstacles

on the way. Newer technologies available offer a solution to either of the two problems-obstacle

detection or navigation- at a high cost that not many could afford. The paper proposes a design for a

device which will help them overcome two basic problems visually challenged people face, viz.

navigation and obstacle avoidance. The device is a pair of wristbands that when worn on the wrist

helps the visually impaired to navigate to the destination through different tactile stimuli. The

proposed device is an IoT-based device that will be connected to an android application which will

help the person set his path. The hardware module will consist of sensors offering haptic feedback

and proximity sensors for obstacle detection. The device will store frequently travelled destinations

along with the traversed path for future use.

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PAPER ID: AI24

Standalone Device for Home Automation and

Personalized Recommendation

Sameer Korlahalli1, Harsh Parmar2, Akshay More3, Prof. Pranjali Thakre4 1,2,3,4Department of Computer Engineering


Email: [email protected], [email protected], [email protected], [email protected]

Over the years of progress in technology, there have been great paradigm shifts in the way we

communicate with devices. In the early stages, it was through physical buttons, then came the

revolutionary touch screen, and now speech is fast becoming popular for communication, leading to

more and more natural interactions with the device. Voice has been gaining ground as an upcoming

mode of communication with the advent of smart assistants in our personal devices such as

smartphones. So, one of the practical applications of using this new mode of communication is to

automate our home’s appliances with our voice. To extend this application, this ‘home assistant’ can

perform web search and give results through voice, and suggest recommendations to the user based

on his/her appliance usage and web activity using machine learning. Hence, keeping in mind the

increasing use of voice based interaction and also extending the application using machine learning,

we are implementing this home automation device.

PAPER ID: AI26

A Synopsis of Analytics for a Search Engine Aishwarya Sadasivan1, Komal Dhuri2, Manaswini Muralidaran3, Prof. Meghna Mohan4

1,2,3,4 V.E.S.I.T, Chembur, Mumbai-400074


Our project covers the analytics involved in developing a Search Engine for an E-book portal. The

dataset for the same has been extracted from Project Gutenberg. Various front end and back end

algorithms have been implemented in order to analyse text. The front end processing includes- Spell

Checker, Text Segmentation and Language Modelling. Back end processing includes Similarity

Modelling, Clustering and Retrieval of results. The search query entered is processed by the front end

algorithms to obtain the most coherent sequence of words in a search query. Subsequently, the

backend processing algorithms are executed in order to obtain the similarity between the search query

and dataset thereby facilitating retrieval of relevant search results. In addition, to visualize the

correlations within the dataset we perform clustering.

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PAPER ID: AI27

Providing Personalized Study Material for Learning

Disability using Machine Learning

Mohit Shah1, Meet Shah2, Ameya Shirke3, Prof. Khushali Deulkar4

1, 2, 3, 4Department of Computer Engineering



The objective of the project is to diagnose a child with a learning disability and provide appropriate

study material according to his needs. The system is developed with a viewpoint of the intellectual

development of an individual suffering from Learning Disability. Earlier the detection of Learning

Disability better it is for the student’s growth as a proper remedial therapy can be applied on the

student for his intellectual development. The model will first classify a child as learning disabled or

not- learning disabled based on certain assessment parameters. Once diagnosed with learning

disability, the child is further classified into different types of learning disability like dyslexia,

dysgraphia and dyscalculia. The model will also identify the level of Learning Disability and provide

the student with study material for improvement. The model is trained using the student’s history and

parameters of curriculum-based test to determine the level of Learning Disability. Based on the level

of Learning Disability an Individualized Learning Plan will be provided to the children.

DJ ASCII-17

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PAPER ID: AI29

Document Classification Using NLP

Payal Jain1, Divya Panchal2, Abhishek Pandey3 1,2,3Department of Computer Engineering



Text Classification is a technique in which an unknown set of documents that are given to the

application are classified based on the features (words) that are present in the input document. The

very first stage in processing the document is to parse the sentences resent in the document using

Natural Language Processing, the sentences are parsed and a syntax tree having the nouns and verbs

is made. The document is further parsed using NLP, and taggers (Important words) are generated

based on the words extracted in the previous step. In this paper a Fuzzy Similarity Based Concept

Mining Model (FSCMM) is proposed to classify an unknown set of documents by preparing on the

sentence, document and integrated corpora levels using NLP. The Fuzzy Feature Category Similarity

Analyzer (FFCSA) is used to analyze each feature extracted from the Integrated Corpora Feature

Vector (ICFV) with the corresponding categories or classes. We will be using Vector Space Model

(VSM) to classify the documents using the Term-Frequency and Inverse Document Frequency (IDF,

to take into consideration the importance of the words that occur rarely but have a major impact on

classification of the document) to make the necessary calculations for the known set of documents

and then generate a similarity measure between the documents. The proposed model works efficiently

and effectively with high performance and high accuracy results.

PAPER ID: AI30

Intelligent Travel Bot using Machine Learning

Danish Ali Furniturewala1, Sagar Raulo2, Siddhant Rele3, Prof. Neepa Shah, Prof. Leena Raut 1,2,3,4Department of Information Technology


Email:[email protected]

There are many ways to plan a trip to a destination. The manual way is to book through a travel

company, which will give you an itinerary for your trip and the costs involved, another way is to book

through an online website, where you can pick a place, look for hotel, book a room and then make

travel arrangements to your desired place. The process involved is tedious and involves looking

through various booking websites to find the best bang for your buck. We propose a solution which

will make this process as smooth as possible through the use of an interactive travel bot deployed on

social media platforms. In this travel bot, a user enters a query asking for a place to stay in a location.

The travel bot then constructs a persona based on transactional history of the user, for example, hotels

that the user has shown interest in previously. Using this persona and our wide and deep network, a

personalized recommendation is generated by the system.

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PAPER ID: AI31

Categorization of Wheat

Prachi Patel1, Aditya Ramnathkar2, Hetashavi Shah3, Prof. Purva Raut4 1,2,3,4Department of Information Technology



Globally, wheat is the leading source of vegetable protein in human food, having a higher protein

content than other major cereals, maize or rice. In terms of total production tonnages used for food,

India is the second largest producer of wheat in the world. Analysis and Classification of wheat is

done visually and manually by human inspectors which is tedious, not accurate and requires an expert

judgment. An automated system is introduced which is used for categorization of wheat. The aim of

this proposal is to suggest algorithm for identification of wheat using machine learning techniques.

This inspection approach based on image analysis and processing has found a variety of different

applications in the food industry. This project proposes a model that to identify or recognize the image

on the basis of features of wheat grains present in the input image.

PAPER ID: AI33

Automatic Question Generation for E-Learning Systems

Riken Shah1, Deesha Shah2, Prof. Lakshmi Kurup3 1,2,3Department Computer Engineering

D.J. Sanghvi College of Engineering, India Mumbai

E-mail: [email protected]

We present a system of automatic MCQs (Multiple Choice Questions) generation in this paper. Given

an input text, the system dynamically generates a set of MCQs along with a valid set of distractors.

We have used Wikipedia-based dataset, which consists of URLs of Wikipedia articles to train the

system. The keywords (important words), which consist of both bigrams and unigrams are extracted

and stored in a data structure, along with many other components of the knowledge base. Inverse

Document Frequency (IDF) measure is used for ranking the extracted keywords and “Context-Based

Similarity’’ approach using Paradigmatic Relation discovery techniques is used for generation of

distractors. Also, the runtime execution phase of question generation includes eliminating sentences

that start with Discourse Connectives to avoid a question with incomplete information. We have

obtained significant accuracy compared to many similar approaches. We observe that results are quite

promising considering that there is no human intervention. Especially in MOOCs, the task of

automatic question generation can be of quite an importance. It has many applications in Intelligent

Tutoring Systems and for self-assessment while learning a new concept. Currently, we have trained

our system only for the field of physics, however, due to its generalized nature, it can be extended to

any field of study.

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PAPER ID: AI34

Interview Bot Vikash Salvi1, Adnan Vasanwalla2, Niriksha Aute3




Preparing for Interview is very haptic. It becomes difficult for a person to identify in which skill

he/she is lacking and improving that is very important. Interview Bot is an application which helps

user to prepare well for the Interview process. Interview Bot mainly focuses on the interview process.

User has to provide his/her resume to the bot. Bot will scan the resume and get the information such

as skills, marks of various examinations, achievements and certifications, if any, of the user. Bot will

perform Text Mining along with NLP on the resume and it will get the intricate details of the user.

Once that is done, it scans for the skills and experiences the user has. Accordingly it saves the skills

and collects the questions from the database. These questions are asked to user as aptitude test.

Crawler is responsible for getting these questions. After crawling, the questions are assigned difficulty

level. Based on the user’s level, a set of questions are asked to him/her. User answers questions and

after that it displays the score of the user. Based on the user’s answer, difficulty level of question as

well as user’s level is updated. Bot then takes the interview of the user, who clears the aptitude test.

The bot will be a 3D human model.

PAPER ID: AI35

Personality Identification using Social Media and its

Applications Ria Echhpal1, Najeeb Qazi2, Rohil Shah3 1,2,3Department of Computer Engineering,


E-mail?

Personality of an individual and psychology are widely studied and researched topics. They have

primarily dealt with a how a human interacts with his environment, peers and colleagues. His behavior

to situations is assessed and based on which, reasonable conclusions about his personality are derived.

Twitter is a social media platform, where a user can post what he is thinking in short sentences called

“tweets”. These tweets are limited to 140 characters which makes a user to convey his opinions in

distinct ways using slang, hashtags and short forms. These specific linguistic features can be used to

deduce useful traits of a person. This project would help us know how accurately we can predict a

person’s personality using Twitter. Myers-Briggs Type Indicator (MBTI) is a personality test which

assigns each person four letter code based on four parameters, thus creating 16 distinct personality

types. Analysing the data of users, the expected outcome is to predict accurately the personality. The

prediction results of the user’s personality can be used for many applications, such as corporate

recruitment, career counselling and even psychological evaluation.

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PAPER ID: AI41

Sarcasmometer

Measuring Sarcasm using Sentiment Analysis and Topic

Modeling

Namrata Bhan1, Janki Joshi2, Kena Mehta3, Prof. Mitchell D’silva4 1,2,3,4Department of Information Technology



Sarcasm is a type of sentiment where the notion that is conveyed is opposite of what it is meant. It is

generally used to denote something that is funny or to denote anger or dislike regarding a particular

situation. Sarcasm has become a part of our daily lives. It is used in various social networking sites,

review posts, entertainment businesses, etc. However, different people have different interpretation

of sarcastic texts and this leads to debatable opinions about the product which is being described.

Recognizing sarcastic statements can be very useful as it enhances the efficiency of after-sales

services or consumer assistance through understanding the intentions and real opinions of consumers

when browsing their feedbacks or complaints. In this paper we propose a system that will measure

sarcasm using tweets from Twitter. We propose different algorithms to calculate the effect of sarcasm

on texts and generate a score. Different features are generated from the received tweets which helps

us to generate the score. At the end, we compare the scores from different algorithms to present the

most efficient way to detect sarcasm. The proposed system also provide a separate portal to check the

score of any sentence/text entered by user and determine its score using the most accurate algorithm.

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PAPER ID: AI45

Object Recognition and Classification by Image Data

Analysis using Machine Learning Algorithm Siddhi Thakkar1, Sanket Shah2, Niyati Shah3, Raj Mehta4


Shah and Anchor Kutchhi Engineering College, Mumbai, India.


Digital images are widely used in various applications such as entertainment, security, business

purpose, scientific purposes and medical purposes etc. The captured images contain large amount of

information. The information in these images are not understandable to the computer system therefore

it is extracted by different computer vision methodologies and by optimization techniques for human

interpretation. Nowadays there is a major emphasis on extracting information from images. So, some

pre-processing enhancement on the image is required which eliminates the noise and prepares the

image useful for particular application. In this project work Object recognition and counting number

of object of particular class are the main objectives. In the first phase study of different methodologies

for recognising the objects of use is done. Various object detection techniques such as morphological

operations and Image Segmentation techniques are studied for object recognition. In this project work,

in phase I, identifying and extracting of the objects is done. Further these objects will be classified in

the classes of interest in phase II. This is performed by using the concepts of Back Propagation

Machine Learning Algorithm. Image classification is an important problem for classifying objects of

the image under consideration. Various image features are extracted and stored in the database.

Further machine learning algorithm such as Back Propagation can be applied for objects classification

of different images.

PAPER ID: AI54

Street Lighting Intensity Controller using

Density Mapping Mechanism

Rajas Walvalkar1, Yogesh Yadav2, Abhishek Yedurkar3, Sagar Suchak4, Prof. Swapnil Gharat5

1,2,3,4,5Department of Computer Engineering

Rajiv Gandhi Institute of Technology, Mumbai, India.


Object Detection with small computation cost and processing time is a necessity in diverse domains

such as: traffic analysis, security cameras, video surveillance etc. With current advances in technology

and de-crease in prices of image sensors and video cameras, the resolution of captured images is more

than 1MP and has higher frame rates. Real time video processing with high performance can be

achieved with GPU technology. The aim of this study is to evaluate the influence of different image

and video resolutions on the processing time, number of objects detections and accuracy of the

detected object. MOG2 algorithm is used for processing video input data with GPU module. Fuzzy

interference system is used to evaluate the accuracy of number of detected object and to show the

difference between CPU and GPU computing methods.

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PAPER ID: AI55

Video Annotation for Active E-Learning

Sneha Baviskar1, Shamli Dangare2, Shruti Gaikwad3, Shradhha Gosavi4

1,2,3, 4Department of Computer Engineering

[email protected], [email protected], [email protected],

[email protected]

Video annotation functions themselves will be beneficial for students in case of E-Learning or

distance learning. The first benefit is the easier browsing of the video lecture. Annotation of video

refers to the extraction of the information about video automatically, which can serve as the first step

for different data access modalities such as browsing, searching, comparison, and categorization. The

use of video lectures in distance learning involves the two major problems of searchability and active

user participation. In our project, we will promote the implementation and usage of a collaborative

educational video annotation functionality to overcome these two challenges. Different use cases and

requirements, as well as details of the implementation, will be explained. We want to indicate not

only that students perceive it as useful, but also that the learning effectiveness increases.

PAPER ID: AI56

Design and Fabrication of Prototype for Automatic Car

Parking System using RFID tagging for Modern Cities

(ACPS)

Saloji Mohammed1, Shaikh Alif2, Singh Sudhirkumar3, Nabanita Nath Chowdhury4

M.H. Saboo Siddik College of Engineering, Byculla, Mumbai, India.

Lack of space availability has always been a problem in urban areas and major cities and to add to it

there are cars parked callously on the streets that further limit the space. In order to handle the issue

of parking in busy places various types of vehicle parking systems are used worldwide namely Multi-

level Automated Car Parking, Automated Car Parking System, Volkswagen Car Parking [1] and

many more. The present project work is aimed to develop a reduced working model of a car parking

system for parking 6 to 10 cars. It is an amalgamation of the already developed parking systems with

the added advantage of reduced space occupancy by the design of a simpler and compact parking

system that is lifted up and occupies vertical parking space. The project is aimed to develop a car

parking system automatically without having driver. In automatic car parking, RFID module is used

along with car for finding on which floor, slot the car has to be parked. Here required slot is fixed for

some specific car. Here lifting mechanism along with different motors is used for parking a car to

required floor & slot. Hence ACPS can be used at busy commercial places, malls, hotels etc. to

prevent space shortage.

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PAPER ID: C001

Treal : Virtual Trial Room using Virtual Reality

Rajat Rao1, Jinesh Shah2, Mayur Chawada3




A virtual trial room is the online equivalent of an in-store changing room. It enables shoppers to try

on clothes to check one or more of size, fit or style, but virtually rather than physically. Due to the

increase interest in augmented reality and Virtual Reality, there have been many applications

developed. The current system of Virtual Trial Room is not as attractive as it can be. It lacks

participatory interaction from the user point of view. Keeping this in mind, the primary goal of Trial

is to interface 3D animation software and gesture recognition hardware to create an interactive trial

room environment. VR head gear is used for creating a virtual environment. This application

interaction method can be used to make the whole concept of trail rooms more visual, animated and

lively rather than the earlier systems.

PAPER ID: C004

Smart Cloud Phone Karan A. Shah1, Jinay Mehta2, Omkar V. Sawant3, Prof. Laxmi Kurup4

1,2, 3,4Department of Computer Engineering


E-mail: [email protected], [email protected]

Everyday new ideas and fresh concepts ushers in myriad of opportunities to upgrade the technological

devices. In a smaller attempt to stand with the changing technologies we came up with such a

smartphone unit that does not require processing unit. The mobile device will act as display unit and

all the computation part will be offloaded to the server where the OS is setup. This will minimize the

usage of resource’s in mobile client.

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PAPER ID: DM01

Consumer Credit Default Predictor

Yash Poddar1, Sanat Shah2, Anmol Sheth3, Prof. Chetashri Bhadane4 1,2,3,4Department of Computer Engineering

D. J. Sanghvi College of Engineering, Mumbai – 400 056

Emails: [email protected], [email protected]

Credit scoring models are very useful for many practical applications especially for banks and

financial institutions. The decision-making process of accepting or rejecting a client’s credit by banks

is commonly executed via judgmental techniques and/or credit scoring models. Most banks and

financial institutions use the judgmental approach that is based on the 3C’s, 4C’s or 5C’s which are

character, capital, collateral, capacity and condition.

Credit scoring is a system creditors use to assign credit applicants to either a ‘‘good credit’’ one that

is likely to repay financial obligation or a ‘‘bad credit’’ one who has a high possibility of defaulting

on financial obligation. Generally, Linear Discriminant Analysis and logistic regression are two

popular statistical tools to construct credit scoring models. However, with the advance in information

and computer technology new techniques are appearing under the name of data mining.

Data Mining and Machine Learning algorithms provide not only the classical methods but new novel

predictive modeling and classification techniques such as decision tree, neural networks, support

vector machine (SVM), and k-nearest neighbors. Our system also uses a Credit scorecard model that

is a hybrid model and combines the best of the features to generate higher, accurate and actionable

results.

PAPER ID: DM02

Dipriori

Yadynesh Desai1 , Mrunal Medhekar2 , Disha Mehta3 , Prof. Vinaya Sawant4 1,2,3,4 Department of Information Technology


Email: [email protected], [email protected]

Modern organizations are geographically distributed. There is lot of online as well as offline purchase

of data items taking place. Typically, each site locally stores its ever increasing amount of day-to-day

data. Using centralized data mining to discover useful patterns in such organizations' data isn't always

feasible because merging data sets from different sites into a centralized site incurs huge network

communication costs. Data from these organizations are not only distributed over various locations

but also vertically fragmented, making it difficult if not impossible to combine them in a central

location. Distributed data mining has thus emerged as an active subarea of data mining research.

Our proposed solution is going to apply the Apriori algorithm in distributed manner on real world

large datasets with precision and with great speed. This approach can be used by both online shopping

sites and offline marts.

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PAPER ID: DM03

Smart Question Paper Generator

Jagruti Malani1, Shreya Managute2, Khushboo Jain3, Prof. Khushali Deulkar4

1,2, 3,4Department of Computer Engineering



In Current Educational System, Teachers follows manual process for generating question paper which

is very tedious and time consuming task. Generating an effective question paper is a task of great

importance for any educational institute. Teachers search for the questions in each chapter so that the

entire syllabus gets covered in the generated question paper. There are chances of selection of some

questions in every examination because of biasing. This paper represents a smart question generation

tool that will automatically generate question paper and proposes its use in educational application.

The concept of selection by randomization is used. It is made to allow universities to generate question

papers with random but even questions to cover most chapters of subject within seconds. The paper

is produced by the tool according to standard university format specified by examiner. The smart

question generation tool will help generate papers from qualitative perspective and ease out teacher’s

tasks to a great extent.

PAPER ID: DM05

Drought Prediction and Management System using Big

Data Analytics

Benita Jeyakumar1, Vinita Rane2, Himani Shah3, Jayesh Nainani4, Dr. Nupur Giri5 1,2,3,4Department of Computer Engineering,

Vivekanand Education Society’s Institute of Technology, Mumbai, India.

Email: [email protected], [email protected], [email protected], [email protected], [email protected]

The prediction of occurrence of droughts has been a difficult task for a long time. However, it is

necessary that this prediction is done with at most accuracy to prevent loss of life and property. Based

on the previous year’s rainfall, temperature and evapotranspiration data, DDI is calculated which is

based on SPI, SPEI, PDSI, PHDI and ZIND indices. Training of this proposed index will be done

using random forest algorithm and the output will help to predict the severity of drought for the

upcoming years. Also, for resource allocation, dynamic quantum size round robin algorithm has been

used.

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PAPER ID: DM07

Prediction and Optimization of Products for Online

Sales

Shweta Sohani1, Neel Shah2, Aneri Shah3 1,2,3Department of Computer Engineering

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India [email protected], [email protected], [email protected]

How to forecast product sales effectively and efficiently in E-commerce is a significant task for E-

commerce producers to manage product inventory and design marketing strategies. However, under

the uncertainty of product demand, sales prediction is a complex task. The prediction of online sales

demands evaluation and accuracy. In this study different data mining prediction models/algorithms

to forecast the online sales and optimise the offers have been used. Although it is difficult to take into

account all the features/ attributes that influence the prediction of online sales, an attempt to find the

most significant features is made, also few software programs are used to find out the features that

are most contributing like R, various data mining techniques/models like decision making tree, F-

measure/ F-Score are used to evaluate the sales online. Finally the most significant attributes are

selected and the evaluation technique gives us the best F1-Score.

PAPER ID: DM09

Teacher Guardian Log System

Abhishek Tiwari1 1Department of Information Technology

Thakur College of Engineering & Technology, Mumbai, India.


The product is an entire ERP system which is a feature-rich web application for all the sections in the

hierarchy of the college. It deals in the way in which the files are accessed from the MySQL database.

The implementation has been carried out purely in Java under the J2EE framework. The product will

assist in organized management of the student information handled by their teacher guardians and the

higher authorities. The system is an Internet based application that can be accessed by all the

legitimate users from wherever they wish to access the system and read/write data based on their

privilege. The system is developed entirely for an Engineering college under University guidelines

and curriculum to maintain and facilitate easy access to information. For this, the users must be

registered with the system after which they can access as well as modify based on the privileges given

to them. This system can be used as a smart, knowledge based learning management system. It also

includes a Content Management System (CMS) for the same which gives it an upper hand on its

dynamicity and future purpose.

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PAPER ID: DM15

Duplication Avoidance in Big Data

Pravina Vyawahare1, Bhavin Bhoi2, Pratik Avhad3

1,2,3Department of Computer Engineering

Viva Institute of Technology [email protected], [email protected], [email protected]

The database is a collection of interconnected data which is managed and retrieved in an efficient

manner. The concept of the larger database is large scale database which will consist of many data

can be stored in the database system. Duplication of data is a technique for minimizing storage needs

by eliminating inordinate data. Data avoidance is rejection of risk, the action that can negatively effect

on a larger database system. Duplicate detection is a problem of material or stuff in many kinds of

application including user relationship management, confidential information management or data

mining. Duplicate detection is a method of detecting or observation of all cases multiple

demonstrations in the real-world application. In the existing system, the duplication of data is checked

based on string which checked character by character, so it is time-consuming and it occupied more

memory. The proposed system is implemented in Hadoop which handle larger database. Its consist

detection of duplicate data based on the multiple attributes. In our system, we used data pre-processing

is data mining technique that consists transformed row data in the understandable format. We applied

Parallel Progressive Sorted Neighborhood Method & Map Reduce algorithm on this data will get a

clean database. Hadoop Map-reduce programming allows for the processing of such large data in a

completely safe and cost-effective manner. It will provide more manageable space and efficient

handling of data.

PAPER ID: DM16

Weather Prediction Model: a Data Mining Approach

Sudhir Kuwar1, Pratiksha Gudme2, Manali Band3 1,2,3Department of Computer Engineering,

VIVA Institute of Technology, Mumbai, India.


Data mining is defined as the process of discovering the knowledge from a large amount of data. It is

the process of extracting the important information from a huge volume database. The proposed

system is developed to make use of data mining approach for the weather prediction. The proposed

system predicts the various numerical parameters of weather using the technique of Linear

Regression. It also uses the Decision Tree classifier, which trains the system to predict the rainfall.

The weather dataset for various cities has been gathered from the year 2010 to 2015. The existing

system can yield better results when applied on more cleaner and larger dataset. To overcome this

drawback of the previous system the proposed system makes use of the pre-processing techniques to

filter the large dataset and make the data more accurate and consistent, which will gradually improves

the accuracy of the prediction.

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PAPER ID: DM17

Web based Code Testing and Monitoring Engine

Adit Shinde1, Sushilkumar Takkekar2, Ratnesh Dubey3

1,2,3 Department of Computer Engineering

Ramrao Adik Institute of Technology, Nerul, Navi Mumbai, India


Practical sessions play an important role in improving the technical knowledge of a student. Most of

the colleges follow an offline system for the assessment of practical. An offline assessment of these

practical sessions consists of various steps and also has a number of flaws. Grading the students on

the basis of these sessions include the steps like compiling the source code, applying different test

cases, etc. which is a lengthy task. The procedure might seem easy if there are a few students but

more number of students make this a difficult task. An online assessment tool automates this

procedure and makes it more efficient. Students can be graded for a given experiment as soon as they

submit their code. The students would be able to improve their grades by submitting better solutions

for the same experiment. A solution could be assessed on more number of test cases, even the trivial

cases can be covered using an automated assessment tool. By the time a program is evaluated in an

offline manner for a few test cases, hundreds of test cases could be evaluated using an online tool.

Evaluation using trivial test cases would make the students develop the habit of writing efficient,

correct and concise codes. One such auto assessment tool is ‘Codebot’. Codebot allows the faculties

to add various experiments to a course and any number of test cases could be added for an experiment.

When a student selects a course, he can see a list of experiments to be performed. On submitting a

solution for a program, score would be shown on the basis of test cases passed for the given solution.

Codebot also gives an additional feature of live code monitoring to the faculties. Using this feature,

the faculties can monitor the code being written by a student from a remote computer. Codebot has

been written in Nodejs and has used Express framework. MongoDB has been used to support the

backend.

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PAPER ID: DM19

Graduate Application Evaluation

using Machine Learning

Varun Kasbekar1, Hiral Rayani2, Ami Sangani3 , Prof. Neepa Shah4

1,2,3,4Information Technology

Department of Information Technology

Jemin Jain5 ,Vivek Jain6 and Srinath Prabhu7 5,6,7Department of Computer Engineering


Email: [email protected], [email protected], [email protected],

[email protected],

Application Evaluation is a process of evaluating candidate’s profile for MS with respect to the

criteria's of the respective university. An increasing number of engineering undergraduates apply for

a master’s degree abroad preferably in United States. However the university standards of evaluating

a profile changes from university to university. Generally applicants GPA, GRE score,

IELTS/TOEFL scores, work experience, SOPs, LORs, Major and backlogs history plays a major role.

University selection alone has already become a big business in India. An applicant normally

approaches a counsellor for guidance regarding shortlisting the universities to apply for and related

information. This list can vary from counsellor to counsellor and can be error prone as no detailed

analytical study of past trends in a university is performed by the counsellor. Also a list of graduate

programs suitable for an applicant can be charged Rs.40000 in India. So the applicant has to shell out

a huge amount in order to get his/her profile reviewed by a counsellor. So here we would be providing

the solution to this problem by creating an Application Evaluation System that would be able to

determine whether an applicant would be getting an admit from a university of his choice using

Machine Learning.

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PAPER ID: DM20

Hybrid Approach to Distributed Document Clustering

Varun Kasbekar1, Hiral Rayani2, Ami Sangani3 , Neepa Shah4 1,2,3Department of Computer Engineering



The elevation in the field of information technology has resulted in a rapid increase in volumes of

data. Due to the enormous data generated, there is a massive demand for computational resources

which makes centralized clustering of distributed documents difficult. Therefore distributed

document clustering algorithms are required to cluster documents using distributed resources. The

proposed hybrid approach comprises of Particle Swarm Optimization (PSO), K-Means clustering and

Distributed Latent Semantic Indexing (LSI) algorithm, along with Map Reduce framework for

distributed computation. The resultant of this algorithm is expected to deliver great clustering quality

and the execution time will be considerably reduced as the dimensionality of documents reduces. The

Map Reduce framework is used as a distributed programming model which will improve the speedup

of algorithm.

PAPER ID: DM21

Agro Analytics: Drought Prediction and

Suggestions for Optimal Agricultural Practices

Manan Shah1, Mihin Sumaria2, Mohit Shah3 1,2,3Department of Computer Engineering



Agricultural statistics and forecast is an important resource that the government has not explored

commensurate to its impact. The aim of our project, Agro Analytics, is to make this process

computerized by implementing principles of data mining and analytics. More specifically, our project

aims at targeting the social issue of drought, analyzing data based on amount of rainfall, average

temperature and pressure, crop produce, agricultural inputs, and similar factors for crops in the state

of Maharashtra. Based on the extensive research carried out through this project, effective

countermeasures and suggestions will be given, which if implemented expeditiously, can help

tackling the problem of drought in our state and enable the farmer with the means to ensure a good

harvest. Data can be mined and analysed to find various trends and relations, such as – contrast

between total irrigation area and type of crop; total principal and non-principal crop amount versus

district-wise rainfall etc. The end result of the project will be research based reports specifying these

trends, studied and analysed from data taken over the past few years. Actions to minimize the damage

of drought and suitable farming techniques will also be suggested.

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PAPER ID: HCI03

Portable Book Reader for Visually

Impaired

Nishi Jain1, Mandar Kanade2, Harsh R Mehta3, Prof. Khushali Deulkar4 1,2,3,4Department of Computer Engineering,


Email: [email protected], [email protected], [email protected] [email protected]

For the visually-impaired population, the inability and inaccessibility to read has created a negative

impact on their quality of life. The books available are not easily found in separate volumes and there

are hardly a few applications available which help in reading the actual book in front of us. So we

thought of a portable device which the visually impaired can carry anywhere and at any time and

which is feasible to operate. In this paper, we discuss the design and implementation of the device

using the OCR engine and the TTS engine (Text-to-Speech) Conversion. We propose a prototype for

this portable device. This prototype utilizes an economical approach of being cost-effective. This

prototype can be seen as a loop of a user taking snapshots of the text, optical character recognition,

Text-to-Speech conversion and finally the process of playing the audio output to the user.

PAPER ID: HCI04

VidMute Silence those annoying loud ads

Rushabh Dharia1, Chirag Jain2 1,2Department of Computer Engineering,

Dwarkadas J. Sanghvi College of Engineering, Mumbai, India. [email protected], [email protected]

This paper describes our project “VidMute” which uses Image Processing to mute the advertisements

on YouTube. As we all know that advertisements can be very loud and annoying and can disrupt our

mood. So we decided to do something about it. Currently VidMute works only when the

advertisements are viewed in the full screen mode.

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PAPER ID: HCI06

Multiple Object Tracking and Monitoring

Shreya Redekar1, Nishita Sheth2, Nisha Shah3, Prof. Khushali Deulkar4 1,2,3,4Department of Computer Engineering,



This project proposes a novel method which assists in tracking and monitoring of multiple objects

through a video sequence. The system uses image processing mechanisms to instrument a prediction

model which focuses on a number of inter-linked factors for tracking of objects between different

frames. The entire system is divided into two phases, the detection phase, where objects are manually

detected in the first frame and later, recognised and associated in the consequent frames with image

processing techniques. In the second phase, the associated objects are tracked based on their

trajectories. In addition to trajectories, for ease of evaluation and tracking, images of the movement

of the object along with the respective coordinates are recorded on per second basis. The system is

designed to be robust and give positive results even in complex scenarios where a large number of

objects are being tracked simultaneously and where the objects face occlusions. This system can be

mainly used for security reasons, but when combined with other computing technologies like machine

learning, it can facilitate in learning the playing patterns of players in team sports.

PAPER ID: HCI08

MonVoix – An Android Application for Acoustically

Challenged People Aishwarya Danoji1, Aishwarya Dhage2, Rachana Kamat3, Priya Puranik4, Prof. Sharmila Sengupta5

1,2,3,4,5 Department of Computer Engineering

Vivekanand Education Society’s Institute of Technology, Mumbai-400074, India

Email: [email protected], [email protected], [email protected], [email protected], [email protected]

Communication is a mode through which people from various socio-economic backgrounds interact

with one another to develop a mutual relation. The ability to voice their opinions, ideas and intentions

effectively through messages is quite an essential life skill that majority of people possess. However,

there exists distinguishable cliques who are devoid of vocalizing their views but they dominate the

world of expressions through hand gestures. Acoustically challenged people have to rely on

interpreters to blend into a sane conversation with their hearing counterparts and not just be a mute

spectator. It is the need of the hour to find a common ground that can release the mute from these

shackles. This paper proposes an Android application- ’MonVoix’ for a coherent interpretation of

sign language gestures. This application offers users an interface to capture hand gestures through

their smart phone. A sequential image processing operations and database emulation is carried out in

the backdrop and the outcome procured is its corresponding textual meaning. The user can converse

with others either by posting the converted text or by attaching as an audio file.

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PAPER ID: HCI09

Interpretation of Music Score sheet to Generate

Audio File

Bhakti Raichura1, Karan Shah2, Ronak Thakkar3 1,2,3Department of Computer Engineering,



Music is considered to be the universal language. Music has a wide variety of applications and can

be perceived in aural, visual or written format. One of the major issues faced by a beginner in music

is reading music scoresheet. Generally, for beginners it is perplexing to understand which symbol

represents which note and it corresponds to which tune. Most beginners face issues deciphering the

scoresheet correctly and playing the correct tune which makes it difficult for them to learn and master

a particular tune. The proposed system aims at helping beginners in music to learn quickly by

generating an audio file as output for the users to listen to, by simple providing a music scoresheet

image as input. Segmentation is carried out using Hierarchical Decomposition and segmented

symbols are recognized by employing an Artificial Neutral Network coupled with a Boosting

algorithm. The proposed system makes use of PCA model followed by SVD for training. The sole

purpose is to help users decipher the symphony of music notes from scoresheet.

PAPER ID: HCI10

Structured Light 3D Scanner

(Point Cloud Generation using Triangulation)

Kushal Vyas1, Prof. Ruhina Karani2 1, 2Department of Computer Engineering,


E-mail: [email protected], [email protected]

The primary objective of this research is to produce a digital means for storing and replicating any

real world object. It focuses on a setup capable of analyzing and modelling a general object through

triangulations thereby estimating the object’s geometry. From the usual stereo setup, we prefer using

a single camera coupled with a projector, for faster and efficient reconstruction. The system makes

use of structured light for acquisition of geometry. The single view point clouds are then merged

together through a rigid body transform, further refined using the iterative closest point algorithm.

The end objective is to create a point cloud file of the entire 3D model. (The project was conducted

under the auspices of Automata Systems).

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PAPER ID: HCI11

Prevention of Accidents while Drunken Driving

Kevin Maru1, Prathamesh Dongre2, Purvi Udhwani3, Neha Mundra4


Vivekanand Education Society's Institute of Technology, Chembur, Mumbai, India.


This project proposes a model to increase vehicular safety. It basically consists of three modules -

Intelligent Headlight Control, Fog Removal, and Drowsiness Detection. Fog Removal has been

implemented for a single image using dark channel prior. Intelligent Control of Headlight is

implemented using an effective algorithm which uses SVM classifier for training the data to get

correct detection of blobs. The proposed model shows an algorithm to detect the Eye Map for eye

detection, iris and pupil detection, and analysing the state of the eyes to make the drowsy decision.

Finally, the paper shows how to make the required connections on a Raspberry Pi, and get the model

effective.

PAPER ID: HCI12

Virtual Try-On of Clothes

Aashni Savani1, Raj Vastani2, Harshal Vora3, Prof. Ruhina Karani4




Today one of the major problems in the apparel related e-commerce industries is that it is not possible

to know how the apparel fits or suits you just by looking at the images. We provide a solution to this

problem by the help of virtual try-on system where with the use of image processing methodologies

and techniques such as Image Warping and body ratios the user can see how the apparel (i.e. t-shirt)

will look on him/her. This will help is making the decisions regarding the purchase of goods online

easier and will help the e-commerce industry. The performance of the proposed system is evaluated

experimentally on the acquired images in the real life scenario. As per the result, the processing time

and the fitting accuracy varies with the image resolution and illumination changes.

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PAPER ID: HCI13

Baby Mentor: Learning through Images

Jeremy Samuel1, Sanket Solanki2, Saurabh Patil3, Prof. Ruhina Karani4




Technology changes the way how children think, what they learn, and the way they interact with

peers and adults. A computer based audio visual learning is often found to be effective for tutoring

babies and young children particularly those suffering from learning and mental disabilities. Baby

Mentor is a system that ameliorates this concept and makes learning a more interactive and fun based

activity by identifying and generating human like description for real world objects like toys, which

are commonly used by the children. The proposed system employs SIFT (Scale Invariant Feature

Transform) algorithm for feature detection and extraction. The features taken from SIFT is then used

to generate vocabulary for Bag of Visual Words Model which is then utilized for generating template-

based sentences. These sentences are conveyed through audio devices in a human like voice making

the children understand and recognise the object just like how a teacher or parent would teach them.

PAPER ID: HCI14

3D Facial Reconstruction using Skull of a Deceased

Person

Priya Singh1, Lilavati Swamy2, Aishwarya Tate3, Anam Shah4 1,2,3,4Department of Information Technology



Reconstructing the 3D facial model of an unidentified individual from his skull contributes

considerable benefits to terms of archaeology, anthropology and forensic investigation but it is still

significantly complicated matter. Computer aided system of 3D facial reconstruction based on skull

has a great advantage of reduction in time consumption. Nevertheless, existing results either contain

graphical artifacts or reflect incorrectly differences among reconstructed faces. In this paper, we

propose a 3D facial reconstruction system from skull that can overcome existing problems. We are

using SHA feature extraction since the human skull identification needs the shape of the curves

present. Neural Network is also used for estimating the age of the person so as to construct accurate

curves of the 3D face.

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PAPER ID: HCI15

Measuring Length of an Infant from its Image using

Reference Object and Monitoring Growth

Dimpi Dedhia 1, Nidhi Patel 2, Kavita Soni 3, Prof. Stevina Correia 4, Prof. Pratik Kanani 5

1,2,3,4,5Department of Information Technology,


E-mail: [email protected], [email protected], [email protected], [email protected], [email protected]

Keeping a track of an individual's growth is very important considering the importance of growth for

maintaining health and nutritional level. This practice is of much more importance in infants because

it helps in early detection of the infant's vulnerability to any disorder or disease like thyroid, Celiac

disease etc. Length and weight of the baby play an important role in understanding its growth. While

measuring the length of the infant using the currently used infantometer or a measuring tape, the

pediatricians face difficulties because of the infant's anatomy especially its bow-shaped legs. Forcibly

handling them for such measurements may result in causing harm to the baby's fragile bones. Thus

automation of such an exhausting task would prove to be of great help to the pediatricians and can

lead to faster, more efficient and reduced human efforts. Our system fully automates the task. All the

doctor has to do is capture an image and give weight of the baby as an input to the system. The system

generated length and weight values are than compared with the standard graph values by the system

and the doctor is shown a graph representing the comparison.

PAPER ID: HCI17

Interactive Learning using Augmented Reality Books

Aayushi Vora1, Soham Mehta2, Pratish Jain3



E-mail: [email protected], [email protected], 3p [email protected]

This paper intends to demonstrate how studying electronic concepts learning can be made easy. Using

the augmented reality, the project aims at simplifying the learning process of understanding electronic

devices, circuits and concepts. This application can be used by the students, and it will be as simple

as just hovering over the text or the image they want to understand. Automatically, the related data

will be shown from the application database or from the cloud. The project will enable students to

make the concepts clear by simply using the smart phone and the intended electronics book.

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PAPER ID: HCI20

Reflective Intelligence - an Odroid Based Approach

Priti Nalawade 1, Shraddha Upadhyay 2, Navin Das 3, Vijal Jain 4

1,2,3,4Department of Information Technology,

Vidyalankar Institute of Technology, Mumbai


The proposed work describes the design of a “Reflective Intelligent System”, an artifact augmented

with intelligence to demonstrate personalized services for enhanced comfort. The proposed system

aims at detecting the speech based command of the user and displaying the appropriate result on the

mirror and provides features like speech recognition, weather and news reports, maps and location,

to-do list etc. The proposed system will detect the presence of user by either detecting the user’s face

or voice and greet the user and display date, weather, etc. The user can then issue appropriate

commands. This project will be completely based on Android OS which will be hosted on Odroid C2.

PAPER ID: NS06

Novel Encryption Technique to Secure Document Data

Store

Elita Dsouza1, Dimpal Jayani2 , Anuja Patil3, Pratik Kanani4, Prof. Kriti Srivastava5 1,2,3,4,5Department of Information Technology,



In the rapidly evolving world of technology and the ever-increasing size of datasets, NoSQL databases

have become the one-stop solution for any enterprise. However, it has various challenges i.e. it is less

secure, authentication is not enabled by default, data transfer is in clear text format. There has been

significant increase in the interest shown by researchers for studying Security Issues in NoSQL.

Various algorithms and their combinations have been used in existing system to make the database

more secure. This paper proposes a system that makes use of Extended Transpose Substitution

Folding Shifting (ETSFS) Algorithm to secure hospital-related data as it is extremely critical. It

compares ETSFS with other algorithms like AES, DES, RSA, MD5 stating its advantages over the

others. To test the vulnerabilities in NoSQL database MongoDB, and to test how ETSFS enforces

security over big-data various attacks like NoSQL-injection, scripting attacks, unauthenticated

database access has been performed.

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PAPER ID: NS08

Prevention of Parallel Active Dictionary Attack on

WPA2-PSK Wi-Fi Networks

Drishti Kakar1, Nagendra Kamath2, Aneek Guha3, Dr. N. M. Shekokar4

1,23,4Department of Computer Engineering,



The wireless LAN provides ubiquitous access to the Internet globally, also being extremely user-

friendly and cheap. The secure access to the Internet is now of paramount importance. The modern

standard used is the Wireless Protected Access 2-Pre-Shared Key (WPA2-PSK), which protects the

IEEE802.11 wireless networks. The offline dictionary based attacks on the WPA2-PSK involves the

capturing of the four-way handshaking frames transferred between the Access Point (AP) and the

wireless client. The online parallel dictionary attack on the WPA2-PSK, however allows the external

client to bypass the frame capture phase and continuously inject pass phrases until itis accepted and

connection is established. We propose the use of an encrypted global counter in the message exchange

of the Extensible Authentication Protocol (EAP) over LAN (EAPoL)framework, the use of SHA-512

in Password Based Key Derivation Function - 2 (PBKDF2) and putting a limit on the number of

unsuccessful connection attempts to prevent parallel active dictionary attacks on WPA2-PSK Wi-Fi

networks.

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PAPER ID: NS10

Design and Overview of a Navigation Application

for the Blind

Sanjana Panicker1, Maitreyi KV2, Merrill Gonsalves3, Kane Gonsalves 3, Prof. Sandhya Patil4


Fr. CRIT, Vashi, Navi Mumbai, India.


Navigating brings up challenges for people who are Visually Impaired (VI). It is tough for people

with Visual Impairment to move both indoor and outdoor on their own. We aim to address these

challenges. Our application provides indoor navigation on a smartphone with the help of Bluetooth

Beacons and Indoor Atlas technology. The mobile application provides voice assistance to users to

navigate to their destination. The indoor component of the app is to assist members of the Xaviers

Resource Centre for the Visually Challenged(XRCVC). This application also provides outdoor help

for VI individuals and guides them to the nearest bus stop. GPS will be used for this function. The

application aims to facilitate a commuter to reach a bus stop of their choice. It provides information

such as bus numbers and different routes. Also the application prompts when the arrival of a desired

bus stop is expected. The application would be scalable and expandable to add more areas. This

application enables VI individuals to travel independently by overcoming many of the obstacles faced

by them.

PAPER ID: NS11

Enhancement of Security using Three Level Graphical

Authentication

Prashant Chiplunkar 1, Tejal Patil2, Sunil Dewoolkar 3

1,2,3Department of Computer Engineering,

VIVA Institute of Technology, Mumbai, India.


The most familiar authentication technique is to use textual usernames and passwords. This technique

possesses many flaws. For e.g. Normally users picks the passwords that are easily remembered but

the drawback over here is this password can also be easily guessed by the attackers. On the other

hand, if a word is hard to guess, then it's always troublesome to remember. To deal with this problem

we've a selection sort of a graphical positive identification which would be hard to guess and though

easily remembered by normal users. The Proposed three level authentication system provides

graphical passwords which can be easily remembered as well as provides security. In this system 1st

level is based on alphanumerical password,2nd level is based on RGB color pattern and 3rd level is

Related images.

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PAPER ID: NS19

Smart Network for Fire Control

Heena Tailor1, Kashmeera Sawant2, Niel Vaishya3, Shivani Sherekar4

1,2,3,4Department of Electronics & Telecommunications,

K.C College of Engineering Kopri, Thane


A smart network for fire control is a system which monitors the occurrence of fire and takes necessary

steps for fire controlling as well as to provide safe evacuation from the building. The system proposed

by us consists of sensors network which will detect gas element released by fire. If fire situation

arises, the warning ALARM'S will turn On immediately and sprinklers will also turned ON, to control

fire. System tries to reduce casualties due to panic, by determining point of occurrence of fire and it

uses indicators to guide the people towards the exist which are safe or unaffected by fire. In such

situations, calling for fire brigade is also necessary, which will done automatically by sending SMS

to nearest fire station. The system provides Graphical mapping of sensor and indicators on computer

which will be located away from building or inside the security room.

PAPER ID: NS20

Puppet Attack and its Detection

Manasi Deshmukh1, Jash Nichani2, Komal Mehta3, Prof. Aruna Gawde4



E-mail: [email protected], 2 [email protected], [email protected], [email protected]

Ad-hoc networks are computer networks which are not connected by any kind of cables. Ad-hoc

networks are prone to many attacks and one such specific attack is a puppet attack. In this paper, a

new DoS attack called puppet attack is presented, which can result in flooding of network due to the

attack packets sent by the intruder to the puppet node. This scenario is serious as it exhausts the

network communication bandwidth and node energy. A proactive and receptive defense architectures

have been coordinated, and arbitrarily collaborates with stochastic nearby node. Cooperative Bait

Detection scheme is used to detect the presence of malicious node in the network.

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PAPER ID: NS21

Intelligent Ambulance Fleet Management System

Monica Chhabria 1, Latika Wadhwa 2, Shruti Dhumale 3, Omkar Patinge4


Vivekanand Education Society Institute of Technology, Mumbai, India.


The time after a medical mishap if used optimally serves as a measure of the effectiveness of any

ambulance service provider system. For a minimal loss of life, recovery actions should be taken in

time. In spite of advancement of technology in today’s world, the service providers are not well

equipped. Also, problems like routing problems and traffic congestions hamper their speedy recovery

action in real time. Our aim is to save maximum number of lives in an emergency by reducing the

reaction time by various means. Pre-registration and extracting the real-time location helps to reduce

the reaction time. Another approach is by providing the shortest path to the ambulance driver. We

identified that the current traffic situation is the biggest challenge for the ambulance to reach in time.

Thus coordination with the traffic control room is essential in solving this problem. The proposed

system is fully automated and thus allows booking an ambulance, to which system allocates

ambulance and informing TCR in case of extreme emergency.

PAPER ID: NS22

An access control model for an E-Commerce Business

Model using Mongo-DB

Khushali Shah1, Priyal Shah2, Prof. Kriti Srivastava3




The wide proliferation of the Internet has set new requirements for access control policy specification.

Due to the demand for ad-hoc cooperation between organizations, applications are no longer isolated

from each other. Applying access control policies becomes challenging in a large, heterogeneous, and

dynamic environment. Policies, while maintaining their main functionality, go through many minor

adaptations, evolving as the environment changes. Current development platforms are web scale,

unlike recent platforms which were just network scale. There has been a rapid evolution in computing

paradigm that has created the need for data storage as agile and scalable as the applications they

support. With NoSQL databases being adopted by an increasing number of organizations, the

provision of security for them has become a growing concern. In order to implement a security

framework, it is mandatory to provide real time and on-demand access control management approach

that should take care of User identity, data integration and sanitation, multi-tenancy, relation between

different users and the resources. With the aim of encapsulating persistent goals of policies we

introduce extensions in the form of policies.

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AUTHOR INDEX

Aneri Shah 18 Danoji Aishwarya 24

Aute Niriksha 11 Das Navin 29

Avhad Pratik 19 Dave Vaibhav 4

Dedhia Dimpi 28

Band Manali 19 Desai Yadynesh 16

Baviskar Sneha 14 Deshmukh Manasi 32

Baxi Bhavin 2 Deulkar Khushali 8, 17, 23, 24

Bhadane Chetashri 16 Dewoolkar Sunil 31

Bhan Namrata 12 Dhage Aishwarya 24

Bhat Shivani 6 Dharia Rushabh 23

Bhoi Bhavin 19 Dhumale Shruti 33

Bhowmick Kiran 2 Dhuri Komal 7

Dikshit Chirag 6

Chawada Mayur 15 Dongre Parathamesh 26

Chhabria Monica 33 Doshi Krusha 1

Chiplunkar Prashant 31 Dubey Ratnesh 20

Chowdhury Nabanita Nath 14

Correia Stevina 28 Echhpal Ria 11

D’silva Mitchell 12 Furniturewla Danish Ali 9

D’souza Elita 29

Dangare Shamli 14

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Gaikwad Shruti 14 Korlahalli Sameer 7

Gawde Aruna 5,32 Kothari Bansari 1

Gharat Swapnil 13 Kurup Lakshmi 5, 10,15

Giri Nupur 17 Kuwar Sudhir 19

Gonsalves Kane 31 KV Maitreyi 31

Gonsalves Merrill 31

Gosavi Shradhha 14 Maheshwari Harsh 1

Gudme Pratiksha 19 Malani Jagruti 17

Guha Aneek 30 Managute Shreya 17

Gupta Ilina 5 Maru Kevin 26

Medhekar Mrunal 16

Jai Meghna 1 Mehta Disha 16

Jain Chirag 2 Mehta Harsh R 23

Jain Chirag 23 Mehta Jinay 15

Jain Hardik 1 Mehta Kena 12

Jain Khushboo 17 Mehta Komal 32

Jain Jemin Mehta Raj 13

Jain Nishi 23 Mehta Soham 28

Menezes Rachel 5

Kakar Drishti 30 Mohammed Saloji 14

Kamat Rachana 24 Mohan Meghna 7

Kamath Nagendra 30 Mohit Shah

Kanade Mandar 23 More Akshay 7

Kanani Pratik 28, 29 Muralidaran Manaswini 7

Karani Ruhina 25, 26, 27 Mundra Neha 26

Kasbekar Varun 21

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Nainani Jayesh 17 Patil Tejal 31

Nair Sindhu 1 Patinge Omkar 33

Nalawade Priti 29 Poddar Yash 16

Narula Harish 1 Prabhu Srinath

Narvekar Meera 2 Puranik Priya 24

Nichani Jash 32

Nisar Karan 2 Qazi Najeeb 11

Olia Fatema 5 Raichura Bhakti 25

Ramnathkar Aditya 10

Pamecha Monik 2 Rane Vinita 17

Panchal Divya 9 Rao Rajat 15

Panchamia Yash 4 Raulo Sagar 9

Pandey Abhishek 9 Raut Purva 10

Pandya Twinkle 1 Rayani Hiral 21

Panicker Sanjana 31 Rele Siddhant 9

Parekh Akash 4 Redekar Shreya 24

Parekh Sagar 4

Parmar Harsh 7 Sadasivan, Aishwarya 7

Patel Bhaveen 3 Sadaye Raj 6

Patel Nidhi 28 Salvi Vikash 11

Patel Prachi 10 Samuel Jeremy 27

Patil Anuja 29 Sangani Ami 21

Patil Sandhya 31 Sanghavi Kinjal 4

Patil Saurabh 27 Savani Aashni 26

Sawant Kashmeera 32

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Sawant Omkar V. 15 Shah Niyati 13

Sawant Vinaya 16 Shah Priyal 33

Sen Malabika 5 Shah Riken 10

Sengupta Sharmila 24 Shah Rohil 11

Shah Akash 3 Shah Sanat 16

Shah Anam 27 Shaikh Alif 14

Shah Aneri 18 Shekokar N. M. 30

Shah Bansi 3 Sherekar Shivani 32

Shah Bhavya 3 Sheth Anmol 16

Shah Deesha 10 Sheth Nishita 24

Shah Hetashavi 10 Shinde Adit 20

Shah Himani 17 Shirke Ameya 8

Shah Jinesh 15 Singh Priya 27

Shah Karan 25 Singh Sudhirkumar 14

Shah Karan A. 15 Sohani Shweta 18

Shah Khushali 33 Solanki Sanket 27

Shah Manan 22 Somasundaram Harishkandan 6

Shah Meet 8 Soni Kavita 28

Shah Mohit 8 Sowmyasree L. 6

Shah Mohit 22 Srivastava Kriti 29, 33

Shah Neel 18 Suchak Sagar 13

Shah Neepa 21 Sumaria Mihin 22

Shah Neeti 5 Swamy Lilavati 27

Shah Nisha 24

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Tailor Heena 32 Yadav Yogesh 13

Takkekar Sushilkumar 20 Yedurkar Abhishek 13

Tate Aishwarya 27

Thakkar Ronak 25

Thakkar Siddhi 13

Thakre Pranjali 7

Tiwari Abhishek 18

Turakhia Drashti 3

Upadhyay Shraddha 29

Udhwani Purvi 26

Vaishya Niel 32

Vasanwalla Adnan 11

Vastani Raj 26

Vora Aayushi 28

Vora Harshal 26

Vora Yash 6

Vyas Kushal 25

Vyawahare Pravina 19

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