Research Internships @RCOEM - RKNEC

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Research Internships @RCOEM

Our college is offering Research Internships to the students of VIII semester BE. These

internships are designed to enhance the knowledge of the students and to provide them a

professional research experience. The selected interns are required to work full time on the

project for one full semester under the supervision of faculty guides and are exempted from

regular VIII semester classes. However, these students are required to complete the applicable

winter term and/or all other perquisites mentioned by their department.

The following internships are available to the students by the concerned faculty guides who

will work as Principal Investigators (PI). For detailed information regarding these projects the

students are requested to contact the concerned guide.

The students who are interested in these Research Internships are requested to contact the respective faculty guides on or before 26th November 2020.

Following internships are available:

SN Name of Project Faculty Guide

1 Anti-Social - Security from Social

Engineering attacks

Prof. Devishree Naidu

Department: Computer Sc. & Engg.

[email protected]

View

Details

2 Automated Productivity and Work

Analysis for Industrial Videos.

Prof. Khushboo Khurana

Department: Computer Sc. & Engg.

[email protected]

View

Details

3 Designing, Simulation and Study

of X-Ray Radiation MOS based

sensor for space applications

Prof. Shubham Anjankar

Department: Electronics Engineering

[email protected]

View

Details

4 Designing, Simulation and Study

of Gamma-Ray Radiation MOS

based sensor for space applications



[email protected]

View

Details

5 Flexible Antenna Design Prof. Archana Tiwari,


[email protected]

View

Details

6 Development of android

application based Soil Macro

Nutrients Detection System for

farmers

Prof. Suresh Balpande

Department: Electronics Engg.

[email protected]

View

Details

7 Development of Triboelectric

Enery Harvester for internet-of-

the-things (IOT) sensor node


Department: Electronics Engg.

[email protected]

View

Details

8 Design and Development of

framework for Eco-friendly Water

Cooling System.

Dr. T. A. Madankar

Department: Industrial Engineering

[email protected]

View

Details

9 Development of AI tools for life

estimation of Li-Ion batteries.

No. of Internships: Two(02)

Dr. Uday B. Mujumdar

Department: Electrical Engineering

[email protected]

View

Details

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10 Design and Development of Early

Stage Disease Diagnostic System

through Nail analysis

Dr. (Mrs.) Richa R. Khandelwal


[email protected]

View

Details

11 Development of Anomaly

Detection Model for

Security/Surveillance

Dr. (Mrs.) Richa R. Khandelwal


[email protected]

View

Details

12 Design of System on Chip (SOC)

for the application of Biomedical

analysis

Dr. (Mrs.) Jayu Kalambe


[email protected]

View

Details

13 Development of hardware and

Control algorithm for Grid

Connected PV System.

Dr. Vijaya Huchche

Department: Electrical Engineering

[email protected]

View

Details

14 Design of AI/ML based ECG

diagnosis application with power

optimization for wearable gadgets.

Dr. Pankaj Joshi / Prof. Vipul Lande

Department: Electronics Engineering /

Electronics & Communication Engg

[email protected] /

[email protected]

View

Details

15 Grid Connected PV System

monitoring using IoT

Dr. G. N. Goyal / Dr. (Mrs) P. V.

Kapoor


[email protected] /

[email protected]

View

Details

mailto:[email protected]

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1. Title of the Project Anti-Social – Security from Social Engineering attacks

Name of Principal

Investigator (PI)

Prof. Devishree Naidu

Assistant Professor in Computer Science and Engineering

Place of Work /

Department

Computer Science and Engineering Department, RCOEM

Brief description of the

project

Social engineering attacks are on the rise today and most cyber

attackers target people through such tactics like fake calls,

messages, mails, links etc. The project is aimed at designing a

mobile application to protect users from such attacks by

accessing calls, messages, emails in real time, perform analysis

on them and alert the user regarding their malicious nature in

minimal processing time possible.

Expected outcomes of

the project Access links and documents shared via Whatsapp, SMS etc.

Perform analysis on the links in the backend and verify their

authenticity.

The links can then be classified as having malware, phishing,

etc. as per the analysis results.

The user must be alerted about the type of link they are about

to click.

The application must specifically focus on fast computation

time on link analysis since users require instant results.

The concept of Machine Learning can be used to enable the

application to identify links based on experiences rather than

a fixed database.

The application must identify fake messages, mails etc. even

if they do not consist of any links. This identification must be

done based on the general format in which these fake

messages are written.

Possible learning

outcomes for the

interns

Experience in android app development, learning social

engineering tactics and their prevention, utilising machine

learning to develop smart applications

Requirements from the interns

UG / PG Program B.E, MCA, M.Tech Program

Discipline Computer Science, IT

Technical background (eg. Courses that should

have been done, topics

that should have been

known)

Mobile Application Programming, Network Security, topics

related to Cyberattacks, Information security, Machine Learning.

Cloud computing.

Specific skill set (eg. Programming,

theoretical reasoning,

constructing

mathematical proofs

etc.)

Python, Machine learning, android development

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2. Title of the Project Automated Productivity and Work Analysis for Industrial

Videos.

Name of the Principal

Investigator (PI)

Prof. Khushboo Khurana, CSE, RCOEM.

Place of Work /

Department

Computer Science and Engineering Department, RCOEM


project

The main objectives of the project are:

To develop a framework for automated analysis the videos

from a small scale industry.

Work Analysis: It is expected to compute the working hours

of various operators working at different machines.

Productivity Analysis: To find the number of pieces

manufactured at each machine for various products.


the project

To generate day-wise plant working report.

Possible learning

outcomes for the

interns

Learn to perform video analysis using video processing

techniques.

To learn and design solution using the Deep Learning

techniques. To perform experimentation using tensor flow and

keras.


UG / PG Program UG Program

Discipline CSE




known)

Programing using Python.



constructing

mathematical proofs,

handling specific

laboratory equipments

such as CRO, Electron

Microscope etc.)

Knowledge about image or video processing will be

appreciated.

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3. Title of the Project Designing, Simulation and Study of X Ray Radiation MOS

based sensor for space applications.


Investigator (PI)


Place of

Work/Department

Electronics Engineering


project

Ionizing radiation causes degradation to electronic devices.

Space devices are facing major issues of degradation like

threshold shift, body bias current swift, interface charge

trapping due to ionizing radiation. X-rays and Gamma rays are

most powerful radiation results to degradation of devices causes

whole chip and circuit failure. As device fabrication technology

is shrinking causing more circuit failure.

Aim of this project is to study and simulate same radiation

effects so that sensors can be designed to overcome that effect.


the project

1. Research Paper

2. Radiation Sensor

Possible learning

outcomes for the

interns

1. MOS devices fabrication and simulation

2. MOS devices characterisation

3. Radiation effect on electronic devices


UG / PG Program UG/PG

Discipline EN, EC, EDT




known)

Knowledge of Metal Oxide Semiconductor Devices



constructing


handling specific



Microscope etc.)

1. Constructing mathematical proofs

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4. Title of the Project Designing, Simulation and Study of Gamma Ray Radiation

MOS based sensor for space applications.


Investigator (PI)


Place of

Work/Department



project

Ionizing radiation causes degradation to electronic devices.

Space devices are facing major issues of degradation like

threshold shift, body bias current swift, interface charge

trapping due to ionizing radiation. X-rays and Gamma rays are

most powerful radiation results to degradation of devices causes

whole chip and circuit failure. As device fabrication technology

is shrinking causing more circuit failure.

Aim of this project is to study and simulate same radiation

effects so that sensors can be designed to overcome that effect.


the project

1. Research Paper

2. Radiation Sensor

Possible learning

outcomes for the

interns

1. MOS devices fabrication and simulation

2. MOS devices characterisation

3. Radiation effect on electronic devices


UG / PG Program UG/PG





known)

Knowledge of Metal Oxide Semiconductor Devices



constructing


handling specific



Microscope etc.)

1. Constructing mathematical proofs

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5. Title of the Project Flexible Antenna Design


Investigator (PI)

Prof. Archana Tiwari

Place of

Work/Department


Brief description

of the project

The aim of the proposed research work is to design, fabricate an

antenna with flexible substrate materials for working on ISM

band (Industrial Scientific Medical band). Depending on the

comparative study based on the parameters like compactness

(size and thickness), electrical properties (permittivity, loss

tangent & thickness) and robustness the substrate material

could be selected as polyamide, felt fabric, Rogers RO3003

flexible, polyethylene terephthalate (PET) films, Kapton etc.

Expected outcomes

of the project

To design and fabricate the flexible antenna to allow exploiting

the area of

clothing and other flexible materials to create efficient antennas

in critical applications.

Possible learning

outcomes for the

interns

It provides career path to get into different antenna

manufacturing industry such as Linx technology, Wavelin

Inc. etc.

It provides an active participation in the electronics

industry where advance antennas are essential equipment

such as in Samsung,

Apple etc.

It provides an opportunity to serve as a research person

in RF & Microwave industries and research

organizations.


UG / PG Program UG, PG


Technical background

(eg. Courses that

should have been

done, topics that

should have been

known)

Graduate level studies in the field of Physics or adjacent field

like Electromagnetics, radiation and waves propagation,

antennas etc.

Specific skill set

(eg. Programming,


constructing


handling specific



Microscope etc.)

Good proficiency in one or several of the following RF-

analysis and general design tools such as CST, HFSS,

MATLAB etc. are required.

6. Title of the Project Development of android application based Soil Macro

Nutrients Detection System for farmers

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Name of Principal

Investigator (PI)

Dr. Suresh Balpande

Place of Work/

Department



project

This system would be useful to determine concentration of

macronutrients like nitrogen, phosphorous, potassium, carbon

etc in soil/water etc. Smartphone camera interfacing, android

application development, and calibration are the major stages.


the project

Idea would be converted to product. This system would be

very useful for farmers

Outcome:

Patent, research publications and copyright(s).

Possible learning

outcomes for the

interns

Smart phone camera handling , sensor working and calibration

process, nutrients detection methods


UG / PG Program UG or PG

Discipline Preferably ‘e’ branches


(eg. Courses that should



known)

Engineering Physics, Engineering Chemistry, android

application, machine learning techniques , Colorimetry

Specific skill set

(eg. Programming,


constructing


handling specific



Microscope etc.)

Camera handling/ colour sensor, optical filters, android

Programming, machine learning.

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7. Title of the Project Development of Triboelectric Energy Harvester for

internet-of-the-things (IOT) sensor node

Name of Principal

Investigator (PI)


Place of Work /

Department



project

This system would be used as a perpetual alternative to

battery/power supply to drive a sensor node. This technique

will make any low power system/gadget like wrist watch,

fit band, sensor nodes etc self powered.


the project

Patent, research publications and copyright(s).

Possible learning

outcomes for the

interns

Small scale energy generation mechanisms , Power management

unit, characterization methods


UG / PG Program UG or PG

Discipline Any branch


(eg. Courses that

should have been

done, topics that

should have been

known)

Nano materials (physics), Engineering chemistry,

Material science, Engineering Mechanics.

Specific skill set

(eg. Programming,


constructing


handling specific



Microscope etc.)

Understanding of polymers, Triboelectric mechanisms,

device testing.

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8. Title of the Project Design and Development of Framework for Eco-friendly

Water Cooling System.


Investigator (PI)

Dr. T. A. Madankar

Place of Work/

Department

Industrial Engineering


project

Specifically in summer, getting very hot water through tap is

very common problem. The proposed work will be focused to

conduct the research work for evaluating the various parameters

related to the problem, conducting the detail experimentation

and finding out the eco-friendly way to remove the heat from

hot water coming from overhead tanks to the tap fitted in

various places at offices and in houses without using the

electricity.


the project

To design and develop the framework of removing the heat

without using electricity.

Possible learning

outcomes for the

interns

Design of Experimentation through practical approach.

Requirements from the interns:

UG / PG Program UG

Discipline Any branch ( But more useful to Mechanical and Industrial

Engineering)




known)

General science and engineering.



constructing


handling specific



Microscope etc.)

Mechanical fabrication, installation of setup and handling the

laboratory equipments such as various thermometers, sensors

and interested in basic chemistry.

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9. Title of the Project Development of AI tools for life estimation of Li-Ion

batteries


Investigator (PI)

Dr. Uday B.Mujumdar

Department of Electrical Engineering, RCOEM, Nagpur

Place of

Work/Department

Energy Research Centre,



project

Li-Ion batteries are playing a crucial role in the fields of

renewable energy systems and electric vehicles. The reliability

of these systems depends on a battery management system

(BMS) which monitors the state of charge (SoC) and state of

health (SoH) effectively. Knowing the SoH of a battery in

advance enhances the system reliability.

Presently, Energy research centre of the college is working on

the life estimation of Li-Ion batteries. In this work, the Li-Ion

batteries are charged and discharged under controlled operating

conditions using the hardware already developed in the centre.

All the related parameters are logged for the further analysis.

Application of AI-ANN tools on the battery charging/

discharging parameters for accurate estimation of balance life of

the battery is

the challenging task. Same is the main objective of this

internship project.


the project

Development of AI-ANN based algorithm for accurate

prediction of balance life of Li-Ion battery is the expected

outcome of this

project.

Possible learning

outcomes for the

interns

After the successful completion of Internship, Internee/s will be

able to

Model Li-Ion battery used in Electrical vehicles,

Apply digital filters on the real time generated data,

Apply/Develop AI-ANN tool/s on the real time battery

charging/discharging data.


UG / PG Program UG/ PG

Discipline Computer Science/Information Technology/Electrical/

Electronic/Electronics & Communication/EDT/Mechanical

Technical background Basics knowledge of Electrical engineering i.e. covered

in Electrical Engineering course

Specific skill set Interns should have sound knowledge of Python and

AI Tools.

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10. Title of the Project Design and Development of Early Stage Disease Diagnostic

System through Nail analysis


Investigator (PI)

Dr. (Mrs.) R. R. Khandelwal

Associate Professor, Electronics Engineering Department,

Place of

Work/Department

Electronics Department


project

Nails are the body part which are last to receive oxygen as they

are farthest from the heart. As a result the nails are the first who

shows the symptoms of disease in the human body.

Through this project work we will design and develop a system

that can take images of nails, extract features from the images,

predict the disease using classifier and display the result to the

user.


the project

The system will prove to be useful in early detection of the

disease.

The developed system will be easy to use and cost effective.

Possible learning

outcomes for the

interns

After working on the research project, interns will be able to

apply knowledge related to Image Processing and

machine learning to develop system

implement algorithms contentedly using simulation

tools and experimental environment

communicate research results with academic standards

orally as well as in writing.


UG / PG Program UG

Discipline Electronics, EDT, Electronic and Communication Engineering,

CS, IT.




known)

Fundamentals of image processing

Basics of Machine Learning



constructing


handling specific



Microscope etc.)

Interns should have the basic knowledge of implementation of

algorithms in Python. Basics of working on Raspberry Pi kit.

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11. Title of the Project Development of Anomaly Detection Model for

Security/Surveillance


Investigator (PI)

Dr. (Mrs.) R. R. Khandelwal

Associate Professor, Electronics Engineering Department,

Place of

Work/Department

Electronics Department


project

Anomaly detection is a technique used to identify unusual

patterns that do not conform to expected behavior, called

outliers. It has many applications such as anomaly detection for

traffic control, in health monitoring (spotting a malignant tumor

in an MRI scan), fraud detection in credit card transactions and

fault detection in operating environments. The objectives of this

project work will be

1. Characterise the properties of the Surveillance/ security

domain that are required to select suitable anomaly

detection algorithm

2. Review and analyze the existing methods

3. Propose a method for anomaly detection based on literature

survey

4. Evaluate the proposed method on different data sets

5. Compare the evaluation of proposed method with the results

of existing methods


the project

The developed system will be able to detect anomaly and

analyze the abnormality to provide security to the system.

Possible learning

outcomes for the

interns

After working on the research project, Interns will be able to

apply knowledge related to Image Processing and machine

learning to develop system

implement algorithms contentedly using simulation tools

and experimental environment

communicate research results with academic standards

orally as well as in writing.


UG / PG Program UG

Discipline Electronics, EDT, Electronic and Communication Engineering,

CS, IT.




known)

Fundamentals of image processing

Basics of Machine Learning



constructing


handling specific

laboratory equipment )

Interns should have the basic knowledge of implementation of

algorithms in Python.

12. Title of the Project Design of System on Chip (SOC) for the application of

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Biomedical analysis


Investigator (PI)

Dr. Jayu Kalambe

Place of Work /

Department

Centre for Microsystems/Electronics Engineering Department


project

In this project we proposed to develope

the Microfluidics based fully automated fluid Analysis platform

for the analysis of various fluids using image processing

techniques and machine learning algorithm. The developed

system will be implimented on hardware platform such as

FPGA and mapped with microfluidics platform. This system

can be utilize for the development of biomedical application.


the project

Fully Integrated platform for fluid analysis will be developed

which can be utilize for biomedical application.

Possible learning

outcomes for the

interns

Application of FPGA for developement of System for fluid

analysis

Microfluidics (New platform for fluid analysis) Chemistry

behaind the fluid analysis

Research paper writting

Research work presentation


UG / PG Program Both

Discipline Any


(eg. Courses that should



known)

Basic Electronics, Basic Chemistry

Specific skill set

(eg. Programming,


constructing


handling specific



Microscope etc.)

Programming Skills

Basic knowledge of FPGA

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13. Title of the Project Development of i. hardware and ii. Control algorithm for

Grid Connected PV System.


Investigator (PI)

Dr. (Mrs.) Vijaya Huchche


Place of

Work/Department



project

Renewable energy has been a subject of research owing to the

continuous environmental concerns across the globe.

Employing photo-voltaic (PV) cell modules, harnessing solar

power has become one of the most viable sources of renewable

energy.There are growing trends in setting up grid interactive

power plants worldwide. In grid interactive mode the solar

power can be utilised to its full potential. This project will help

in adding the power in grid thus indirectly will reduce the

import of power from other sources. The grid interfacing

inverter in the presented system can be used to current

harmonics compensation at PCC. The sophistication in power

electronics and digital control technology has capacitated the

PV systems are now regulated to step up the system operation

with improved power quality.


the project

Research outcome in the area of power quality will be utilized

in:Development of inverter to mitigate power quality issues in

general and improvement of overall power factor in particularof

the Grid Connected PV System.

i. Completely developed hardware set up.

ii. Control algorithm development with microcontroller.

Possible learning

outcomes for the

interns

Interns will get an insight into

i. hardware/PCB development.

ii. Control algorithm development with microcontroller

so that their skills will be developed keeping in view the need

of the industry.


UG / PG Program UG/ PG

Discipline i. Electrical Engineering/ Electronics Engineering/ EDT/ EC

ii. CS/IT Engineering




known)

Basic Hardware Knowledge



constructing


handling specific

laboratory equipment)

Programming of C/ C++

14. Title of the Project Design of AI/ML based ECG diagnosis application with

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power optimization for wearable gadgets.


Investigator (PI)

Prof. Pankaj Joshi, Electronics Engineering (PI) /

Prof. Vipul Lande Electronics and Comm. Engg. (Co-PI)

Place of

Work/ Department



project

Cardiovascular disease (CVD) tops the reason of deaths around

the globe as per World health Organization (WHO) survey.

Electrocardiograph (ECG) has been considered as primary

instrument for investigation of CVDs. In recent years portable

ECG machines have developed , but to monitor ECG over long

period and during routine activities of a patient remains still a

challenge. To address such issue researchers are developing

healthcare wearable gadgets.

Our focus is to develop efficient algorithm/architecture for

acquiring ECG signal with low computational load on

processing hardware with an objective to reduce power

consumption. The diagnosis of CVDs through accurate and

efficient investigation by ECG may be achieved by deployment

of Deep Neural Networks (DNNs) techniques. DNNs have

emerged as the state-of-the-art technique in a wide range of

machine learning tasks for analytics and computer vision in the

next generation of embedded (mobile, IoT, wearable) devices.

Despite their success, they suffer from high energy

requirements both in inference and training.

In recent years, the inherent error resiliency of DNNs has been

exploited by introducing approximations at either the

algorithmic or the hardware levels to obtain energy savings

while incurring tolerable accuracy degradation. We will

perform a comprehensive analysis to determine the

effectiveness of approximations for this DNN.


the project

1. Scopus Journal Paper

Possible learning

outcomes for the

interns

1. Students will gain the knowledge about Biomedical

equipments, Smart sensors, wearable gadgets architecture and

Machine learning.

2. Students will learn optimization of DNN Algorithms and its

hardware realizations.


UG / PG Program UG, PG

Discipline Electronics/ Electronics and Communication

Engineering/ Computer Science

Technical background Signal Processing, Digital System Design, Digital

Logic Design

Machine Learning (Not a Compulsion)

Specific skill set Matlab, Python, VHDL or Verilog HDL coding

15. Title of the Project Grid Connected PV System monitoring using IoT

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Investigator (PI)

Dr. G. N. Goyal


Name of the Co-

Principal Investigator

(Co-PI)

Dr. (Mrs.) P. V. Kapoor


Place of

Work/Department



project

Owing to continuously booming energy demand, if the reliance

is on fossil fuel only then energy crunch is very near within few

decades. To explore renewable green energy sources is the

empirical solution which can dodge the energy crunch. In order

to bridge the energy gap, solar energy is used widely. In

interfacing of grid with voltage source inverter, the pivotal

concern is synchronization. In this project, interfacing of solar

PV panels and Ac grid is implemented using line commutated

twelve pulse converter and it does not necessitate additional

synchronizing circuit. The performance of PV array is affected

by variation in irradiance and temperature. As a consequence,

the Maximum Power Point (MPP) also shifts. A Maximum

Power Point Tracking (MPPT) controller is modelled in order

to utilize maximum power from PV array.


the project

Real time monitoring and display of expected outcome of the

project.

Possible learning

outcomes for the

interns

Interns will get an insight into

1. Application of IoT in renewable energy: learning sensor-based

technology

2. Microcontroller programming and its implementation.

3. Familiar with SCR Converter


UG / PG Program UG

Discipline Electrical Engineering/ Electronics Engineering/ EDT/

Electronics & Communication/CS/IT Engineering




known)

Basic Electronics

Digital Electronics

Microcontroller



constructing


handling specific

laboratory equipment)

1. Programming of C/ Python

2. Familiarisation with PCB designing software, Circuit

simulation will be preferred.

3. App Development

Research Internships @RCOEM - RKNEC

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