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.
naidud@rknec.edu
View
Details
2 Automated Productivity and Work
Analysis for Industrial Videos.
Prof. Khushboo Khurana
Department: Computer Sc. & Engg.
khuranakp@rknec.edu
View
Details
3 Designing, Simulation and Study
of X-Ray Radiation MOS based
sensor for space applications
Prof. Shubham Anjankar
Department: Electronics Engineering
anjankarsc1@rknec.edu
View
Details
4 Designing, Simulation and Study
of Gamma-Ray Radiation MOS
based sensor for space applications
Prof. Shubham Anjankar
Department: Electronics Engineering
anjankarsc1@rknec.edu
View
Details
5 Flexible Antenna Design Prof. Archana Tiwari,
Department: Electronics Engineering
tiwariar@rknec.edu
View
Details
6 Development of android
application based Soil Macro
Nutrients Detection System for
farmers
Prof. Suresh Balpande
Department: Electronics Engg.
balpandes@rknec.edu
View
Details
7 Development of Triboelectric
Enery Harvester for internet-of-
the-things (IOT) sensor node
Prof. Suresh Balpande
Department: Electronics Engg.
balpandes@rknec.edu
View
Details
8 Design and Development of
framework for Eco-friendly Water
Cooling System.
Dr. T. A. Madankar
Department: Industrial Engineering
madankarta@rknec.edu
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
mujumdarub@rknec.edu
View
Details
Page 2 of 17
10 Design and Development of Early
Stage Disease Diagnostic System
through Nail analysis
Dr. (Mrs.) Richa R. Khandelwal
Department: Electronics Engineering
khandelwalrr@rknec.edu
View
Details
11 Development of Anomaly
Detection Model for
Security/Surveillance
Dr. (Mrs.) Richa R. Khandelwal
Department: Electronics Engineering
khandelwalrr@rknec.edu
View
Details
12 Design of System on Chip (SOC)
for the application of Biomedical
analysis
Dr. (Mrs.) Jayu Kalambe
Department: Electronics Engineering
kalambej@rknec.edu
View
Details
13 Development of hardware and
Control algorithm for Grid
Connected PV System.
Dr. Vijaya Huchche
Department: Electrical Engineering
huchchev@rknec.edu
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
joshipu@rknec.edu /
landevs@rknec.edu
View
Details
15 Grid Connected PV System
monitoring using IoT
Dr. G. N. Goyal / Dr. (Mrs) P. V.
Kapoor
Department: Electronics Engineering
goyalg@rknec.edu /
kapoorpv@rknec.edu
View
Details
Page 3 of 17
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
Brief description of the
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.
Expected outcomes of
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.
Requirements from the interns
UG / PG Program UG Program
Discipline CSE
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Programing using Python.
Specific skill set (eg. Programming,
theoretical reasoning,
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.
Name of the Principal
Investigator (PI)
Prof. Shubham Anjankar
Place of
Work/Department
Electronics Engineering
Brief description of the
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.
Expected outcomes of
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
Requirements from the interns
UG / PG Program UG/PG
Discipline EN, EC, EDT
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Knowledge of Metal Oxide Semiconductor Devices
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
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.
Name of the Principal
Investigator (PI)
Prof. Shubham Anjankar
Place of
Work/Department
Electronics Engineering
Brief description of the
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.
Expected outcomes of
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
Requirements from the interns
UG / PG Program UG/PG
Discipline EN, EC, EDT
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Knowledge of Metal Oxide Semiconductor Devices
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
Microscope etc.)
1. Constructing mathematical proofs
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5. Title of the Project Flexible Antenna Design
Name of the Principal
Investigator (PI)
Prof. Archana Tiwari
Place of
Work/Department
Electronics Engineering
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.
Requirements from the interns
UG / PG Program UG, PG
Discipline EN, EC, EDT
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,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
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
Page 8 of 17
Name of Principal
Investigator (PI)
Dr. Suresh Balpande
Place of Work/
Department
Electronics Engineering
Brief description of the
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.
Expected outcomes of
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
Requirements from the interns
UG / PG Program UG or PG
Discipline Preferably ‘e’ branches
Technical background
(eg. Courses that should
have been done, topics
that should have been
known)
Engineering Physics, Engineering Chemistry, android
application, machine learning techniques , Colorimetry
Specific skill set
(eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
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)
Prof. Suresh Balpande
Place of Work /
Department
Electronics Engineering
Brief description of the
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.
Expected outcomes of
the project
Patent, research publications and copyright(s).
Possible learning
outcomes for the
interns
Small scale energy generation mechanisms , Power management
unit, characterization methods
Requirements from the interns
UG / PG Program UG or PG
Discipline Any branch
Technical background
(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,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
Microscope etc.)
Understanding of polymers, Triboelectric mechanisms,
device testing.
Page 10 of 17
8. Title of the Project Design and Development of Framework for Eco-friendly
Water Cooling System.
Name of the Principal
Investigator (PI)
Dr. T. A. Madankar
Place of Work/
Department
Industrial Engineering
Brief description of the
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.
Expected outcomes of
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)
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
General science and engineering.
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
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
Name of the Principal
Investigator (PI)
Dr. Uday B.Mujumdar
Department of Electrical Engineering, RCOEM, Nagpur
Place of
Work/Department
Energy Research Centre,
Department of Electrical Engineering, RCOEM, Nagpur
Brief description of the
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.
Expected outcomes of
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.
Requirements from the interns
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
Name of the Principal
Investigator (PI)
Dr. (Mrs.) R. R. Khandelwal
Associate Professor, Electronics Engineering Department,
Place of
Work/Department
Electronics Department
Brief description of the
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.
Expected outcomes of
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.
Requirements from the interns
UG / PG Program UG
Discipline Electronics, EDT, Electronic and Communication Engineering,
CS, IT.
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Fundamentals of image processing
Basics of Machine Learning
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
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
Name of the Principal
Investigator (PI)
Dr. (Mrs.) R. R. Khandelwal
Associate Professor, Electronics Engineering Department,
Place of
Work/Department
Electronics Department
Brief description of the
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
Expected outcomes of
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.
Requirements from the interns
UG / PG Program UG
Discipline Electronics, EDT, Electronic and Communication Engineering,
CS, IT.
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Fundamentals of image processing
Basics of Machine Learning
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
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
Page 14 of 17
Biomedical analysis
Name of the Principal
Investigator (PI)
Dr. Jayu Kalambe
Place of Work /
Department
Centre for Microsystems/Electronics Engineering Department
Brief description of the
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.
Expected outcomes of
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
Requirements from the interns
UG / PG Program Both
Discipline Any
Technical background
(eg. Courses that should
have been done, topics
that should have been
known)
Basic Electronics, Basic Chemistry
Specific skill set
(eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipments
such as CRO, Electron
Microscope etc.)
Programming Skills
Basic knowledge of FPGA
Page 15 of 17
13. Title of the Project Development of i. hardware and ii. Control algorithm for
Grid Connected PV System.
Name of the Principal
Investigator (PI)
Dr. (Mrs.) Vijaya Huchche
Department of Electrical Engineering, RCOEM, Nagpur
Place of
Work/Department
Department of Electrical Engineering, RCOEM, Nagpur
Brief description of the
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.
Expected outcomes of
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.
Requirements from the interns
UG / PG Program UG/ PG
Discipline i. Electrical Engineering/ Electronics Engineering/ EDT/ EC
ii. CS/IT Engineering
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Basic Hardware Knowledge
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipment)
Programming of C/ C++
14. Title of the Project Design of AI/ML based ECG diagnosis application with
Page 16 of 17
power optimization for wearable gadgets.
Name of the Principal
Investigator (PI)
Prof. Pankaj Joshi, Electronics Engineering (PI) /
Prof. Vipul Lande Electronics and Comm. Engg. (Co-PI)
Place of
Work/ Department
Electronics Engineering
Brief description of the
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.
Expected outcomes of
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.
Requirements from the interns
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
Page 17 of 17
Name of the Principal
Investigator (PI)
Dr. G. N. Goyal
Department of Electrical Engineering, RCOEM, Nagpur
Name of the Co-
Principal Investigator
(Co-PI)
Dr. (Mrs.) P. V. Kapoor
Department of Electrical Engineering, RCOEM, Nagpur
Place of
Work/Department
Department of Electrical Engineering, RCOEM, Nagpur
Brief description of the
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.
Expected outcomes of
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
Requirements from the interns
UG / PG Program UG
Discipline Electrical Engineering/ Electronics Engineering/ EDT/
Electronics & Communication/CS/IT Engineering
Technical background (eg. Courses that should
have been done, topics
that should have been
known)
Basic Electronics
Digital Electronics
Microcontroller
Specific skill set (eg. Programming,
theoretical reasoning,
constructing
mathematical proofs,
handling specific
laboratory equipment)
1. Programming of C/ Python
2. Familiarisation with PCB designing software, Circuit
simulation will be preferred.
3. App Development
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