Research Laboratories

Research Laboratories

R&D Centre

Jawaharlal Nehru Technological University Kakinada(JNTUK), Kakinada, Andhra Pradesh has recognized Department of CSE, Velagapudi Ramakrishna Siddhartha Engineering College,Vijayawada, Andhra Pradesh as a Research Center For The Academic Years 2014-15, 2015-16, 2017-18, 2018-19, 2019-20, 2020-21.

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ISRO, RESPOND - Geo Spatial Lab

Objective:
Suite of best fit algorithms along with pixel level confidence level estimates addressing local scale quantitative and regional scale qualitative bamboo resources assessment
Scope:
Study area of this project is limited to KarbiAnglong East & West district and DimaHasao District of North-Eastern Region (NER) of India

Sanctioned On : 27th Aug 2021, Duration : 3 Years (2021-2024), Funding Agency : ISRO, Department of Space
Project Amount : Rs 25,30,000/-

Artificial Intelligence Lab for Remote Sensing Data Analysis

Objective:
The main objective of the proposed project is to collect the old datasets, or generate maps form VHRS data, and update the maps/GIS database using latest VHRS to produce new maps
Scope: Study area of this project is limited to Atal Mission for Rejuvenation and Urban Transformation (AMRUT)
Sanctioned On : 23rd June2022, Duration : 2 Years (2022-2024),
Funding Agency : ISRO, Department of Space, NRSC
Project Amount : Rs 17,84,920/-
Project Title : Updating of Very Large Scale Urban GIS Maps with Latest Very High Resolution Satellite Data Using Deep Learning Techniques
Principal Investigator : Dr. S.Vasavi, Professor, Dept of CSE
Co- Principal Investigator : Dr. SC Jaynathi, Scientist SG, Group Head, Urban Studies and Applications (USAG), National Remote Sensing Centre (NRSC), Hyderabad
Co- Principal Investigator : Dr. M.Sobhana, Sr Asst Professor, Dept. of CSE
Co- Principal Investigator : Smt N.Malathi , Asst Professor

ISRO, ADRIN – Video Analytics Lab

Artificial Intelligence & Machine Learning Lab

Objective:
To motivate the faculty and students to carry out research in Artificial Intelligence and Machine Learning.
Achievements:
Dr. K. Suvarna Vani registered for Post Doctoral Fellowship.
Ph.D. Awarded during last 4 years:
1. Dr. K. Praveen Kumar
2. Dr. G. Kranthi Kumar
3. Dr. B. Jayanag
Mr. J. Karthik Submitted Thesis:
Registered for Ph.D:
1. Mr. A. Raghu Veera Pratap
2. Mrs. M. Vani Pujitha
3. Ms. V. Deepa
Consultancy:
Resource App Management from Apsolut Software India Pvt. Ltd., for worth of Rs.75000/- by Dr. M.Sobhana, and Mr.A.R.V.Pratap.
Seed Grant Project funded by Siddhartha Academy of General and Technical Education
Title of the Project : Crop Yield and Price Prediction
Principal Investigators : Dr. G. Kranthi Kumar
Sanctioned Amount : Rs. 35000
Title of the Project : Smart Door Lock using Simultaneous Face Liveness and Face Detection Algorithms
Principal Investigators : Dr. G. Anuradha
Sanctioned Amount : Rs. 26250

Publications during 2020-21

Publications during 2021-22

Title:- Sugarcane price and yield prediction using forecasting models
Agriculture is the major thing for which we are targeting. Farmers take part a remarkable role in agriculture sector. Farmers lose a large amount when the value of a product drops after the harvest. Agricultural commodity price variations will influence the country’s economy. Estimation of crop prices and evaluations are performed in order to make a profitable decision prior to the cultivation of a specific crop. Forecasting the price of a crop will help farmers to make smarter judgments, which will help them to save money. We projected the price of some crops and have done the same process for some other commodities. Crops price are predicted based on some factors like previous rainfall and previous year’s prices of the crop. The decision tree regressor algorithm was utilized to assess documented data and forecast price for the forthcoming months. The results were displayed in a mobile app.

Journals:
https://www.tandfonline.com/toc/wcim20/current?cookieSet=1
https://www.springer.com/journal/12892
https://ipindexing.com/journal-details/Advance-Research-Journal-of-Crop-Improvement/828
http://researchjournal.co.in/temp/temp/admin_checkpaper2.asp?j=27

Title:-  Smart  Door Lock using Simultaneous Face Liveness and Face Detection Algorithms

The rapid growth of technology in the modern society has raised many questions on the terms like security and privacy. Doors act as defense mechanisms against burglars. Therefore, door security system is very much needed to enhance home security. Authentication is a key factor which helps for the identification of authorized people and helps in eradicating fraudulent activities, robberies, and many other social crimes. Facial recognition is the easiest way to unlock the door as one doesn’t need to make any physical efforts to open the door lock and just needs to look into the camera. The electromagnetic lock on the door will unlock if the image is present in the database. A security alert message in the form of an email is sent to the owner of the house in the case of an intruder. But there always lies a chance of spoofing of an authentic user to manipulate the recognition algorithm. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types of techniques used for liveness detection. This categorization helps understanding different spoof attacks scenarios and their relation to the developed solutions. A review of the works regarding face liveness detection works is presented which is done using a combination of Blinking analysis and Texture Analysis of any presented face in front of the camera.

Keywords- Home Automation, Facial recognition using AI, Liveness Detection, Local Binary patterns, Blinking Analysis, Face Recognition

Bioinformatics Lab

Motivated by the School of Computer and Information Sciences, University of Hyderabad and Centre for Cellular and Molecular Biology(CCMB), research was carried out in Pattern mining of Bio-informatics during doctoral research.

The three dimensional structure of a protein can be described by a network made from its constituent amino acids as the nodes, and their inter residue interactions as the links among the nodes. For the analysis, here the coarse grained protein contact network is generated from the structural data available in the PDB by considering only the C-alpha atoms as links. This distance map is a 2D symmetric, square matrix where the entry (i, j) represents the distance between the nodes i and j along the protein primary sequence chain from the N to C terminal. The contact map of the PCN is a Boolean matrix of pair-wise inter–residue contact networks.

The following problems were addressed: Protein fold recognition problem, 2D pattern extraction algorithms for sparse matrices, Protein secondary structure assignment, Association rule mining of signature for a protein fold, and Contact map overlap problem.

As part of this, the work was published in journals, patented and presented in various prestigious conferences and SIGKDD workshop at various countries as per the list given in outcome

Currently, Post Doctoral Research is going on AI Pattern modelling for cervical and breast cancer using protein sparse matrices at Artificial Intelligence Laboratory, Ton Duc Thang University, VIETNAM,  June 25, 2022.

International and National collaborative research is going on in this area. UGC Funded project was carried out under this lab entitled, Mining Alzheimer’s Disease Signal Transduction Modularity Drug Target Networks. Seed Grant from SAGTE to carry out the project entitled A Smart Retina Capturing System to Diagnosis Diabetic Retinopathy, in collaboration with Pinnamaneni Siddhartha Institute of Medical Sciences and Research Foundation and Sai Verna Eye Hospital.

Under Graduate  and Post Graduate students projects were guided. Ongoing projects are also there under this lab.