Beaulah David

@hicet.ac.in

Information technology/Associate professor
Hindusthan College of Engineering and Technology

Beaulah David


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https://researchid.co/drbeaulahdavid
Dr. Beaulah David is working as Associate Professor at Hindusthan College of Engineering and Technology, Coimbatore. She pursued her Doctorate in Department of Computer Science and Engineering at Karpagam Academy of Higher Education, Coimbatore and Bachelor degree in Computer hardware and Software Engineering from Avinashilingam Institute for Home Science & Higher Education for Women, Coimbatore and Master degree with a specialization of Network and Internet Engineering from Karunya Institute of Technology and Sciences, Coimbatore. She has gained more than a decade of experience in teaching from various colleges and her area of interest includes Data Sciences, Pervasive computing, Machine learning with Artificial Intelligence, Wireless Sensor Networks. She has published many patents and papers in refereed national journals and international journals.

EDUCATION

Ph.D
Karpagam University
2019

M.E
Karunya University
2006

B.E(CSE)
Avinashilingam Institute for Home Science and Higher Education for Women

RESEARCH INTERESTS

Mobile and Pervasive Computing, Blockchain Technology, Artificial Intelligence, MachineLearning
12

Scopus Publications

105

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • AX-YOLOV8-Based Indian Traffic Sign Detection and Classification in Autonomous Vehicles
    Vijay J. Antony, M. Mythily, Beaulah David
    Real Time Artificial Intelligence AI Key Motivations Technologies Platforms and Use Cases, 2026
    The field of autonomous vehicles has been rapidly developing in recent years, and deep learning technology has played an increasingly important role in this development. With the growing number of vehicles on roads, traffic sign recognition technology has become increasingly important in mitigating the risk of accidents. It is essential for autonomous vehicles to understand the environment and obey traffic rules and regulations in order to prevent accidents, and traffic sign recognition plays a key role in this process. In this chapter, we discuss traffic sign detection works by analyzing real-time video data from a camera mounted on the vehicle to detect road signs such as stop sign, speed limit signs, no entry sign, cautionary traffic signs, and informative traffic signs. To detect the traffic signs effectively, every traffic sign is scanned and pre-processed to 322extract key points using deep learning-based AX-YOLOv8 Algorithm. It generates dynamic anchor boxes around the traffic signs and non-maximum suppression technique produces confidence scores for each box, based on that traffic sign prediction is performed. AX-YOLOv8 is used to recognize the various sizes of traffic sign images more effectively and this feature works perfectly for removing noises as well as helps in dimensionality reduction by removing the less important features from the image. To classify the traffic sign, the CNN model acts as the backbone network of AX-YOLOv8 to predict the 43 classes of traffic sign images. This model is analyzed and compared with various deep learning algorithms, in which AX-YOLOv8 achieves the maximum precision of 98.9 and 99.2% in detection and classification for TRID, Indian traffic sign datasets. This system alerts about the road traffic signs to the driver before the driver reaches new roads. This greatly reduces drivers’ stress levels and helps them respond proactively to changes in the driving environment even when traveling on new roads.
  • SOULSYNC: An AI-Driven Emotional and Cognitive Support System for Alzheimer's Care
    Beaulah David, G Krishna, Shafna thasni K, Shreya S, Sona Krishna K
    Proceedings of 2nd International Conference on Multi Agent Systems for Collaborative Intelligence Icmsci 2026, 2026
    Alzheimer disease is a progressive disorder that affects memory, cognition, and emotional stability hence increasing care giver dependency and lowering the quality of life. The majority of available mobile health apps are based on the principle of reminders and schedule planning, without emotional and cognitive support. This paper suggests SOULSYNC, an AI-based mobile emotion assistant that would improve both cognitive and emotional health of patients with Alzheimer disease. The system operates offline-first architecture in which patient information such as reminders, mood data, memory content, and activity log are stored locally with the help of SQLite and updated with the cloud backend when the network connection is present. The analysis of emotion trends and routine patterns are applied to create individualized interventions including music therapy, cognitive games, and relaxing activities. A caregiver-related feature is a source of real-time notifications, emergency messages, and health-related information to maintain constant assistance. The flow application encompasses secure authentication, dashboardbased interaction, emotive tracking, cognitive interaction and intelligent feedback.
  • Graph Convolutional Network-Based Model for Attack Detection and Mitigation Technique in Wireless Sensor Networks
    Dorsela Venkata Rami Reddy, Meghna Sharma, Ashish Reddy Kumbham, Prasanthi Vallurupalli, Beaulah David, Saran Kumar A
    2025 3rd World Conference on Communication and Computing Wconf 2025, 2025
    To conduct monitoring tasks, WSN deploys several cost-effective sensor nodes with constrained resources in challenging environments. The utilisation of inexpensive, commercially available hardware, combined with the restricted processing capabilities, memory, and battery longevity of these nodes, renders them very vulnerable to various physical and malicious assaults. Consequently, it is imperative to tackle the issue of attack detection and mitigation in WSN. This research establishes a robust basis for enhancing WSN security via graph-based learning and refined preprocessing techniques. The initial step is to utilise an IPE. This process will integrate the data by Kalman filtering, normalise it via Min-Max scaling, and subsequently denoise it using Gaussian filtering. The most informative features are chosen for feature selection utilising the MI technique. Node categorisation is subsequently performed via a GCN model. The proposed model enhances resistance to malicious manipulation by substituting vector representations with concealed Gaussian distributions in each convolutional layer, distinguishing it from traditional GCNs. The experimental findings indicate that the enhanced GCN surpasses the leading methodologies, achieving a classification accuracy of 99.31%. The results indicate that the proposed strategy enhances the security of WSNs and provides a promising direction for research on detecting and mitigating assaults in WSN.
  • Digital Twin Application in Various Sectors
    Transforming Industry Using Digital Twin Technology, 2024
  • Dual interactive Wasserstein generative adversarial network optimised with remora optimisation algorithm-based lung disease detection using chest X-ray images
    Beaulah David, P. Mohamed Shameem, K. Ravikumar, G. Simi Margarat
    International Journal of Bio Inspired Computation, 2024
    Numerous prevailing approaches on lung disease identification are exploited with deep learning, but it does not precisely categorise the lung disease and correspondingly it takes high computation time. To engulf these complications, dual interactive Wasserstein generative adversarial network optimised with remora optimisation algorithm-based lung disease detection with chest X-ray images (DIWGAN-ROA-LDD-CXRI) is proposed for classifying COVID-19, normal and pneumonia lung diseases. Initially, the chest X-ray images are gathered via the dataset of chest X-ray (COVID-19 and pneumonia). The extracted features are given to DIWGAN-ROA for effectively categorise the chest X-ray image from COVID-19, normal and pneumonia. The proposed DIWGAN-ROA-LDD-CXRI approach is activated in Python. The performance of the proposed DIWGAN-ROA-LDD-CXRI approach attains 14.54%, 21.56%, 23.15% and 15.45% higher accuracy, 27.33%, 17.71%, 22.22% and 23.37% lower computation time and 21.11%, 28.89%, 29.95% and 28.14% higher AUC value compared with existing methods.
  • Deep Learning-Based Smart Healthcare System for Patient’s Discomfort Detection
    J. Antony Vijay, B. Gomathi, M. Mythily, Beaulah David
    Deep Learning for Smart Healthcare Trends Challenges and Applications, 2024
    Nowadays, deep learning has been extensively supported in various healthcare applications to detect diseases from the human body. It becomes so powerful when it is combined with other domains like deep learning and machine vision. The conventional methods of healthcare monitoring systems only contain smart wearables and vision-based methods that are limited to detecting only the specific issues from the human body. The proposed system gives a detailed summary and experiments on a deep learning-based non-invasive disease diagnosis approach in a smart healthcare system. The proposed system is processed into two steps: first, AX-YOLOV5 (Arbitrary Extra-Large You Only Look Once Version 5) algorithm is to detect the position of the patient in the video input, and next the AlphaPose Library is to detect 17 key points from the patient’s body, and their body movements are continuously captured by an IP camera. AX-YOLOV5 algorithm analyzes the real-time images from the video sequences to localize the position of the patient’s body. The key points are compared with the five most important key point coordinates of the human body using the rule of mining associations. These key points are used to identify the body position of a patient either lying on a bed or sitting. The temporal thresholding technique recognizes healthcare issues by how repeatedly the coordinates of the key points of the human body move in a certain period. Last, the distance of key points and the temporal threshold helps to categorize the diseases of the human organs. Moreover, the coordinates of the key points are accessed for identifying the correct disease from the human body. Based on the experimental results, the confusion matrix created by the proposed system reveals the accuracy is 99%.
  • OPTIMISING REAL-TIME MONITORING OF GAS-PHASE OXIDATION USING AI ALGORITHMS FOR AGROCHEMICAL INDUSTRIES
    Oxidation Communications, 2024
  • RETRACTION:Model transformation and code generation using a secure business process model
    M. Mythily, Beaulah David, R. Venkatesan, Iwin Thanakumar Joseph
    Journal of Intelligent and Fuzzy Systems, 2023
    Emerging daily, new devices and software-driven advancements pose challenges in software development, including errors, bugs, and evolving requirements. This leads to delays in delivery. Ensuring software security within the Software Development Life Cycle (SDLC) is crucial. To address this, the research focuses on incorporating security aspects early in the SDLC through model transformation. Platform-independent models with security attributes like Integrity, Privacy, Security Audit, non-repudiation, and authentication are generated. A template-based source code generator is utilized to create the structure of the source model. The Secure Business Process Model (SBPM) encompasses Unified Modeling Language (UML) artifacts, such as analysis level classes and sequence diagrams, enriched with security attributes derived from the activity model. Security requirements are linked to elements extracted from the source model, and structural codes with security-enabled members are produced. Automation in software development is inevitable, though not complete, as it plays a vital role in addressing these challenges and improving the security of software applications.
  • Map Building of Indoor Environment with Sensors using Neural Network
    S Angel Latha Mary, K. Ulagapriya, A Poonguzhali, R. Menaha, Beaulah David, T.R. Priyadharshini
    Winter Summit on Smart Computing and Networks Wisscon 2023, 2023
    The necessity of a blueprint of a building structure is a mandatory requirement for any reconnaissance or rescue operations. In our project, we build a modular system combining sensors related to sonar, laser, micro-wave to read sensory values and generate a 2D path of any building. The data is fetched and stored to feed to anOptimal Neural Network (ONN)-based computing system to create a 2D route with minimal discrepancies of error. Here the NN architecture is fine-tuned using Modified Dolphin Partner Optimization (MDPO) Exploration of unknown environments and space using autonomous vehicles has recently gained good attention in the field of Robotic Mapping. The recent advancements in the Internet of Things have enabled us to establish an ideal frame of reference for sonar and lidar-based systems. New effects are displayed by the sensors according to the physical characteristics of a room. The range data from sensors in various surroundings are interpreted by NNs. The distorted errors due to the material medium, particles, and moving objects present in the environment pose a threat to building a high-quality path map. The sensor fusion technique is applied to the rotatable modular array sensor to minimalize discrepancies caused by cloth materials during sonar readings, particle noise in an environment for Lidar reading, and moving human bodies present in the environment for path building and obstacle detection.
  • Prediction of Epidemic Disease Dynamics on the Infection Risk Using Machine Learning Algorithms
    Shanthi Palaniappan, Ragavi V, Beaulah David, Pathur Nisha S
    SN Computer Science, 2022
  • Fault tolerance and QoS based pervasive computing using Markov state transition model
    Beaulah David, Dr R. Santhosh
    International Journal of Engineering and Technology Uae, 2018
  • Performance analysis of QoS based model for wireless network communication
    Beaulah David, P. Raviraj
    2013 4th International Conference on Computing Communications and Networking Technologies Icccnt 2013, 2013

RECENT SCHOLAR PUBLICATIONS

  • SOULSYNC: An AI-Driven Emotional and Cognitive Support System for Alzheimer's Care
    B David, G Krishna
    2026 Second International Conference on Multi-Agent Systems for … , 2026
    2026
  • AX-YOLOV8-Based Indian Traffic Sign Detection and Classification in Autonomous Vehicles
    BD Vijay J. Antony, M. Mythily
    https://www.researchgate.net/publication/399043140_AX-YOLOV8 … , 2025
    2025
  • Graph Convolutional Network-Based Model for Attack Detection and Mitigation Technique in Wireless Sensor Networks
    DVR Reddy, M Sharma, AR Kumbham, P Vallurupalli, B David
    2025 3rd World Conference on Communication & Computing (WCONF), 1-6 , 2025
    2025
    Citations: 11
  • Digital Twin Application in Various Sectors
    BDJAV M. Mythily
    Transforming Industry using Digital Twin Technology,, pp. 219–237 , 2024
    2024
    Citations: 7
  • Dual interactive Wasserstein generative adversarial network optimised with remora optimisation algorithm-based lung disease detection using chest X-ray images
    B David, PM Shameem, K Ravikumar, GS Margarat
    International Journal of Bio-Inspired Computation (IJBIC) 23 (3), pp 189-201 , 2024
    2024
    Citations: 2
  • Optimising Real-Time Monitoring Of Gas-Phase Oxidation Using Ai Algorithms For Agrochemical Industries” Published paper in “Oxidation Communications
    A Poosapadi, D., Vanitha, G., Devi, S.R., Nalinashini, G., Beaulah David ...
    Oxidation Communications 47 (4), Pages 583-592 , 2024
    2024
    Citations: 44
  • Deep Learning-Based Smart Healthcare System for Patient’s Discomfort Detection
    BD Antony Vijay, Gomathi Babu, Mythily Ganesh
    Deep Learning for Smart Healthcare, pp.107-128 , 2024
    2024
  • Model Transformation and Code Generation Using a Secure Business Process Model
    AAE M Mythily, Arul Xavier VM, Beaulah David, K Martin Sagayam
    Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press,, 2023 … , 2023
    2023
    Citations: 2
  • Map Building of Indoor Environment with Sensors using Neural Network
    SAL Mary, K Ulagapriya, A Poonguzhali, R Menaha, B David, ...
    2023 Winter Summit on Smart Computing and Networks (WiSSCoN), 10.1109 … , 2023
    2023
  • Intelligent Energy-Aware Decision-Making At The Edge In Healthcare Using Fog Infrastructure
    TR Priyadharshini, B David, S Athira
    2023
  • Vision Based Drone Obstacle Avoidance by Deep Reinforcement Learning
    DNSRMSKMMMMAGSTMTRPDBDMDGMSSMAGDB Sathian
    IN Patent App. 202,241,013,930 , 2022
    2022
  • Analysis on 6G Networks Using AI Techniques in WSN to Improvise QoS
    G Vanitha, B David, SP Nisha, M Mythily, R Padmapriya, ...
    Handbook of Research on Design, Deployment, Automation, and Testing … , 2022
    2022
    Citations: 1
  • Prediction of epidemic disease dynamics on the infection risk using machine learning algorithms
    S Palaniappan, R V, B David, PN S
    SN computer science 3 (1), 47 , 2022
    2022
    Citations: 20
  • An automated emergency vehicle management system during road accidents using IoT
    DVSTDNVDDGSDSPNDBDPNSSN NAGARAJAN
    IN Patent App. 202,141,028,026 , 2021
    2021
  • REAL-TIME SMARTPHONE TRACKING APP OF VIRTUAL CLOUD SERVER BASED HEALTHCARE MONITORING SYSTEM FOR EMERGENCY SERVICE USING WBSN
    MRGMSSSMRGDMSDRSDKPDNRNDBDDMMMMMMRRDS Sudhakar
    IN Patent App. 202,141,033,362 , 2021
    2021
  • ONLINE MODEL ACCESS THROUGH USER DECISION AND SOCIAL NETWORK
    S PathurNisha, MB David, R Vijaya
    International Journal of Aquatic Science , 2021
    2021
  • Industrial Gas leakage system using GSM Technology
    DAK Arumugam Ranjith, Dr. Beaulah David, Dr. M. Sukanya, Ms. VANITHA.G, Dr ...
    IN Patent App. 202,141,043,269 , 2021
    2021
  • Automatic Battery Replacement of Home Surveillance Robot using WSN
    L Nithy, B David, K Sudha, C Sunil
    Int. J. Aquat. Sci 12, 671-676 , 2021
    2021
    Citations: 4
  • Face Detection Opencv Based ATM Security System
    DBD Priyadharshini R, Priyadharshini V, Vijeletchumi R
    International Journal of Scientific Research in Computer Science … , 2020
    2020
  • Fault Tolerance and QoS based Pervasive Computing using Markov State Transition Model
    DRS Ms.Beaulah David
    International Journal of Engineering & Technology (UAE) 7 (4), 2403-2409 , 2018
    2018
    Citations: 1

MOST CITED SCHOLAR PUBLICATIONS

  • Optimising Real-Time Monitoring Of Gas-Phase Oxidation Using Ai Algorithms For Agrochemical Industries” Published paper in “Oxidation Communications
    A Poosapadi, D., Vanitha, G., Devi, S.R., Nalinashini, G., Beaulah David ...
    Oxidation Communications 47 (4), Pages 583-592 , 2024
    2024
    Citations: 44
  • Prediction of epidemic disease dynamics on the infection risk using machine learning algorithms
    S Palaniappan, R V, B David, PN S
    SN computer science 3 (1), 47 , 2022
    2022
    Citations: 20
  • Graph Convolutional Network-Based Model for Attack Detection and Mitigation Technique in Wireless Sensor Networks
    DVR Reddy, M Sharma, AR Kumbham, P Vallurupalli, B David
    2025 3rd World Conference on Communication & Computing (WCONF), 1-6 , 2025
    2025
    Citations: 11
  • Digital Twin Application in Various Sectors
    BDJAV M. Mythily
    Transforming Industry using Digital Twin Technology,, pp. 219–237 , 2024
    2024
    Citations: 7
  • Hybrid Cryptography Algorithms for Enhanced Adaptive Acknowledgment Secure in MANET
    K Ramya, B David, H Shaheen
    IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN 16 (1), 2278-0661 , 2014
    2014
    Citations: 7
  • Automatic Battery Replacement of Home Surveillance Robot using WSN
    L Nithy, B David, K Sudha, C Sunil
    Int. J. Aquat. Sci 12, 671-676 , 2021
    2021
    Citations: 4
  • Dissemination of Link State Information for Enhancing Security in Mobile Ad Hoc Networks
    SH Chandrasekar P, BeaulahDavid
    IOSR Journal of Computer Engineering (IOSR - JCE) 16 (1), 24-31 , 2014
    2014
    Citations: 3
  • Performance analysis of QoS based model for wireless network communication
    DPR Beaulah David
    Computing, Communications and Networking Technologies (ICCCNT), 2013 Fourth … , 2013
    2013
    Citations: 3
  • Dual interactive Wasserstein generative adversarial network optimised with remora optimisation algorithm-based lung disease detection using chest X-ray images
    B David, PM Shameem, K Ravikumar, GS Margarat
    International Journal of Bio-Inspired Computation (IJBIC) 23 (3), pp 189-201 , 2024
    2024
    Citations: 2
  • Model Transformation and Code Generation Using a Secure Business Process Model
    AAE M Mythily, Arul Xavier VM, Beaulah David, K Martin Sagayam
    Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press,, 2023 … , 2023
    2023
    Citations: 2
  • Analysis on 6G Networks Using AI Techniques in WSN to Improvise QoS
    G Vanitha, B David, SP Nisha, M Mythily, R Padmapriya, ...
    Handbook of Research on Design, Deployment, Automation, and Testing … , 2022
    2022
    Citations: 1
  • Fault Tolerance and QoS based Pervasive Computing using Markov State Transition Model
    DRS Ms.Beaulah David
    International Journal of Engineering & Technology (UAE) 7 (4), 2403-2409 , 2018
    2018
    Citations: 1
  • SOULSYNC: An AI-Driven Emotional and Cognitive Support System for Alzheimer's Care
    B David, G Krishna
    2026 Second International Conference on Multi-Agent Systems for … , 2026
    2026
  • AX-YOLOV8-Based Indian Traffic Sign Detection and Classification in Autonomous Vehicles
    BD Vijay J. Antony, M. Mythily
    https://www.researchgate.net/publication/399043140_AX-YOLOV8 … , 2025
    2025
  • Deep Learning-Based Smart Healthcare System for Patient’s Discomfort Detection
    BD Antony Vijay, Gomathi Babu, Mythily Ganesh
    Deep Learning for Smart Healthcare, pp.107-128 , 2024
    2024
  • Map Building of Indoor Environment with Sensors using Neural Network
    SAL Mary, K Ulagapriya, A Poonguzhali, R Menaha, B David, ...
    2023 Winter Summit on Smart Computing and Networks (WiSSCoN), 10.1109 … , 2023
    2023
  • Intelligent Energy-Aware Decision-Making At The Edge In Healthcare Using Fog Infrastructure
    TR Priyadharshini, B David, S Athira
    2023
  • Vision Based Drone Obstacle Avoidance by Deep Reinforcement Learning
    DNSRMSKMMMMAGSTMTRPDBDMDGMSSMAGDB Sathian
    IN Patent App. 202,241,013,930 , 2022
    2022
  • An automated emergency vehicle management system during road accidents using IoT
    DVSTDNVDDGSDSPNDBDPNSSN NAGARAJAN
    IN Patent App. 202,141,028,026 , 2021
    2021
  • REAL-TIME SMARTPHONE TRACKING APP OF VIRTUAL CLOUD SERVER BASED HEALTHCARE MONITORING SYSTEM FOR EMERGENCY SERVICE USING WBSN
    MRGMSSSMRGDMSDRSDKPDNRNDBDDMMMMMMRRDS Sudhakar
    IN Patent App. 202,141,033,362 , 2021
    2021

Publications

P. Priya, K.Vani, V.Vivek, Beaulah David, “Reliable Communication with Dynamic Routing Topology Inference” , CIIT International Journal of Network & Communication, January 2011, Print: ISSN 0974 – 9713 & Online: ISSN 0974 – 9616, ( IMPACT FACTOR - 0.569)

Beaulah David, P.Raviraj, “Resource constrain Qos Based Clustering Model in Pervasive Computing” , European Journal of Scientific Research, ISSN 1450-216X / 1450-202X Vol. 100 No 3 May, 2013, – 486

Chandrasekar P, Beaulah David ,Shaheen H, Dissemination of Link State Information for Enhancing Security in Mobile Ad Hoc Networks, IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727Volume 16, Issue 1, Ver. VIII (Feb. 2014), PP 24-31

Ramya K, Beaulah David, Shaheen H, Hybrid Cryptography Algorithms for Enhanced Adaptive Acknowledgment Secure in MANET, IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p- ISSN: 2278-8727,Volume 16, Issue 1, (Feb. 2014), PP 32-36.

Akshara Premkumar, H. Shaheen, Beaulah David, R. Vijaya, “Blue Brain Technology”, Australian Journal of Basic and Applied Sciences, 9(15) Special 2015, Pages: 112-118.

Beaulah David, P.Raviraj, “Resource Oriented Pervasive Computing Via Qos-Cooperative Queueing Model” published in International Journal of Applied Engineering Research, ISSN 0973-4562 Vol. 10 (2015), pg 401 to 410, (SJR 0.12, Q3).

Deepica.K, Keerthana.S, Shifa Parveen.S, Silpa , Beaulah David, “Enhanced Collaborative Con

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

Title
:
AN AUTOMATED EMERGENCY VEHICLE MANAGEMENT SYSTEM DURING ROAD ACCIDENTS USING IOT


Application Number
:
202141028026


Date of filing
:
22/06/21


Published date
:
09/07/21




Title
:
REAL-TIME SMARTPHONE TRACKING APP OF VIRTUAL CLOUD SERVER BASED HEALTHCARE MONITORING SYSTEM FOR EMERGENCY SERVICE USING WBSN


Application Number
:
202141033362


Date of filing
:
25/07/2021


Published date
:
06/08/2021




Title
:
INDUSTRIAL GAS LEAKAGE SYSTEM USING GSM TECHNOLOGY


Application Number
:
202141043269


Date of filing
:
23/09/2021


Published date
:
01/10/2021




Title
:
VISION BASED DRONE OBSTACLE AVOIDANCE BY DEEP REINFORCEMENT LEARNING


Application Number
:
202241013930


Date of filing
:
15/03/2022


Published date
:
25/3/2022










Title
:
SYSTEM AND METHOD FOR AUTOMATIC MODEL TRANSFORMATION USING BEHAVIOR EXTRACTION


Application Number
:
202241022561


Date of filing
:
16/04/2022


Published date
:
06/05/2022