Drug Recommendation System in General Medical Emergencies Vaibhavi Shivanna, Silpa Chalichalamala, V Jyothsna, Bhasha Pydala, T Pavan Kumar, K Srilakshmi 2025 IEEE 5th International Conference on ICT in Business Industry and Government Ictbig 2025, 2025 During medical emergencies, quick and accurate drug recommendations are essential when doctors are not available. The proposed system is intended to develop a Drug Recommendation System (DRS) in the field of data science using machine learning techniques that can help in making faster decisions. The system processes patients' symptoms and medical history in real time using predictive analytics to provide individual medication recommendations for treating patients. This offers real-time, secure, and personalized care, improving response time and accuracy in acute situations and assessing the system's performance and user satisfaction through user feedback.
Enhanced SMS Spam Detection Using Boost Light Approach Bhasha Pydala, K. K. Baseer, K V Siva Reddy, K Krushna Harshi, Ganne Hemanth, M Thejomsri 2025 International Conference on Computing Technologies Icoct 2025, 2025 Mobile Telecom subscriber’s are interrupted by these spams and it becomes necessary for the service providers to take steps to protect the user. In this project, we aim toward developing an end to end SMS spam detection model using different ML algorithms available in today’s day and age. Instead, it provides latest algorithms used in group such as CatBoost, LightGBM and XGBoost to enumerate text. Using these algorithms, the system is able to very accurately classify an SMS message as spam or not. In this project each of the algorithms are tested and they are compared based on some of the key metrics (accuracy, precision, recall and F1 score). Since there is a need to apply the textual pre processing methods like TF-IDF and bag of words methods in order for the model to learn the appropriate underlying on sms message content. For this spam sms classification issue, in this project, we will attempt to make a decision for what will be the most appropriate choice for a scalable solution for the spam problem. Therefore, this will help with their security and give them a quick means to organize their communication with this approach rather than through other systems form of spam filtration.
An Enhancing Comprehensive Machine Learning Framework for DDoS Defense Through Leveraging Multiple Algorithms Bhasha Pydala, Dinasekhar Govardhan, Chapalamadugu Venkatesh, Kornepalli Lokeshwar Goud, Kavadi Dinesh, V. Jyothsna 2024 IEEE International Conference on Information Technology Electronics and Intelligent Communication Systems Iciteics 2024, 2024 Addressing Distributed Denial of Service (DDoS) attacks involves leveraging organizational assets, particularly the website framework. Departing from prior studies relying on an outdated KDD dataset, the paper emphasizes the importance of using the latest data for a comprehensive understanding of the current DDoS landscape. Utilizing machine learning techniques, including Random Forest, k-Nearest Neighbors (KNN), Support Vector Machine (SVM), Gaussian, and Naive Bayes classification algorithms, the study introduces an amalgamated model for classifying and predicting DDoS attack types. The DDoS attack network logs dataset from GitHub and Python as a simulator were utilized. Model performance evaluation involved generating confusion matrices. In the first classification using Random Forest, Precision (PR) and Recall (RE) both reached high values, yielding an average Accuracy (AC) in a satisfactory range (81% to 90%). In the second classification, PR and RE both attained notable values, resulting in an average AC within an acceptable range. The innovation lies in the construction of an integrated model that combines Random Forest, KNN, SVM, Gaussian, and Naive Bayes to enhance overall predictive performance. Notably, a significant improvement in defect determination accuracy was observed when compared to existing research. This underscores the effectiveness of the integrated model in addressing the dynamic landscape of DDoS attacks.
Applying AWS and the Kafka Framework for Real-Time Weather Data Analysis International Journal of Intelligent Systems and Applications in Engineering, 2024
YOLOv8-Based Person Detection, Distance Monitoring, Speech Alerts, and Weapon Identification with Email Notifications V. Jyothsna, Chamundi Alle, Ragavendra Kurnutala, Ganesh K N, KushalKarthik K R, Bhasha Pydala Proceedings 2024 International Conference on Expert Clouds and Applications Icoeca 2024, 2024 An advanced security system utilizing the YOLOv8 algorithm for comprehensive object detection enables real-time identification of individuals and weapons. Innovative features include precise distance estimation and email alerts upon weapon detection, enhancing communication during security breaches. Rigorous testing ensures reliability, while ethical considerations ensure adherence to standards. This project represents a significant contribution to automated threat detection and response, exemplifying advancements in security technology within ethical boundaries, effectively addressing contemporary challenges. The integration of YOLOv8 for object, person, and weapon detection in audio, alongside distance estimation and email notification, marks a substantial leap in security surveillance technology, offering swift threat detection and coordinated response capabilities. Rigorous validation confirms its efficacy, promising to fortify security protocols and proactive threat mitigation strategies, thereby paving the way for further advancements in audio-based threat detection systems.
Relative Positioning of Autonomous Ground Vehicles Combining Multi-GNSS (GPS-L1, GLONASS-G1 and BDS-B1) Observations International Journal of Intelligent Systems and Applications in Engineering, 2024
Deep Learning Model for Intrusion Detection in SDN Networks V. Jyothsna, E. Sandhya, Thammisetty Swetha, P. Lokesh Kumar Reddy, B. Jyothsna, P. Bhasha 2023 1st International Conference on Optimization Techniques for Learning Icotl 2023 Proceedings, 2023
Prediction of Dynamic Churn using Azure and Machine Learning P. Bhasha, R. Vishnuvardhan Reddy, P. Hamsaveni, P. Hema Sravani, N. Devakee Nandan, P. Samhitha Vitecon 2023 2nd IEEE International Conference on Vision Towards Emerging Trends in Communication and Networking Technologies Proceedings, 2023
Intrusion Detection System for IoT Networks V. Jyothsna, E. Sandhya, R. Roopa, B. Deena Divya Nayomi, D. K. Shareef, P. Bhasha 2023 1st International Conference on Optimization Techniques for Learning Icotl 2023 Proceedings, 2023
Photos: 3rd International Conference on “Data Analytics, Smart Computing and Networks” R Kasarapu, J Veeramreddy, B Pydala AIP Conference Proceedings 3371 (1), 010002 , 2026 2026
Smart vehicle control system for safe and efficient driving P Bhasha, Y Kohitha, PM Chowdary, MN Krishna, N Akash, NV Kaushik AIP Conference Proceedings 3371 (1), 020018 , 2026 2026
LoRa-based disaster response network for emergency communication B Pydala, P Challa, DS Dinesh, JP Reddy, CB Reddy, KK Baseer AIP Conference Proceedings 3371 (1), 040019 , 2026 2026
Aqua detect: A YOLO-based enhanced model for marine fish detection B Pydala, CR Bhumireddy, PS Lanka, PS Kolli, MK Bobba, TP Kumar AIP Conference Proceedings 3371 (1), 040017 , 2026 2026
Real-time traffic optimization using reinforcement learning-based adaptive traffic light control P Bhasha, P Nandini, UV Kumar, VSM Moulana, R Dharmik, TP Kumar AIP Conference Proceedings 3371 (1), 020012 , 2026 2026
Analyzing and comparing the performance of ML algorithms using bankruptcy dataset E Sandhya, C Silpa, CR Mohan, K Nirmala, NK Kumar, B Pydala AIP Conference Proceedings 3371 (1), 040002 , 2026 2026
Smart traffic management system through anomaly detection and load balancing using YOLOv5 and MobileNet B Pydala, A Begum, H Epparla, KR Chavan, V Thaluchuri, SB Jugunta AIP Conference Proceedings 3371 (1), 020005 , 2026 2026
Preface: 3rd International Conference on “Data Analytics, Smart Computing and Networks” R Kasarapu, J Veeramreddy, B Pydala AIP Conference Proceedings 3371 (1), 010001 , 2026 2026
Intelligent embedded vision for object abandonment detection through YOLOv8 P Bhasha, AH Arun, A Sushmita, GG Achyuth, H Pavan, GV Kishore AIP Conference Proceedings 3371 (1), 040008 , 2026 2026
Garbage classifier through AlexNet architecture P Bhasha, SK Sameera, PC Raj, PSK Reddy, T Ujwal, MY Noor AIP Conference Proceedings 3371 (1), 030005 , 2026 2026
Air Pollution Surveillance System With Automated Server-Based Notifications PK ES, RM Chinnem, P Modukuru, B Pydala 2026 IEEE International Conference on Emerging Computing and Intelligent … , 2026 2026
Drug Recommendation System in General Medical Emergencies V Shivanna, S Chalichalamala, V Jyothsna, B Pydala, TP Kumar, ... 2025 IEEE 5th International Conference on ICT in Business Industry … , 2025 2025
Enhanced SMS Spam Detection Using Boost Light Approach B Pydala, KK Baseer, KVS Reddy, KK Harshi, G Hemanth, M Thejomsri 2025 International Conference on Computing Technologies (ICOCT), 1-7 , 2025 2025
AI-Driven Threat Detection in Cloud Environments V Jyothsna, E Sandhya, KB Kamalapuram, P Bhasha Convergence of Cybersecurity and Cloud Computing, 261-284 , 2025 2025 Citations: 11
Visual data analysis and inference through dimensionality reduction techniques V Jyothsna, E Sandhya, P Bhasha, NN Swetha, TSD Sree Interactive and Dynamic Dashboard, 21-68 , 2024 2024
Enhancing anomaly detection: A comprehensive approach with MTBO feature selection and TVETBO-Optimized-Optimized Quad-LSTM classification NV Reddy, R Sekhar, NS Divya, B Jagadesh, R Gandikota, KK Lella, ... COMPUTERS & ELECTRICAL ENGINEERING 119 , 2024 2024
Enhancing anomaly detection: a comprehensive approach with MTBO feature selection and TVETBOOptimized Quad-LSTM classification RSR NV, N SreeDivya, BN Jagadesh, R Gandikota, KK Lella, B Pydala, ... Computers and Electrical Engineering 119, 109536 , 2024 2024 Citations: 34
A Smart Stick for Visually Impaired Individuals through AIoT Integration with Power Enhancement B Pydala, MK Reddy, T Swetha, V Ramavath, P Siddartha, VS Kumar International Conference on Computational Innovations and Emerging Trends … , 2024 2024 Citations: 3
Hybrid deep learning model for detecting DDoS attacks in IoT networks J Veeramreddy, CKR Vardhireddy, H Thangella, K Sarangula, ... International Conference on Computational Innovations and Emerging Trends … , 2024 2024 Citations: 8
Detecting ransomware threats in disk storage through behavioral analysis using CNN2D and flask framework B Pydala, A Sireesha, PT Rao, S Veluru, RSC Reddy, V Jyothsna International Conference on Computational Innovations and Emerging Trends … , 2024 2024 Citations: 6
MOST CITED SCHOLAR PUBLICATIONS
Smart_Eye: a navigation and obstacle detection for visually impaired people through smart app B Pydala, TP Kumar, KK Baseer Journal of Applied Engineering and Technological Science (JAETS) 4 (2), 992-1011 , 2023 2023.0 Citations: 77
VisiSense: a comprehensive IOT-based assistive technology system for enhanced navigation support for the visually impaired B Pydala, TP Kumar, KK Baseer Scalable Computing: Practice and Experience 25 (2), 1134-1151 , 2024 2024.0 Citations: 36
Enhancing anomaly detection: a comprehensive approach with MTBO feature selection and TVETBOOptimized Quad-LSTM classification RSR NV, N SreeDivya, BN Jagadesh, R Gandikota, KK Lella, B Pydala, ... Computers and Electrical Engineering 119, 109536 , 2024 2024.0 Citations: 34
Blockfog: A blockchain-based framework for intrusion defense in iot fog computing VG Prasuna, BR Babu, B Pydala Scalable Computing: Practice and Experience 25 (3), 1950-1962 , 2024 2024.0 Citations: 30
A Simple and Effective Electronic Stick to Detect Obstacles for Visually Impaired People through Sensor Technology DKKB P. Bhasha, Dr. T. Pavan Kumar Journal of Advanced Research in Dynamical and Control Systems 12 (Issue-06 … , 2020 2020.0 Citations: 30
An IoT-Based BLYNK Server Application for Infant Monitoring Alert System to Detect Crying and Wetness of a Baby JV Bhasha P., Pavan Kumar T., Baseer K.K. Springer, Singapore 1312 , 2021 2021.0 Citations: 24
Automated Crop Yield Prediction System Using Machine Learning Algorithm SKS P Bhasha, Dr. J Suresh Babu, Muniraju Naidu Vadlamudi, Kochumol Abraham Citations: 19
YOLOv8-based person detection, distance monitoring, speech alerts, and weapon identification with email notifications V Jyothsna, C Alle, R Kurnutala, G KN, KK KR, B Pydala 2024 International Conference on Expert Clouds and Applications (ICOECA … , 2024 2024.0 Citations: 14
Deep learning model for intrusion detection in sdn networks V Jyothsna, E Sandhya, T Swetha, PLK Reddy, B Jyothsna, P Bhasha 2023 1st International Conference on Optimization Techniques for Learning … , 2023 2023.0 Citations: 13
AI-Driven Threat Detection in Cloud Environments V Jyothsna, E Sandhya, KB Kamalapuram, P Bhasha Convergence of Cybersecurity and Cloud Computing, 261-284 , 2025 2025.0 Citations: 11
Hybrid deep learning model for detecting DDoS attacks in IoT networks J Veeramreddy, CKR Vardhireddy, H Thangella, K Sarangula, ... International Conference on Computational Innovations and Emerging Trends … , 2024 2024.0 Citations: 8
Advancing android security: leveraging stacking ensemble and bioinspired feature selection for efficient malware detection V Jyothsna, P Mokshitha, S Khulud, LGP Reddy, NJ Reddy, B Pydala 2024 5th International Conference for Emerging Technology (INCET), 1-11 , 2024 2024.0 Citations: 7
Detecting ransomware threats in disk storage through behavioral analysis using CNN2D and flask framework B Pydala, A Sireesha, PT Rao, S Veluru, RSC Reddy, V Jyothsna International Conference on Computational Innovations and Emerging Trends … , 2024 2024.0 Citations: 6
An Enhancing Comprehensive Machine Learning Framework for DDoS Defense Through Leveraging Multiple Algorithms B Pydala, D Govardhan, C Venkatesh, KL Goud, K Dinesh, V Jyothsna 2024 IEEE International Conference on Information Technology, Electronics … , 2024 2024.0 Citations: 6
Intrusion Detection using HRO with Ensemble Learning Models and Comparison B Pydala, NPR Reddy, CR Mohan, E Sandhya, V Jyothsna, KK Baseer 2023 1st International Conference on Optimization Techniques for Learning … , 2023 2023.0 Citations: 6
Enhancing Remote Sensing Object Detection Through YOLOV5x6 Model B Pydala, BV Bhavana, G Gamyasree, K Jyotsna, M Lohitha, V Jyothsna 2024 2nd World Conference on Communication & Computing (WCONF), 1-7 , 2024 2024.0 Citations: 5
Intrusion Detection System for IoT Networks V Jyothsna, E Sandhya, R Roopa, BDD Nayomi, DK Shareef, P Bhasha 2023 1st International Conference on Optimization Techniques for Learning … , 2023 2023.0 Citations: 5
Retracted: Classification of Brain Disease & MRI-Based Age Estimation Using Deep Learning Algorithms S Kamakshi, P Penchalaiah, P Bhasha 2023 International conference on intelligent systems for communication, IoT … , 2023 2023.0 Citations: 5
A Smart Stick for Visually Impaired Individuals through AIoT Integration with Power Enhancement B Pydala, MK Reddy, T Swetha, V Ramavath, P Siddartha, VS Kumar International Conference on Computational Innovations and Emerging Trends … , 2024 2024.0 Citations: 3
Machine Learning Applications in Predictive Pest Modeling for Developing Pest-Resistant Crop Varieties KK Baseer, MJ Pasha, G Ramu, B Pydala, DW Albert Revolutionizing Pest Management for Sustainable Agriculture, 381-410 , 2024 2024.0 Citations: 3
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