sravanthi gudikandula
@iare.ac.in
asst professor
Scopus Publications
- An Innovative and Resilient Deep Learning Approach for a Weather Invariant Traffic Sign Identification System in a Dynamic Setting
M. Naresh, P. Rashmitha, Arangi Sahithi, G. S. Sravanthi, S. Asha
Lecture Notes in Electrical Engineering, 2026 - Integrating Machine Learning Approaches to Detect Plant Diseases Through Crop Monitoring Using IOT Sensors and Live Image Captures
Ch. Sankar Rao, G. Sravanthi, G. ArchanaDevi, Y. Prathima, M. Jamuna Rani
Lecture Notes in Electrical Engineering, 2026 - Active Learning Pipelines for Efficient Annotation of Large-Scale IOT Video Streams
Kumaresh Sheelavant, Sanjay Kumar Suman, G Sravanthi, L. Bhagyalakshmi, J Jesintha Princy, D. Sravanthi
Proceedings of the 4th IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation Iatmsi 2026, 2026
Manual frame-level annotation for large-scale IoT video streams in Indian urban deployments imposes prohibitive cost and latency, undermining timely analytics for traffic management and incident response. This work presents an edgeaware active-learning pipeline that fuses epistemic uncertainty sampling with geometric/topological diversity through persistence-based summaries of short embedding windows and temporal-consistency regularizers. The pipeline is engineered for low-latency on-device operation and amortized topological computation. Evaluation uses an India urban traffic video corpus and a ResNet-18 / video-embedding backbone as a pragmatic baseline (ResNet-18 edge pipeline and dataset split reported in the reference). Empirically, the hybrid acquisition reduced annotation expenditure by <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\approx 40-60 \%$</tex> to reach operational F1/AUC comparable to full supervision, and with 50 % of labels achieved AUC up to 0.998 (marginally exceeding the baseline AUC <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\boldsymbol{\approx} \mathbf{0. 9 9 7}$</tex>) while preserving sub-second decision windows through model compression and batch amortization. The results indicate that topologically-aware, temporally-aware acquisition materially increases per-label utility and enables practical, privacy-preserving municipal rollouts that minimize human-in-the-loop burden. - Development of machine learning methods on crop prediction analysis for plant disease identification and soil fertility
Jonnadula Narasimharao, Vadla Pradeep Kumar, Sinde Jayavanth Rao, Gasi Lakshmi Praveena, Obu Venkatesh Yadav, Grandhamala Sravanthi
Aip Conference Proceedings, 2025 - A Feature Extraction Method for Deep Learning and HDR Image Reconstruction Optimization
Vankudothu Malsoru, Najeema Afrin, Madhavi Pingili, G. S. Sravanthi, B. Sujani, R. Suhasini
Lecture Notes in Networks and Systems, 2025 - A Novel Approach of Enhancing and Developing IDS to Use Ml for Analyzing Malicious Attacks
Madhavi Pingili, G. S. Sravanthi, K. Srujan Raju, V. Rajesh, A. Deepika, Punyaban Patel
Smart Innovation Systems and Technologies, 2025 - Ethical AI for Data Governance: A Fairness-Centric Approach to Responsible Decision-Making in Enterprise Systems
G. Sravanthi, G Karuna, S.Selvi, Hassan Mohamed, S. Jenifer, Karthikeyan V
2025 International Conference on Metaverse and Current Trends in Computing Icmctc 2025, 2025
Ethical AI driven data governance is important such that the decisions in enterprise systems are responsible. Typically, traditional governance models cannot ensure fairness, and transparency and mitigate possible bias issues existently, and result in unintended discrimination and regulatory risks. In this paper, we propose FAIR-Gov AI which is the first novel fairness-centric AI governance framework that consists of Autonomous Fairness Monitoring & Correction (AFMC), Ethical Data Ledger powered by Blockchain (BDL), Fairness Reinforcement Learning (FRL) Engine, Federated Fairness Learning (FFL), and the Ethical Digital Twin Simulation for enforcing real time fairness optimization as well as regulatory compliance. Using a combination of equity auditability and bias mitigation by FAIR-Gov AI reinforcing learning and blockchain auditability with tamper proof decision logs, we have developed. With federated learning, data protection is maintained, while pipes are cut to mediocrity; digital twin simulations let enterprises see how a decision works before their lives. Results show that these new governance models significantly better in the areas of fairness, transparency and accountability compared to the common governance models. It can be used nationwide in finance, healthcare and smart cities, while keeping the AI systems in line with the stakeholders’ expectations and legal standards. In the realm of growing ethical AI and assure data governance field, this research presents a scalable and adjustable mechanism to prevent the biased AI in actual enterprise environment. Future work focused on adversarial robustness with more challenging threats of future deployment and cross-jurisdictional alignment of regulations to enhance synergies for data dissemination between providers. - A Novel Investigation on Employing Deep Learning Techniques for Vehicle Monitoring and Identification in Real-Time Analysis
A. Srinivasula Reddy, G. S. Sravanthi, R. Lavanya, B. K. Bhagyashree, S. Kirubakaran, G. Saidulu
Smart Innovation Systems and Technologies, 2025 - Optimizing Security for Cloud Computing Network Outsourcing Through the Implementation of Mobile Devices and Cryptography Model
Sandhyarani, Bejjanki Pooja, Vivekanand Aelgani, G. Ravi Kumar, Madhavi Pingili, G. S. Sravanthi
Lecture Notes in Networks and Systems, 2025 - Sarcasm Detection of Feature Augmentation Using Multi-objective Genetic Algorithm
Edem Suresh Babu, G. S. Sravanthi, V. Harshavardhan, Mahesh Kotha, M. Shiva Kumar, Sana Afreen
Smart Innovation Systems and Technologies, 2025 - Neural Network Model for Enhancing the Crop Productivity and Effective Fertilizers
K. Srujan Raju, Mahesh Kotha, Lal Bahadur Pandey, G. S. Sravanthi, P. Sravanthi, Borra Sivaiah
Lecture Notes in Networks and Systems, 2025 - A novel technique on Revolutionizing E-Learning with Region-Based Convolutional Neural Networks
C R Shruthi Reddy, N.Venkatasiva Reddy, S. Kirubakaran, G S Sravanthi, R.Sowndharya, D.A.Poongodi
Icrteect 2025 2nd International Conference on Recent Trends in Electrical Electronics and Computing Technologies, 2025 - Adaptive AI Systems for Real- Time Vital Sign Monitoring
Nitin N. Jadhav, Deepak Suresh Asudani, P. A. Deshkar, Gandloju Sravanthi, Patil Dipesh Madhukar Monika, Netaji Gangaram Achwalkar
2025 International Conference on Next Generation of Green Information and Emerging Technologies Giet 2025, 2025 - Deep Learning-Based Intrusion Detection System with Comparative Analysis
M. Shiva Kumar, D. Narsimha Reddy, S. Rao Chintalapudi, M. Sunitha, Edem Suresh Babu, G. S. Sravanthi
Lecture Notes in Networks and Systems, 2025 - Assessment of Early-Stage Alzheimer’s Disease Identification by Employing Support Vector Machine and Random Forest Classifier Techniques
Mahesh V. Sonth, S. V. Suji Aparna, Madhavi Pingili, G. S. Sravanthi, E. N. V. Purna Chandra Rao, S. Krishnaveni
Lecture Notes in Networks and Systems, 2025 - Study on Enhanced Transfer Characteristic in Heat Exchanger Tubes with Low Fins
V Naveenprabhu, K veeramanikandan, S Ragu, S Hariharan, Grandhamala Sravanthi
Journal of Physics Conference Series, 2024 - Implementation of Artificial Intelligence in Medical Electronic Communication Technology
Gurram Sravanthi, Chinthapula Vinay Kumar, Bandi Sampoorna, Ryakam Lavanya, Mulakala Sirin Kumari, Mohammed Imtyaz Ahmed
2024 2nd International Conference Computational and Characterization Techniques in Engineering and Sciences Ic3tes 2024, 2024 - Experimental and analytical investigation on natural composite materials
K. Arunkumar, G. Sravanthi, A. Udaya Deepika, M. Srikanth
Aip Conference Proceedings, 2023 - Optimization of UAV by using tubercles wing configuration
K. Arunkumar, G. Sravanthi, A. Udaya Deepika, M. Srikanth
Aip Conference Proceedings, 2023 - Similitude analysis and model fabrication of aeriel hoverboard
K. Veeranjaneyulu, Vivek Gnan Veer Kura, Kalavagunta Surya Kiran, G. Sravanthi, A. Udaya Deepika
Aip Conference Proceedings, 2023 - Drilling parameters optimization of AA2218 based metal matrix composites by using Taguchi method
Madheswaran Subramaniyan, Prakash Eswaran, Anandha Moorthy Appusamy, M. Poovendrakumar, V. R. Pranesh, K. Sabarish, G. Sravanthi
Aip Conference Proceedings, 2023 - Analysis of supercavitation on 2D and 3D disk cavitator
K. Veeranjaneyulu, N. Sandesh Reddy, P. Sudhakar, A. Rishwanth, K. Akhileshwar Rao, G. Sravanthi, A. Udaya Deepika
Aip Conference Proceedings, 2023 - Detecting Fake News on Twitter by Using Artificial Intelligence
R. Suhasini, B. Ratnamala, Gurram Sravanthi, K. Prasanna Kumari, Subba Rao Polamuri
2023 3rd International Conference on Advancement in Electronics and Communication Engineering Aece 2023, 2023 - Design and Fabrication of Semi-Automatic Child Retraction Mechanism from Bore Well
K. Arunkumar, T. Kumaran, G. Sravanthi, R. Vijayanandh
Aip Conference Proceedings, 2022 - Static Analysis of Conventional Aircraft Fuselage with Different Materials
K. Veeranjaneyulu, G. Sravanthi, K. Surya Kiran, K. Khushal, G. Raj Kumar
Aip Conference Proceedings, 2022 - Elastic Flexural Buckling of Thin Walled Zig-Zag Flanged Section
D. Mahesh Kumar, N. Madhavi, N. Uday Ranjan Goud, G. Sravanthi, R. Kannan
Aip Conference Proceedings, 2022 - Stress analysis of corrugated plate fuselage under different loading conditions
K. Veeranjaneyulu, G. Sravanthi, Sudhir kumar Chaturvedi, Sudhir Joshi, Kalavagunta Surya Kiran
Materials Today Proceedings, 2022
