P.M.S.S.CHANDU

@sietk.org

PROFESSOR AND CSE DEPARTMENT
SIDDHARTH INSTITUTE OF ENGINEERING & TECHNOLOGY

P.M.S.S.CHANDU


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https://researchid.co/chandupmss
Accomplished career as professor in Department of Computer Science and Engineering nearly 14 years of experience at UG and PG level

EDUCATION

PhD Computer science and Engineering from sathyabama university,Chennai
M.E Computer science and Engineering from sathyabama university,Chennai
B.E Computer science and Engineering From SCSVMV ,Kanchipuram,Tamil nadu

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Science, Software, Information Systems
22

Scopus Publications

29

Scholar Citations

3

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • A Machine Learning Framework for Forecasting Flood Severity through the Integration of Reservoir Metrics and Real-Time Meteorological Data
    P. M. S. S. Chandu, Abbu Gunasekhar, R. E. Durai, T. Hemanadhan, T. Durgaprasad, A. P. Dillikumar
    Proceedings of the 2026 International Conference on AI Driven Smart Systems and Ubiquitous Computing Icauc 2026, 2026
    This work integrates reservoir metrics with real-time meteorological information and develops a framework for forecasting flood severity. It predicts water levels using multi-year hydrological and real-time meteorological data. The daily water level storage dataset from Central Water Commission (CWC) for Nagarjuna Sagar dam and weather parameters such as rainfall and temperature are obtained from Open-Meteo API archive. These data are transformed into useful predictors such as lagged levels, cumulative rainfall indices, seasonal indicators, and changes in water storage levels. Multiple regression algorithms, such as Random Forest (RF), Extreme Gradient Boosting (XGBoost), Gradient Boosting Regressor (GBR), and Multiple Linear Regression (MLR), are trained to predict next-day water levels. Their performance is evaluated on a time-ordered dataset using regression error metrics such as Mean Absolute Error (MAE) and Coefficient of Determination (R<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup>). Results show that linear and tree-based models achieve a predictive skill exceeding 0.97, outperforming complex deep-learning models for this dataset. The predictive levels are then used to map them to risk bands based on reservoir safety thresholds, providing a practical framework that can be deployed in real-time to continuously monitor floods and provide timely alerts to downstream communities.
  • A Dual-Stage Framework for Brain Tumor Detection Using MRI Image Enhancement and Deep Learning Classification
    G Indiravathi, P.M.S.S. Chandu, K Bhagavathi, Albert Apsara, K Thriveni, P Jaya Prakash
    2026 International Conference on Recent Advances in Electrical Electronics Ubiquitous Communication and Computational Intelligence Raeeucci 2026, 2026
    Magnetic resonance imaging (MRI) plays a significant role in the diagnosis and planning of treatments for brain tumors. The analysis of MRI scans is subject to inter-observer variability, and the manual techniques used for this purpose are extremely time-consuming, thus making it mandatory for the reliable techniques to take over this process. In this work, a lightweight twomodule end-to-end deep learning pipeline for the detection of brain tumors, along with an image enhancement, segmentation, and classification of tumors in a single pipeline, is proposed. The suggested system will employ a u-shaped convolutional neural network that will be capable of correctly demarcating the tumor characteristics allowing the precise localization of the tissues using efficient and very small deep learning models like MobileNet and DenseNet, and large ones on the MRI of the brain scans.
  • Systematic Access for Layer 7 Attacks and Mitigation
    V. Ramakrishna, P. M. S. S. Chandu, S. Vaithyasubramanian, Y. Immanuel
    Lecture Notes in Networks and Systems, 2025
  • Utilizing Machine Learning Methods to Forecast Passenger Safety in Smart Urban Transportation Systems
    P. M. S. S. Chandu, S. Vaithyasubramanian, R. Sundararajan, P. Vaidhyanathan, V. Thamarai Selvi
    Sustainable Civil Infrastructures, 2025
  • Implementation of a Secure E-Coupon Approach Using Ethereum Blockchain Technology
    P.M.S.S. Chandu, M. Giri, M. Kusuma, Murugesh Kusuma, Shaik Hafizur Rahaman, S. Dhanush
    Proceedings of the International Conference on Electrical Electronics and Computer Science with Advance Power Technologies A Future Trends Ice2cpt 2025, 2025
  • Detecting Patient Condition by Cluster-Boosted Regression with Text-Based Indexing
    Kavitha Esther Rajakumari, P. M. S. S. Chandu, S. Vaithyasubramanian, Y. Immanuel, D. V. N. R. Mohitananda Sanjay
    Lecture Notes in Networks and Systems, 2024
  • Recognition and Analysis of Bone Impairment Using Machine Learning
    P. M. S. S. Chandu, R. S. Subhasree, Y. DurgaPrasanna, T V. Jayasree, P. Kusuma Sri, K. HarshaVardhan
    Proceeding of 2024 International Conference on Communication Computing and Energy Efficient Technologies I3ceet 2024, 2024
    Manual understanding of the x-beams can at times make it hard to decide if it is cracked or not. These x-beams give an unmistakable image of the harm, yet the essential issue is that a few specialists neglect to recognize the minor cracks that could later reason huge damage to the patient. Model that obviously examinations and sorts photographs of breaks to the hand, leg. There are various elective strategies for detecting these breaks, and this examination was molded by different man-made intelligence devices that pre-owned AI and profound learning techniques. As it is a purposeful system of picture investigation calculation to figure in the event that the bone is broken or typical, this examination unequivocally concentrates on a few models relying upon convolutional brain organizations.The field of life science and its dependence on innovation are growing every-day. Elective devices and PC helped medication have fundamentally diminished the tedious and difficult manual conclusion processes. Notwithstanding, the cycle for deciding a bone crack diagnosing actually utilizes manual survey methods. The method utilizes XRAYS to make a halfway XRAY picture of the broke region, which is then physically looked into by the specialists to decide the sort and area of the break. The old cycle isn't just tedious, yet in addition tedious and could bring about mistaken analysis because of human blunder. To decide and sort the exact sort of crack, precise arrangement requires broad experience. Bone break identification and arrangement in XRAY pictures exploitation AI is put out in this examination. The XRAY pictures are taken care of into a brain network model that has been prepared on a sizable training dataset comparing to different kinds of cracks. To work on the arrangement and recognizable proof of bone cracks utilizing dynamic idea, instructing information and information settings have been tweaked. Python is utilized to make a product framework that can import the picture to be recognized and supply the model with unique thoughts regarding the crack. Using similar picture informational index and differentiating CNN and SVM models.
  • IoT-Enabled Smart Parking System using Machine Learning for Real-Time Parking Prediction
    A. Suresh, P.M.S.S. Chandu, S. Subhash Chandra Bose, V. Dhamini, P. Adi Narayana, K. Dilli Balaji
    4th IEEE International Conference on Mobile Networks and Wireless Communications Icmnwc 2024, 2024
    Because of the growing number of cars and the inadequate parking infrastructure, urban parking management has become more and more crucial. To predict parking spot availability in IoT-enabled intelligent systems, this study assesses the performance of many machine learning (ML) models, including decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and extra trees classifier (ETC). F-score, accuracy, recall, and precision were used to gauge performance. The DT model's 88.63% accuracy and 87.61% F-score demonstrated its low predictive power. With an F-score of 91.45% and greater accuracy of 92.30%, RF proved appropriate for medium-sized facilities. XGBoost performed better, capturing intricate parking patterns with 93.87% accuracy and 93.50% F-score. With 93.00% accuracy and 92.74% F-score, ETC performed similarly to XGBoost and provided computational advantages for big datasets. ETC and RF are dependable in medium-sized settings, however XGBoost is advised for large-scale settings.
  • Peer to Peer Information Inter-Change and Network Coding to Improve Transmission Efficiency in Wireless Mesh Network
    Rama Krishna Vanakamamidi, Chandu P.M.S.S, D. David Neels Ponkumar, R. Senkamalavalli
    Proceedings of the 2023 2nd International Conference on Augmented Intelligence and Sustainable Systems Icaiss 2023, 2023
    Wireless Mesh Networks (WMNs) have been widely used in various industries, including industrial control, environmental monitoring, and military operations. The performance of WMNs may be improved with the help of an exciting new technique called network coding (NC). In particular, NC is appropriate for WMN since the energy supply to the fixed backbone of WMNs is often limitless. However, coding collision is a serious issue that negatively impacts the performance of the network. To solve these issues, Peer to Peer (P2P) Information inter-change and Network Coding (PINC) to improve transmission efficiency in WMN is proposed. The objective of this paper is to enhance transmission efficiency and minimize delay. This method P2P information interchange is a method for increasing data availability by leveraging data already existent among network peers. This mechanism uses the NC algorithm can make the most of the transmit channel quality and make the most of the cooperative P2P information sharing that is possible. Experimental results demonstrate that using the PINC mechanism enhances the throughput and reduces the computational overhead in the WMN.
  • Integrating Pedagogical Approaches in the Study of Conic Sections Using Differential Equation and Analysis via Bayesian Inference
    R. Delhibabu, S. Vaithyasubramanian, R. Sundararajan, C. K. Kirubhashankar, K. Vengatakrishnan, Chandu P.M.S.S.
    Engineering Proceedings, 2023
    In science and technology, the application of mathematics and mathematical modelling is crucial. A more conceptual and axiomatic approach has been taken in developing the narrative from geometry in the enormous history of mathematics. Mathematics is distinct from all other topics due to its use of theorems, proofs, axioms, corollaries, examples, results, and analysis. Applications of mathematics can be found, among others, in management sciences, biosciences, chemical technology, computer sciences, information technology, and the medical industry. Differentiation and its extensions are among the most frequently used branches in mathematics. Different curves are created when a plane connects with the surface of a cone. They are called conic sections. Conic sections have uses in physics and architecture, among other fields. In this study, differential equations are used to determine the conic section’s type and locate its center. The effectiveness of conventional and innovative teaching strategies is compared using Bayesian inference. The Bayesian method is employed to update the prior assumptions regarding the relative efficacy of the two approaches. Data on student performance in four different types of classes are gathered for the analysis.
  • Homomorphic approach in green cloud storage to develop and deploy data surveillance
    Journal of Green Engineering, 2020
  • Intensify of metrics with the integration of software testing compatibility
    S. Vaithyasubramanian, P. M. S. S. Chandu, D. Saravanan
    Advances in Intelligent Systems and Computing, 2020
  • Validating product correctness of persistent itemset mining as a service prototype
    B. Shamreen Ahamed, P. M. S. S Chandu
    2017 International Conference on Information Communication and Embedded Systems Icices 2017, 2017
  • Integrating and enhancing the quality of services in cloud computing with software testing
    Chandu P.M.S.S, Divyasree Kata
    Proceedings of the 2016 IEEE International Conference on Wireless Communications Signal Processing and Networking Wispnet 2016, 2016
  • Secure de-cloning process with enhanced reliability along with dual encryption
    Arpn Journal of Engineering and Applied Sciences, 2016
  • Yoking object oriented metrics through mutation testing for minimizing time period ramification
    Journal of Theoretical and Applied Information Technology, 2015
  • An analytical way to improvise test execution and review of software metrics for the software quality
    Journal of Theoretical and Applied Information Technology, 2015
  • Implementation of regression testing of test case prioritization
    P. M. S. S. Chandu, T. Sasikala
    Indian Journal of Science and Technology, 2015
  • Intelligent street lighting concept with maintenance
    International Journal of Applied Engineering Research, 2015
  • Executing object oriented metrics for downsizing pace complexity over mutation examination
    International Journal of Applied Engineering Research, 2015
  • Rule based feedback driven random testing of DHCP Protocol
    International Journal of Applied Engineering Research, 2014
  • Evaluation of phytotoxicity of metallic nanoparticles against Amaranthus Retroflexus
    Asian Journal of Microbiology Biotechnology and Environmental Sciences, 2014

RECENT SCHOLAR PUBLICATIONS

  • Enhancing AI Models with Interpretability: Data Science Methods for Reliable Autonomous Agents
    P Chandu, E Murali, G Meghana, K Sanjana, KM Rathnam, KV Pavan
    2026 International Conference on Data Science, Agents and Artificial … , 2026
    2026.0
  • Semantic Textual Similarity and Unsupervised Text Segmentation: A Hybrid Approach
    RK Vankamamidi, P Chandu, M Giri, K Ammulu, MS Rao, MLM Prasad
    2026 International Conference on Intelligent and Innovative Technologies in … , 2026
    2026.0
  • A Machine Learning Framework for Forecasting Flood Severity through the Integration of Reservoir Metrics and Real-Time Meteorological Data
    P Chandu, A Gunasekhar, RE Durai, T Hemanadhan, T Durgaprasad, ...
    2026 International Conference on AI-Driven Smart Systems and Ubiquitous … , 2026
    2026.0
  • Implementation of a Secure E-Coupon Approach Using Ethereum Blockchain Technology
    P Chandu, M Giri, M Kusuma, M Kusuma, SH Rahaman, S Dhanush
    2025 International Conference on Electrical, Electronics, and Computer … , 2025
    2025.0
  • IoT-Enabled Smart Parking System using Machine Learning for Real-Time Parking Prediction
    A Suresh, P Chandu, SSC Bose, V Dhamini, PA Narayana, KD Balaji
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024.0
    Citations: 2
  • Recognition and Analysis of Bone Impairment Using Machine Learning
    P Chandu, RS Subhasree, Y DurgaPrasanna, TV Jayasree, PK Sri, ...
    2024 International Conference on Communication, Computing and Energy … , 2024
    2024.0
  • Systematic Access for Layer 7 Attacks and Mitigation
    V Ramakrishna, P Chandu, S Vaithyasubramanian, Y Immanuel
    International Conference on ICT for Sustainable Development, 393-408 , 2024
    2024.0
  • Utilizing Machine Learning Methods to Forecast Passenger Safety in Smart Urban Transportation Systems
    P Chandu, S Vaithyasubramanian, R Sundararajan, P Vaidhyanathan, ...
    International Conference on Innovative Discoveries and Emerging Advancements … , 2024
    2024.0
  • Detecting Patient Condition by Cluster-Boosted Regression with Text-Based Indexing
    KE Rajakumari, P Chandu, S Vaithyasubramanian, Y Immanuel, ...
    International Conference on Information and Communication Technology for … , 2024
    2024.0
    Citations: 1
  • Intensify of metrics with the integration of software testing compatibility
    S Vaithyasubramanian, P Chandu, D Saravanan
    Intelligent Computing in Engineering: Select Proceedings of RICE 2019, 693-699 , 2020
    2020.0
    Citations: 4
  • Homomorphic Approach in Green Cloud Storage to Develop and Deploy Data Surveillance
    P Chandu, SR Suganya, R Sundararajan, S Vaithyasubramanian
    Journal of Green Engineering 10, 11526-11539 , 2020
    2020.0
  • Integrating and enhancing the quality of services in cloud computing with software testing
    P Chandu, D Kata
    2016 International Conference on Wireless Communications, Signal Processing … , 2016
    2016.0
    Citations: 1
  • YOKING OBJECT ORIENTED METRICS THROUGH MUTATION TESTING FOR MINIMIZING TIME PERIOD RAMIFICATION.
    P Chandu, T Sasikala
    Journal of Theoretical & Applied Information Technology 77 (3) , 2015
    2015.0
  • Implementation of regression testing of test case prioritization
    P Chandu, T Sasikala
    Indian Journal of Science and Technology 8 (S8), 290-293 , 2015
    2015.0
    Citations: 10
  • An Analytical Way to Improvise Test Execution and Review of Software Metrics for The Software Quality
    P Chandu
    Journal of Theoretical and Applied Information Technology 73 (1), 1-6 , 2015
    2015.0
    Citations: 1
  • Ranking the influence users in a social networking site using an improved Topsis method
    A Muruganantham, M Gandhi, YA Fathima, D Muthumani, H Al-Dossari, ...
    Journal of Theoretical and Applied Information Technology 73 (1) , 2005
    2005.0
    Citations: 10
  • SURVEYING THE SPEED AND ACCURACY WITH AN APPLICATION USING INTEGRATED SOFTWARE TESTING METHODOLOGIES
    P Chandu, T Sasikala
    International Journal of Applied Engineering Research 10 (52), 2015 , 0

MOST CITED SCHOLAR PUBLICATIONS

  • Implementation of regression testing of test case prioritization
    P Chandu, T Sasikala
    Indian Journal of Science and Technology 8 (S8), 290-293 , 2015
    2015.0
    Citations: 10
  • Ranking the influence users in a social networking site using an improved Topsis method
    A Muruganantham, M Gandhi, YA Fathima, D Muthumani, H Al-Dossari, ...
    Journal of Theoretical and Applied Information Technology 73 (1) , 2005
    2005.0
    Citations: 10
  • Intensify of metrics with the integration of software testing compatibility
    S Vaithyasubramanian, P Chandu, D Saravanan
    Intelligent Computing in Engineering: Select Proceedings of RICE 2019, 693-699 , 2020
    2020.0
    Citations: 4
  • IoT-Enabled Smart Parking System using Machine Learning for Real-Time Parking Prediction
    A Suresh, P Chandu, SSC Bose, V Dhamini, PA Narayana, KD Balaji
    2024 4th International Conference on Mobile Networks and Wireless … , 2024
    2024.0
    Citations: 2
  • Detecting Patient Condition by Cluster-Boosted Regression with Text-Based Indexing
    KE Rajakumari, P Chandu, S Vaithyasubramanian, Y Immanuel, ...
    International Conference on Information and Communication Technology for … , 2024
    2024.0
    Citations: 1
  • Integrating and enhancing the quality of services in cloud computing with software testing
    P Chandu, D Kata
    2016 International Conference on Wireless Communications, Signal Processing … , 2016
    2016.0
    Citations: 1
  • An Analytical Way to Improvise Test Execution and Review of Software Metrics for The Software Quality
    P Chandu
    Journal of Theoretical and Applied Information Technology 73 (1), 1-6 , 2015
    2015.0
    Citations: 1
  • Enhancing AI Models with Interpretability: Data Science Methods for Reliable Autonomous Agents
    P Chandu, E Murali, G Meghana, K Sanjana, KM Rathnam, KV Pavan
    2026 International Conference on Data Science, Agents and Artificial … , 2026
    2026.0
  • Semantic Textual Similarity and Unsupervised Text Segmentation: A Hybrid Approach
    RK Vankamamidi, P Chandu, M Giri, K Ammulu, MS Rao, MLM Prasad
    2026 International Conference on Intelligent and Innovative Technologies in … , 2026
    2026.0
  • A Machine Learning Framework for Forecasting Flood Severity through the Integration of Reservoir Metrics and Real-Time Meteorological Data
    P Chandu, A Gunasekhar, RE Durai, T Hemanadhan, T Durgaprasad, ...
    2026 International Conference on AI-Driven Smart Systems and Ubiquitous … , 2026
    2026.0
  • Implementation of a Secure E-Coupon Approach Using Ethereum Blockchain Technology
    P Chandu, M Giri, M Kusuma, M Kusuma, SH Rahaman, S Dhanush
    2025 International Conference on Electrical, Electronics, and Computer … , 2025
    2025.0
  • Recognition and Analysis of Bone Impairment Using Machine Learning
    P Chandu, RS Subhasree, Y DurgaPrasanna, TV Jayasree, PK Sri, ...
    2024 International Conference on Communication, Computing and Energy … , 2024
    2024.0
  • Systematic Access for Layer 7 Attacks and Mitigation
    V Ramakrishna, P Chandu, S Vaithyasubramanian, Y Immanuel
    International Conference on ICT for Sustainable Development, 393-408 , 2024
    2024.0
  • Utilizing Machine Learning Methods to Forecast Passenger Safety in Smart Urban Transportation Systems
    P Chandu, S Vaithyasubramanian, R Sundararajan, P Vaidhyanathan, ...
    International Conference on Innovative Discoveries and Emerging Advancements … , 2024
    2024.0
  • Homomorphic Approach in Green Cloud Storage to Develop and Deploy Data Surveillance
    P Chandu, SR Suganya, R Sundararajan, S Vaithyasubramanian
    Journal of Green Engineering 10, 11526-11539 , 2020
    2020.0
  • YOKING OBJECT ORIENTED METRICS THROUGH MUTATION TESTING FOR MINIMIZING TIME PERIOD RAMIFICATION.
    P Chandu, T Sasikala
    Journal of Theoretical & Applied Information Technology 77 (3) , 2015
    2015.0
  • SURVEYING THE SPEED AND ACCURACY WITH AN APPLICATION USING INTEGRATED SOFTWARE TESTING METHODOLOGIES
    P Chandu, T Sasikala
    International Journal of Applied Engineering Research 10 (52), 2015 , 0

Publications

36 publications

RESEARCH OUTPUTS (PATENTS, SOFTWARE, PUBLICATIONS, PRODUCTS)

3 patents