Dr. Sakthipriya S

@srmist.edu.in

Assistant Professor, Engineering & Technology
Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur Chennai, Tamil Nadu, India - 603203

Dr. Sakthipriya S


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https://researchid.co/sakthipriyas

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Science, Artificial Intelligence, Computer Science Applications
10

Scopus Publications

69

Scholar Citations

3

Scholar h-index

2

Scholar i10-index

Scopus Publications

  • AI and Machine Learning-Enabled Cognitive Digital Twin for Crime Hotspot Detection and Analysis
    T. C. Shiraptini, Kavitha Dhanushkodi, S. Sakthipriya, S. Akshaya, Sherly Alphonse
    IEEE Access, 2026
    A cognitive digital twin using AI and machine learning is proposed in this study. System of crime hot spot identification and investigations in cities. The suggested system forms up a simulated copy of city areas through blending historical crime observations, the environment and real. Introduction of time sensors to model, simulate and predict criminal activity. In this cognitive brother, machine learning algorithms such as time-series forecasting, classification and clustering techniques are used to determine the spatial and temporal trends of crime, which will make the high-risk regions predictable. The AI motor cognitive layer improves reasoning and flexibility in the digital space and enables the twin to constantly learn with new information and simulate different policing policies, including optimized patrol pathfinding and allocation of resources. The prediction of data by transforming both the real-time and non-real-time data into predictive knowledge. System facilitates decision-making proactively and effective law enforcement planning. The results demonstrate that the AI-ML-powered Cognitive Digital Twin (CDT) has a strong enhancement in the accuracy of crime hotspots prediction and situational consciousness, building scalable, adaptive, and data-driven system of smart, preventive policing and urban safety enhancement.
  • Precision Agriculture: Sensors’ Real-Time Challenges and Monitoring in Soil and Plants
    R. Naresh, S. Sakthipriya, C.N.S. Vinoth Kumar, S. Senthilkumar
    Cyber Security and Data Science Innovations for Sustainable Development of Heicc Healthcare Education Industry Cities and Communities, 2025
    This chapter outlines the challenges to adopting precision agriculture and the essential components of a potential automated decision-making system. It provides an overview of the difficulties in implementing sensing systems and electrical interfaces in harsh soil environments. The chapter also summarizes the commonly used sensing concepts for real-time soil health monitoring. It highlights the remaining challenges before automated precision agriculture decision-making systems become a reality and discusses the flaws in current agricultural circuits and sensor systems used for agricultural monitoring. The goal is to maintain healthy soil suitable for planting by preventing soil erosion and excessive use of natural or artificial resources. This can be achieved by real-time monitoring of soil management and appropriate crop strategies during production cycles. Traditional precision agriculture methods have been costly, using satellite and aircraft imagery to monitor soil and crops. Recent studies have used drones and various sensors attached to agricultural equipment for monitoring and assessing the condition of crops and soil during planting and harvesting. The chapter describes an in-situ, real-time agricultural Internet of Things (IoT) device that monitors environmental and soil conditions. This open hardware device includes sensors for soil and environmental electrical conductivity, temperature, humidity, and luminosity. It also utilizes the Global Positioning System (GPS) to communicate data. Soil conditions are monitored through conductivity, temperature, and humidity measurements. Climate data specific to the area can be used to make irrigation and crop health-related decisions. Ongoing research is focused on increasing the number of sensors and reducing energy use. Future applications for the device could include detecting crop fires, especially in sugarcane plantations, and integrating the device with irrigation management systems to optimize water consumption.
  • Edge-AI Enabled Precision Catheter Navigation for Real-Time Adaptive Cancer Therapy
    Sakthipriya S, S. P. Santhoshkumar, Navinkumar V R, Pandiselvi B, P. Arulprakash, P. Kiruthika
    International Conference on Electrical Energy Systems Icees, 2025
    To improve the efficiency of electromagnetic ablation in adaptive cancer therapy, this work introduces a revolutionary Edge-AI-enabled architecture for precise catheter navigation. The system analyzes CT scan datasets containing a variety of tumor types, sizes, and anatomical locations in real time by combining edge computing and CNN architectures designed for volumetric data. The model exhibits a mean absolute error of 0.085 cm for tumor size estimation and a classification accuracy of 90.97% in recognizing tumor features. Furthermore, it correctly classifies the location of tumors inside particular lung lobes or areas. A Gradient Boosting model is used to predict important ablation parameters, like energy dose and time, with an accuracy of 88.2% in order to improve therapy delivery. By dynamically varying the ablation energy between 30 and 150 joules, the technology allows for customized treatment plans that reduce collateral tissue damage. In order to protect patient privacy and facilitate real-time clinical decision-making, edge computing guarantees low-latency data processing and safe AI model execution right at the point of treatment. With enhanced treatment precision, operational efficiency, and overall patient outcomes guaranteed, this combined Edge-AI method offers a solid, scalable option for customized oncological interventions.
  • Precision agriculture based on convolutional neural network in rice production nutrient management using machine learning genetic algorithm
    S. Sakthipriya, R. Naresh
    Engineering Applications of Artificial Intelligence, 2024
  • Precision agriculture: crop yields classification techniques in thermo humidity sensors
    S. Sakthipriya, R. Naresh
    Optical and Quantum Electronics, 2024
  • Image Security Using Triple DES and DES Algorithms
    S Sakthipriya, R. Naresh
    2023 3rd Asian Conference on Innovation in Technology Asiancon 2023, 2023
    Data is always the source of all information and must be more secured at all cost. Cryptography helps in preventing data from outer malicious attacks while it is transferred through the network. In this we use both Triple data encryption standard (TDES) and Data Encryption Standard (DES). It uses a security key of 16 bit and 8 bit respectively to protect the safety of the image being transferred. The main applications of these algorithms rely on medical and military basis as information or images shared must maintain the privacy. The images shared are first encrypted and then decrypted using the key that the receiver must know in prior.
  • Sensing of Nitrogen and Temperature Using Chlorophyll Maps in Precision Agriculture
    Sahadevan Sakthipriya, Ramu Naresh
    Lecture Notes on Data Engineering and Communications Technologies, 2023
  • Effective Energy Estimation Technique to Classify the Nitrogen and Temperature for Crop Yield Based Green House Application
    S. Sakthipriya, R. Naresh
    Sustainable Computing Informatics and Systems, 2022
  • A Short Systematic Survey on Precision Agriculture
    S. Sakthipriya, R. Naresh
    Lecture Notes in Networks and Systems, 2022
  • Pathway Guided Deep Neural Network towards Interpretable and Predictive Modeling and Drug Preparation
    Nandhini K M, Kumar C, Shineka Varshini A P, Tharunika N, Sakthipriya S A
    Proceedings 2nd International Conference on Smart Technologies Communication and Robotics 2022 Stcr 2022, 2022
    The evaporator is vital to the pharmaceutical industry as it is used to refine finished pharmaceutical products. The evaporator is used to remove excess water during the manufacturing of pharmaceuticals. The SISO evaporator is used to determine the dry matter content by measuring temperature. System identification is used to create a mathematical model of the evaporator in a pharmaceutical factory. Adjusting the temperature of an evaporator is a laborious process. Thus, we build and implement a Neural network predictive controller for usage in the pharmaceutical industry. To fine-tune the evaporator’s control signal, it can be utilised to predict the device’s future performance. The effectiveness of the controller is evaluated using error metrics like ISE, IAE, ITSE, and ITAE. Time-domain criteria such as rising time, settling time, and overshoot are utilised to better appreciate controller functionality. Based on these analyses, it is clear that the predictive controller is superior than the more common PID controller in use in the pharmaceutical sector.

RECENT SCHOLAR PUBLICATIONS

  • Precision Agriculture: Sensors' Real-Time Challenges and Monitoring in Soil and Plants
    R Naresh, S Sakthipriya, CNSV Kumar, S Senthilkumar
    Cybersecurity and Data Science Innovations for Sustainable Development of … , 2025
    2025
    Citations: 1
  • Retraction Note: Precision agriculture: crop yields classification techniques in thermo humidity sensors
    S Sakthipriya, R Naresh
    Optical and Quantum Electronics 56 (11), 1828 , 2024
    2024
  • Precision agriculture based on convolutional neural network in rice production nutrient management using machine learning genetic algorithm
    S Sakthipriya, R Naresh
    Engineering Applications of Artificial Intelligence 130, 107682 , 2024
    2024
    Citations: 39
  • RETRACTED ARTICLE: Precision agriculture: crop yields classification techniques in thermo humidity sensors
    S Sakthipriya, R Naresh
    Optical and Quantum Electronics 56 (3), 350 , 2024
    2024
    Citations: 1
  • Image security using triple des and des algorithms
    S Sakthipriya, R Naresh
    2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-4 , 2023
    2023
    Citations: 3
  • Sensing of nitrogen and temperature using chlorophyll maps in precision agriculture
    S Sakthipriya, R Naresh
    Computational Methods and Data Engineering: Proceedings of ICCMDE 2021, 303-316 , 2022
    2022
    Citations: 2
  • Effective energy estimation technique to classify the nitrogen and temperature for crop yield based green house application
    S Sakthipriya, R Naresh
    Sustainable Computing: Informatics and Systems 35, 100687 , 2022
    2022
    Citations: 21
  • A short systematic survey on precision agriculture
    S Sakthipriya, R Naresh
    Expert Clouds and Applications: Proceedings of ICOECA 2022, 427-440 , 2022
    2022
    Citations: 2

MOST CITED SCHOLAR PUBLICATIONS

  • Precision agriculture based on convolutional neural network in rice production nutrient management using machine learning genetic algorithm
    S Sakthipriya, R Naresh
    Engineering Applications of Artificial Intelligence 130, 107682 , 2024
    2024
    Citations: 39
  • Effective energy estimation technique to classify the nitrogen and temperature for crop yield based green house application
    S Sakthipriya, R Naresh
    Sustainable Computing: Informatics and Systems 35, 100687 , 2022
    2022
    Citations: 21
  • Image security using triple des and des algorithms
    S Sakthipriya, R Naresh
    2023 3rd Asian Conference on Innovation in Technology (ASIANCON), 1-4 , 2023
    2023
    Citations: 3
  • Sensing of nitrogen and temperature using chlorophyll maps in precision agriculture
    S Sakthipriya, R Naresh
    Computational Methods and Data Engineering: Proceedings of ICCMDE 2021, 303-316 , 2022
    2022
    Citations: 2
  • A short systematic survey on precision agriculture
    S Sakthipriya, R Naresh
    Expert Clouds and Applications: Proceedings of ICOECA 2022, 427-440 , 2022
    2022
    Citations: 2
  • Precision Agriculture: Sensors' Real-Time Challenges and Monitoring in Soil and Plants
    R Naresh, S Sakthipriya, CNSV Kumar, S Senthilkumar
    Cybersecurity and Data Science Innovations for Sustainable Development of … , 2025
    2025
    Citations: 1
  • RETRACTED ARTICLE: Precision agriculture: crop yields classification techniques in thermo humidity sensors
    S Sakthipriya, R Naresh
    Optical and Quantum Electronics 56 (3), 350 , 2024
    2024
    Citations: 1
  • Retraction Note: Precision agriculture: crop yields classification techniques in thermo humidity sensors
    S Sakthipriya, R Naresh
    Optical and Quantum Electronics 56 (11), 1828 , 2024
    2024

INDUSTRY EXPERIENCE

3 years as sofware testing enginner