SANTHOSH S

@set.jainuniversity.ac.in

Associate Professor and Computer Science and Engineering
JAIN Deemed-to-be University

SANTHOSH S


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https://researchid.co/santhu87

EDUCATION

Ph.D Computer Science and Engineering

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Science, Software, Computer Networks and Communications
7

Scopus Publications

27

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Cloud-Based Software Development Lifecycle: A Simplified Algorithm for Cloud Service Provider Evaluation with Metric Analysis
    Santhosh S, Narayana Swamy Ramaiah
    Big Data Mining and Analytics, 2023
    At present, hundreds of cloud vendors in the global market provide various services based on a customer's requirements. All cloud vendors are not the same in terms of the number of services, infrastructure availability, security strategies, cost per customer, and reputation in the market. Thus, software developers and organizations face a dilemma when choosing a suitable cloud vendor for their developmental activities. Thus, there is a need to evaluate various cloud service providers (CSPs) and platforms before choosing a suitable vendor. Already existing solutions are either based on simulation tools as per the requirements or evaluated concerning the quality of service attributes. However, they require more time to collect data, simulate and evaluate the vendor. The proposed work compares various CSPs in terms of major metrics, such as establishment, services, infrastructure, tools, pricing models, market share, etc., based on the comparison, parameter ranking, and weightage allocated. Furthermore, the parameters are categorized depending on the priority level. The weighted average is calculated for each CSP, after which the values are sorted in descending order. The experimental results show the unbiased selection of CSPs based on the chosen parameters. The proposed parameter-ranking priority level weightage (PRPLW) algorithm simplifies the selection of the best-suited cloud vendor in accordance with the requirements of software development.
  • Iot - Enabled Technologies for Sustainable Smart Agriculture and their Comprehensive Survey
    Santosh S, Raghavendra R
    2023 International Conference on Artificial Intelligence and Smart Communication Aisc 2023, 2023
    Both the quality and amount of food demanded have increased, necessitating agricultural technology and intensification. Agricultural innovation is booming thanks to the Internet of Things, or IoT, is a cutting-edge technology. Research institutions and scientific organizations are creating IoT-based goods and solutions to solve a range of agricultural concerns. This study offers a thorough literature assessment by examining IoT technology and their current applications in a range of farming-related businesses. The comprehensive reviews of the literature conducted for this study were entirely based a review of the literature publications published in government publications during the previous ten years. Carefully selected articles from a wide variety have been arranged into courses. The major objective gathers all pertinent studies on IoT agricultural applications, sensors/devices, communication protocols, and community types. Additionally, it addresses the main problems and challenges that are the focus of modern agricultural research.
  • Diabetic Retinopathy Recognition Using CNN
    M S Sowmya, S Santosh
    International Interdisciplinary Humanitarian Conference for Sustainability Iihc 2022 Proceedings, 2022
    In this study, diabetic retinopathy has been taken into account when analyzing fundus images. An automated knowledge model is proposed to identify the key antecedents of Diabetic Retinopathy (DR) in this paper. A Convolutional Neural Network (CNN) was initially used to train the proposed model, but after testing it with a CPU-trained neural network, it shows the lowest accuracy because it has only one hidden layer, while deep learning outperforms NN. The weight of the patient's eye will be determined by the model by calculating the weights. By integrating a large selection of well-known classification algorithms into one sophisticated diagnostic model, an ensemble-based learning strategy was evaluated. The proposed framework achieved the highest accuracy rates among all other common classification algorithms. Identifying the threshold for each feature class is the most challenging part of this study. In order to identify the target class thresholds, we used a weighted fuzzy C-means algorithm. Using the model, diabetic retinopathy images can be classified according to their severity.
  • Application of An Efficient DC to DC Adaptive on Time Controlled Buck Converter for the Low Power
    Pradeep Kumar Verma, S Santosh
    4th International Conference on Emerging Research in Electronics Computer Science and Technology Icerect 2022, 2022
    A DC converter is an electronic power circuit that changes the DC voltage from one level to the next. They have a very large area of applications that are in various stages of processing and correspondence. They are typically used in high-power transmission, transportation, and equipment control. Its ability to transform electrical energy is what drives its increasing interest. Different topologies are derived from the two fundamental topologies of the DC converter, which are the Buck converter and the Lift converter. A rapid transient stable ON-time (Bed) control buck converter with high output for use in Web of. To increase the measured result swell voltage, input current is sensed and added to the dc converter's critique voltage. In this study, a sliding mode control is developed using Gao's buck converter regulation. The special response of the DC converter framework with internal boundary weaknesses. The regulator is better designed to keep track of the result stacking circumstances and adaptively adjust the control perimeters to provide a perfect, one-of-a-kind display pertaining to any heap types.
  • Systematic Biometric Reorganization Model with CNN Neural Network
    Santosh S, Harjinder Singh
    4th International Conference on Emerging Research in Electronics Computer Science and Technology Icerect 2022, 2022
    The necessity for personal data protection has grown increasingly crucial in recent years. The recognizable proof framework in light of the fusion of multiple biometrics is highly advised in this regard for greatly enhancing and obtaining high performance accuracy. In this article, the authors describe a safe deep learning convolutional neural network-based multimodal biometric recognition system (CNNs). The iris, face, and finger vein biometric modalities are presented in this work as a new multimodal biometric human ID framework that depends on a deep learning calculation. The framework's design is based on convolutional neural networks (CNNs), which concentrate highlights and utilize a SoftMax classifier to order photographs. Three CNN models - one for the iris, one for the face, and one for the finger vein - were incorporated to make the framework. The SDUMLA-HMT dataset, a multimodal biometrics dataset, was used in a number of experiments to empirically assess the presentation of the proposed framework. The results showed that employing three biometric features produced better results than using two or one biometric trait in biometric identification systems. Our technique accomplished an exactness of 99.41 % with an element level combination approach and a precision of 100 percent with different score-level combination strategies, effectively outflanking other cutting edge strategies, as indicated by the outcomes.
  • Intelligence Methods to Fight Covid-19 Spread
    Somashekhara Reddy, Santosh S
    Proceedings of the 2022 11th International Conference on System Modeling and Advancement in Research Trends Smart 2022, 2022
    According to the COVID-19 worldwide sickness, which has wreaked devastation, over than millions of individuals from all over the globe have been afflicted. The COVID-19 virus infected a significant number of people worldwide as a result of both the latency in detecting its existence in the female organism. A.i. (AI) and Computer Vision (ML) may assist in identifying, treatment, and assessing the severity of COVID-besides all the conventional approaches now present. In order to fully understand the role of AI and ML as a crucial tool for COVID-19 and related outbreak detection, forecasting, forecasts, contacts tracking, and therapy formulation, this study aims to offer a comprehensive review of the topic. AI revolutionises diagnostic accuracy in terms of efficiency and precision. This technology holds promise for a self-driving and visible surveillance system that can enable real - time and treat people avoiding spreading the virus to others. Digital Healthcare different applications have also been discovered. This essay investigates how AI may help fight the COVID-19 pandemic. We make an effort to provide an AI-based hospital design. Ai systems (AI) is used in the infrastructure to effectively and quickly carry out health care, assessment, and treatment.
  • Integration of Cloud with AI to Predict Crop Diseases
    K. Manikanta Vamsi, Ch. Abhinav Chandu, S. Santosh, S. Shitharth
    Iet Conference Proceedings, 2021
    In the meantime, technology is reaching every domain. In the software industry, Automobiles, Education, Sports, Cinema technology is molding as a backbone to solve problems quickly and effectively. Technology is even used in the medical field. In pandemic situations, online medication is playing a crucial role. Technology can even be used in the agriculture field to identify crop diseases, which is a major problem for farmers. Even it spoils the environment to a great extent. Due to these, farmers are suffering huge losses. There are many reasons for this like the usage of more pesticides as these are very toxic and dangerous. If the diseases are predicted before, then these crop diseases can be removed or killed at the starting stage without causing much crop damage. Some people like experts can determine the disease by looking at the crop, that is by seeing external symptoms. But farmers don't have the connection with the experts. Our project deals with overcoming this problem by using concepts of artificial intelligence and cloud computing. The project goal is to predict crop disease. Farmers can use this project to predict crop disease at an earlier stage and get steps to remove the disease. We will develop an android app and a website that takes the cropped photo as input. Farmers should upload the affected crop images in the app, so those experts will observe the symptoms and predict the diseases. Here, the project interacts with experts and gets the required solutions. In the absence of experts, an Artificial Intelligence model is trained with the algorithm. This AI model learns from the images uploaded and the expert's instructions to predict the output with more accuracy. Here the cloud is used to save images uploaded by users. AI models are subjected to a large number of datasets that contain disease data and predict the output. The output is then validated by experts to evaluate the correctness of the output.

RECENT SCHOLAR PUBLICATIONS

  • Software Requirement Specification Document Analysis and Identification of Important Parameters for Development Through Machine Learning
    P Rauniyar, MB Thapa, B Rauniyar, J Kulkarni
    2025 International Conference on Information, Implementation, and Innovation … , 2025
    2025
  • Iot–Enabled Technologies for Sustainable Smart Agriculture and their Comprehensive Survey
    S Santosh, R Raghavendra
    2023 International Conference on Artificial Intelligence and Smart … , 2023
    2023
    Citations: 3
  • Cloud-based software development lifecycle: A simplified algorithm for cloud service provider evaluation with metric analysis
    S Santhosh, NS Ramaiah
    Big Data Mining and Analytics 6 (2), 127-138 , 2023
    2023
    Citations: 10
  • Retracted: Systematic Biometric Reorganization Model with CNN Neural Network
    S Santosh, H Singh
    2022 Fourth International Conference on Emerging Research in Electronics … , 2022
    2022
  • Intelligence Methods to Fight Covid-19 Spread
    S Reddy, S Santosh
    2022 11th International Conference on System Modeling & Advancement in … , 2022
    2022
  • Diabetic retinopathy recognition using cnn
    MS Sowmya, S Santosh
    2022 International Interdisciplinary Humanitarian Conference for … , 2022
    2022
    Citations: 3
  • Understanding the significant challenges of software engineering in cloud environments
    S Santhosh, NS Ramaiah
    Computational Intelligence Techniques and Their Applications to Software … , 2020
    2020
    Citations: 1
  • The Impact of Software Engineering Methods for Cloud Computing Models–A Survey
    S Santhosh, NS Ramaiah
    Available at SSRN 3372019 , 2019
    2019
    Citations: 2
  • Survey on Data clustering techniques
    S Madhuri G, S Santhosh
    Journal of Emerging Technologies and Innovative Research 6 (3), 9-14 , 2019
    2019
  • Improved fair scheduling algorithm for tasktracker in hadoop map-reduce
    S Santhosh, H Kumar
    Int J Adv Technol Eng Sci 3 (1) , 2015
    2015
    Citations: 2
  • campus access control system RFID based
    S Santhosh, KK Sanihosh
    International Journal of Electronics and Computer Science Engineering 1 (3 … , 2013
    2013
    Citations: 6

MOST CITED SCHOLAR PUBLICATIONS

  • Cloud-based software development lifecycle: A simplified algorithm for cloud service provider evaluation with metric analysis
    S Santhosh, NS Ramaiah
    Big Data Mining and Analytics 6 (2), 127-138 , 2023
    2023
    Citations: 10
  • campus access control system RFID based
    S Santhosh, KK Sanihosh
    International Journal of Electronics and Computer Science Engineering 1 (3 … , 2013
    2013
    Citations: 6
  • Iot–Enabled Technologies for Sustainable Smart Agriculture and their Comprehensive Survey
    S Santosh, R Raghavendra
    2023 International Conference on Artificial Intelligence and Smart … , 2023
    2023
    Citations: 3
  • Diabetic retinopathy recognition using cnn
    MS Sowmya, S Santosh
    2022 International Interdisciplinary Humanitarian Conference for … , 2022
    2022
    Citations: 3
  • The Impact of Software Engineering Methods for Cloud Computing Models–A Survey
    S Santhosh, NS Ramaiah
    Available at SSRN 3372019 , 2019
    2019
    Citations: 2
  • Improved fair scheduling algorithm for tasktracker in hadoop map-reduce
    S Santhosh, H Kumar
    Int J Adv Technol Eng Sci 3 (1) , 2015
    2015
    Citations: 2
  • Understanding the significant challenges of software engineering in cloud environments
    S Santhosh, NS Ramaiah
    Computational Intelligence Techniques and Their Applications to Software … , 2020
    2020
    Citations: 1
  • Software Requirement Specification Document Analysis and Identification of Important Parameters for Development Through Machine Learning
    P Rauniyar, MB Thapa, B Rauniyar, J Kulkarni
    2025 International Conference on Information, Implementation, and Innovation … , 2025
    2025
  • Retracted: Systematic Biometric Reorganization Model with CNN Neural Network
    S Santosh, H Singh
    2022 Fourth International Conference on Emerging Research in Electronics … , 2022
    2022
  • Intelligence Methods to Fight Covid-19 Spread
    S Reddy, S Santosh
    2022 11th International Conference on System Modeling & Advancement in … , 2022
    2022
  • Survey on Data clustering techniques
    S Madhuri G, S Santhosh
    Journal of Emerging Technologies and Innovative Research 6 (3), 9-14 , 2019
    2019