Dr. Riman Mandal

@krmangalam.edu.in

Assistant Professor, School of Engineering and Technology
K R Manglam University

Dr. Riman Mandal


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https://researchid.co/riman007

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Engineering, Computer Science, Computer Science Applications, Human-Computer Interaction
17

Scopus Publications

247

Scholar Citations

9

Scholar h-index

8

Scholar i10-index

Scopus Publications

  • FIR-Robot: A Federated Learning Approach to Information Retrieval in Robotic Edge Devices
    Rahul Kumar Singh, Imran Siraj, Ashok Kumar, Dipti Singh, Riman Mandal, Pawan Kumar
    2025 2nd International Conference on Multidisciplinary Research and Innovations in Engineering Mrie 2025, 2025
  • Big IoT Data Analytics in Fog Computing
    Fog Computing for Intelligent Cloud Iot Systems, 2024
  • Currency Detection Application for Visually Impaired People using Tensorflow Lite
    Ruchika Bhakhar, Riman Mandal, Archna Goyal, Ashok Kumar, Rahul Singh, Harsh Vardhan
    Proceedings of the 2024 13th International Conference on System Modeling and Advancement in Research Trends Smart 2024, 2024
    The primary aim of the research endeavour is to delineate the process of recognizing the distinctive character- istics of Indian banknotes through the utilization of a mobile application. The team of individuals committed to this project has demonstrated exceptional attention to detail and precision in the development of an intricate system for the identification of Indian currency. This intricate undertaking encompassed an exhaustive and meticulous procedure of instructing the system through the utilization of sophisticated methodologies and algorithms, leveraging the cutting-edge technology facilitated by TensorFlow to its fullest extent. Following this intensive training phase, the system seamlessly transitioned into a more lightweight and efficient version known as TensorFlow Lite, without any disruptions or complications. By strategically employing Convolutional Neural Network (CNN) methodologies for image classification, a thorough and detailed examination of the image dataset was meticulously undertaken, leading to the proficient extraction of complex and nuanced characteristics that are indispensable for the precise recognition and classification of various denominations of Indian currency. The collective efforts and extensive research carried out have ultimately led to the culmination of a sophisticated currency detection model. This model has been enriched with remarkable proficiency in the ability to differentiate and categorize various denominations of Indian banknotes with an unparalleled level of accuracy and precision.
  • Transforming Algorithmic Trading with AI: Achieving Competitive Market Edge
    Harsh Vardhan, Neha Sharma, Manish Kumar, Rahul Kumar Singh, Riman Mandal, Imran Siraj
    Proceedings of the 2024 13th International Conference on System Modeling and Advancement in Research Trends Smart 2024, 2024
    This research examines the use of an algorithmic trading bot that applies the dollar cost averaging (DCA) strategy. This strategy is coded by Python. The bot installation programme is able to perform market orders, delineate trading positions, and calculate a variety of parameters which the consumers will use to make trade decisions. The bot eliminates the need for trading during the most unfavorable times by automating trade execution and profit calculations, creating accurate profit targets, and at the same time reducing the liability by setting safety orders. DCA bot makes purchases of financial assets from currently existing marketplaces and uses a way that the bot will double the trade volume under the bet price change to recoup from previous entry. Given the test run in a fake trading platform using the historical data from the market, the bot always could achieve the 2% profit suggested for each trade. The employment of real-time orders safety through mitigation of risk induced by unexpected price movements and provision of optimum timing for trade exit enhanced the profitability of trades. Main stats, like average profit per trade, and account drawdown helped in formation of the strategy. Last but not least, the results prove that the CNN-based bot used as the automated trading tool is a reliable one with possible further optimization in a real-time trading environment that perhaps will lead to performance and robustness improvement.
  • Advancements in Voice Assistants: A Study of Speech Recognition and Emotional Intelligence
    Narayan Jee, Sumit Kumar, Rajiv Ranjan Patel, Riman Mandal, Rahul Kumar Singh, Harsh Vardhan
    Proceedings of the 2024 13th International Conference on System Modeling and Advancement in Research Trends Smart 2024, 2024
    Today the interaction with a user is achieved in a more advanced way due to the advanced systems, and researchers are coming up with innovative solutions to improve these systems. This paper suggests an automatic Speech Emotion Recognition (SER) algorithm that employs deep learning techniques which combine three-dimensional convolution and recurrent neural networks, and it operates in real time. Taking advantage of advanced feature extraction methods, such as Mel-Frequency Cepstral Coefficients (MFCCs)and chroma features, the model targets happy, sad and angry moods. We show that our system has high accuracy and good response for different emotional states. The proposed research adds to the increasing literature in the affective computing area by focusing on SER system development as well as providing a model for the integration of emotional intelligence into AI powered voice assistant systems.
  • Design and Development of a Fog-Assisted Elephant Corridor over a Railway Track
    Manash Kumar Mondal, Riman Mandal, Sourav Banerjee, Utpal Biswas, Jerry Chun-Wei Lin, Osama Alfarraj, Amr Tolba
    Sustainability Switzerland, 2023
    Elephants are one of the largest animals on earth and are found in forests, grasslands and savannahs in the tropical and subtropical regions of Asia and Africa. A country like India, especially the northeastern region, is covered by deep forests and is home to many elephants. Railroads are an effective and inexpensive means of transporting goods and passengers in this region. Due to poor visibility in the forests, collisions between trains and elephants are increasing day by day. In the last ten years, more than 190 elephants died due to train accidents. The most effective solution to this collision problem is to stop the train immediately. To address this sensitive issue, a solution is needed to detect and monitor elephants near railroad tracks and analyze data from the camera trap near the intersection of elephant corridors and railroad tracks. In this paper, we have developed a fog computing-based framework that not only detects and monitors the elephants but also improves the latency, network utilization and execution time. The fog-enabled elephant monitoring system informs the train control system of the existence of elephants in the corridor and a warning light LED flashes near the train tracks. This system is deployed and simulated in the iFogSim simulator and shows improvements in latency, network utilization, and execution time compared to cloud-based infrastructures.
  • MECpVmS: an SLA aware energy-efficient virtual machine selection policy for green cloud computing
    Riman Mandal, Manash Kumar Mondal, Sourav Banerjee, Gautam Srivastava, Waleed Alnumay, Uttam Ghosh, Utpal Biswas
    Cluster Computing, 2023
  • Fog Assisted Tiger Alarming Framework for Saving Endangered Wild Life
    Manash Kumar Mondal, Riman Mandal, Sourav Banerjee, Monali Sanyal, Uttam Ghosh, Utpal Biswas
    Conference Proceedings IEEE SOUTHEASTCON, 2023
    Real-time monitoring is necessary for saving endangered wildlife. The camera-trapping technology is used to monitor wild animals like tigers, lions, bears etc. in forests. Due to changes in the forest echo system and the expansion of human civilization near the forest, tigers often enter the villages. As a consequence, the Tiger-Human conflict occurs more frequently. Typically, cloud computing technologies are used for storing and processing the image data generated from trap cameras. A wildlife monitoring system is a time-sensitive application, and processing and decision-making using cloud computing are relatively slow. Timeliness and quick response are essential for these types of applications. Highlighting this issue, this article focuses on the design and development of a fog-assisted tiger alarming framework that detects tigers in the corridor. The application also delivers systematic alerts to the villagers. Therefore, the conflict between humans and tigers will reduce. For comparison, we have deployed the same model in a cloud computing environment. The proposed framework is simulated in the iFogSim simulator. The outcome exhibits that the proposed fog-based model successfully reduces latency and network usage compared to the traditional cloud-based model. The comparative analysis also indicates a significant improvement in the execution time over the cloud system.
  • Fog assisted Visitor Identification Framework with improved Latency and Network Usage
    Manash Kumar Mondal, Riman Mandal, Sourav Banerjee, Pushpita Chatterjee, Wathiq Mansoor, Utpal Biswas
    2023 Advances in Science and Engineering Technology International Conferences Aset 2023, 2023
    Visitor identification is one of the vital problems of society. The visitor identification process consists of an intelligent security camera that monitors the entrance of the door of a residence, taking pictures of the human when they enter, automated techniques extract the human face from the image and identify them with the help of a database in real-time. However, there is no such existing research that can deal with visitor identification using fog computing. In this paper, a visitor identification framework is proposed that is entirely deployed in the fog computing environment. The proposed prototype is deployed in the Java-based iFogSim simulator. Each simulation uses a different number of cameras for video stream generations. The human object part is trimmed and selected from the raw data for processing. The trimmed data is transferred to the fog node instead of the cloud for processing. This paper deals with how the generated data pass through each module and takes how much amount of time to process the data in distinct modules. Generally, the fog-based framework reduces latency, network usage, and energy consumption. The research finds an improvement in overall latency and network usage of fog computing environments over the cloud environment.
  • A CPS based social distancing measuring model using Edge and Fog computing
    Manash Kumar Mondal, Riman Mandal, Sourav Banerjee, U. Biswas, Pushpita Chatterjee, Waleed S. Alnumay
    Computer Communications, 2022
  • QoS and Energy Efficiency Using Green Cloud Computing
    Riman Mandal, Sourav Banerjee, Md Bagbul Islam, Pushpita Chatterjee, Utpal Biswas
    Internet of Things, 2022
  • PbV mSp: A priority-based VM selection policy for VM consolidation in green cloud computing
    Riman Mandal, Manash Kumar Mondal, Sourav Banerjee, Pushpita Chatterjee, Wathiq Mansoor, Utpal Biswas
    2022 5th International Conference on Signal Processing and Information Security Icspis 2022, 2022
  • Design and implementation of an SLA and energy-aware VM placement policy in green cloud computing
    Riman Mandal, Manash Kumar Mondal, Sourav Banerjee, Pushpita Chatterjee, Wathiq Mansoor, Utpal Biswas
    2022 IEEE Globecom Workshops GC Wkshps 2022 Proceedings, 2022
  • An approach toward design and development of an energy-aware VM selection policy with improved SLA violation in the domain of green cloud computing
    Riman Mandal, Manash Kumar Mondal, Sourav Banerjee, Utpal Biswas
    Journal of Supercomputing, 2020
  • A survey and critical analysis on energy generation from datacenter
    Riman Mandal, Manash Kumar Mondal, Sourav Banerjee, Chinmay Chakraborty, Utpal Biswas
    Data Deduplication Approaches Concepts Strategies and Challenges, 2020
  • An Approach Toward Amelioration of a New Cloudlet Allocation Strategy Using Cloudsim
    Sourav Banerjee, Aritra Roy, A. Chowdhury, Ranit Mutsuddy, R. Mandal, U. Biswas
    Arabian Journal for Science and Engineering, 2018
  • An approach towards amelioration of an efficient VM allocation policy in cloud computing domain
    Sourav Banerjee, R. Mandal, U. Biswas
    Wireless Personal Communications, 2018

RECENT SCHOLAR PUBLICATIONS

  • Enhancing biometric authentication privacy and security: A synergistic approach using cancelable biometrics and federated learning
    VD Katkar, R Mandal, U Biswas, M Lunagaria, GG Tejani, SJ Mousavirad
    Alexandria Engineering Journal 135, 36-63 , 2026
    2026
    Citations: 1
  • Artificial Intelligence-Driven Approaches for Proactively Securing Cloud Infrastructure
    MS Bhonsle, R Sajjan, R Mandal, B Anil
    Kiwi International Publishing House , 2025
    2025
  • FIR-Robot: A Federated Learning Approach to Information Retrieval in Robotic Edge Devices
    RK Singh, I Siraj, A Kumar, D Singh, R Mandal, P Kumar
    2025 2nd International Conference On Multidisciplinary Research and … , 2025
    2025
    Citations: 2
  • Currency Detection Application for Visually Impaired People using Tensorflow Lite
    R Bhakhar, R Mandal, A Goyal, A Kumar, R Singh, H Vardhan
    2024 13th International Conference on System Modeling & Advancement in … , 2024
    2024
    Citations: 4
  • Transforming Algorithmic Trading with AI: Achieving Competitive Market Edge
    H Vardhan, N Sharma, M Kumar, RK Singh, R Mandal, I Siraj
    2024 13th International Conference on System Modeling & Advancement in … , 2024
    2024
    Citations: 2
  • Advancements in Voice Assistants: A Study of Speech Recognition and Emotional Intelligence
    N Jee, S Kumar, RR Patel, R Mandal, RK Singh, H Vardhan
    2024 13th International Conference on System Modeling & Advancement in … , 2024
    2024
    Citations: 3
  • Big IoT data analytics in fog computing
    MK Mondal, R Mandal, U Biswas
    Fog Computing for Intelligent Cloud IoT Systems, 279-307 , 2024
    2024
    Citations: 2
  • Fog assisted tiger alarming framework for saving endangered wild life
    MK Mondal, R Mandal, S Banerjee, M Sanyal, U Ghosh, U Biswas
    SoutheastCon 2023, 798-803 , 2023
    2023
    Citations: 4
  • Design and development of a fog-assisted elephant corridor over a railway track
    MK Mondal, R Mandal, S Banerjee, U Biswas, JCW Lin, O Alfarraj, ...
    Sustainability 15 (7), 5944 , 2023
    2023
    Citations: 15
  • Fog assisted visitor identification framework with improved latency and network usage
    MK Mondal, R Mandal, S Banerjee, P Chatterjee, W Mansoor, U Biswas
    2023 Advances in Science and Engineering Technology International … , 2023
    2023
    Citations: 2
  • MECpVmS: an SLA aware energy-efficient virtual machine selection policy for green cloud computing
    R Mandal, MK Mondal, S Banerjee, G Srivastava, W Alnumay, U Ghosh, ...
    Cluster Computing 26 (1), 651-665 , 2023
    2023
    Citations: 51
  • PbV mSp: A priority-based VM selection policy for VM consolidation in green cloud computing
    R Manda, MK Mondal, S Banerjee, P Chatterjee, W Mansoor, U Biswas
    2022 5th International Conference on Signal Processing and Information … , 2023
    2023
    Citations: 9
  • Design and implementation of an SLA and energy-aware VM placement policy in green cloud computing
    R Mandal, MK Mondal, S Banerjee, P Chatterjee, W Mansoor, U Biswas
    2022 IEEE Globecom Workshops (GC Wkshps), 777-782 , 2022
    2022
    Citations: 11
  • A CPS based social distancing measuring model using edge and fog computing
    MK Mondal, R Mandal, S Banerjee, U Biswas, P Chatterjee, W Alnumay
    Computer Communications 194, 378-386 , 2022
    2022
    Citations: 13
  • QoS and energy efficiency using green cloud computing
    R Mandal, S Banerjee, MB Islam, P Chatterjee, U Biswas
    Intelligent Internet of Things for Healthcare and Industry, 287-305 , 2022
    2022
    Citations: 12
  • A survey and critical analysis on energy generation from datacenter
    R Mandal, MK Mondal, S Banerjee, C Chakraborty, U Biswas
    Data Deduplication Approaches, 203-230 , 2021
    2021
    Citations: 19
  • An approach towards developments of smart COVID-19 patient's management and triaging using blockchain framework
    PK Lahiri, R Mandal, S Banerjee, U Biswas
    2020
    Citations: 1
  • An approach toward design and development of an energy-aware VM selection policy with improved SLA violation in the domain of green cloud computing: R. Mandal et al.
    R Mandal, MK Mondal, S Banerjee, U Biswas
    The Journal of Supercomputing 76 (9), 7374-7393 , 2020
    2020
    Citations: 80
  • An Approach Towards Amelioration of an Efficient VM Allocation Policy in Cloud Computing Domain
    S Banerjee, R Mandal, U Biswas
    Wireless Personal Communications, 1–22 , 2017
    2017
    Citations: 6
  • An Approach Toward Amelioration of a New Cloudlet Allocation Strategy Using Cloudsim
    S Banerjee, A Roy, A Chowdhury, R Mutsuddy, R Mandal, U Biswas
    Arabian Journal for Science and Engineering, 1-24 , 2017
    2017
    Citations: 10

MOST CITED SCHOLAR PUBLICATIONS

  • An approach toward design and development of an energy-aware VM selection policy with improved SLA violation in the domain of green cloud computing: R. Mandal et al.
    R Mandal, MK Mondal, S Banerjee, U Biswas
    The Journal of Supercomputing 76 (9), 7374-7393 , 2020
    2020
    Citations: 80
  • MECpVmS: an SLA aware energy-efficient virtual machine selection policy for green cloud computing
    R Mandal, MK Mondal, S Banerjee, G Srivastava, W Alnumay, U Ghosh, ...
    Cluster Computing 26 (1), 651-665 , 2023
    2023
    Citations: 51
  • A survey and critical analysis on energy generation from datacenter
    R Mandal, MK Mondal, S Banerjee, C Chakraborty, U Biswas
    Data Deduplication Approaches, 203-230 , 2021
    2021
    Citations: 19
  • Design and development of a fog-assisted elephant corridor over a railway track
    MK Mondal, R Mandal, S Banerjee, U Biswas, JCW Lin, O Alfarraj, ...
    Sustainability 15 (7), 5944 , 2023
    2023
    Citations: 15
  • A CPS based social distancing measuring model using edge and fog computing
    MK Mondal, R Mandal, S Banerjee, U Biswas, P Chatterjee, W Alnumay
    Computer Communications 194, 378-386 , 2022
    2022
    Citations: 13
  • QoS and energy efficiency using green cloud computing
    R Mandal, S Banerjee, MB Islam, P Chatterjee, U Biswas
    Intelligent Internet of Things for Healthcare and Industry, 287-305 , 2022
    2022
    Citations: 12
  • Design and implementation of an SLA and energy-aware VM placement policy in green cloud computing
    R Mandal, MK Mondal, S Banerjee, P Chatterjee, W Mansoor, U Biswas
    2022 IEEE Globecom Workshops (GC Wkshps), 777-782 , 2022
    2022
    Citations: 11
  • An Approach Toward Amelioration of a New Cloudlet Allocation Strategy Using Cloudsim
    S Banerjee, A Roy, A Chowdhury, R Mutsuddy, R Mandal, U Biswas
    Arabian Journal for Science and Engineering, 1-24 , 2017
    2017
    Citations: 10
  • PbV mSp: A priority-based VM selection policy for VM consolidation in green cloud computing
    R Manda, MK Mondal, S Banerjee, P Chatterjee, W Mansoor, U Biswas
    2022 5th International Conference on Signal Processing and Information … , 2023
    2023
    Citations: 9
  • An Approach Towards Amelioration of an Efficient VM Allocation Policy in Cloud Computing Domain
    S Banerjee, R Mandal, U Biswas
    Wireless Personal Communications, 1–22 , 2017
    2017
    Citations: 6
  • Currency Detection Application for Visually Impaired People using Tensorflow Lite
    R Bhakhar, R Mandal, A Goyal, A Kumar, R Singh, H Vardhan
    2024 13th International Conference on System Modeling & Advancement in … , 2024
    2024
    Citations: 4
  • Fog assisted tiger alarming framework for saving endangered wild life
    MK Mondal, R Mandal, S Banerjee, M Sanyal, U Ghosh, U Biswas
    SoutheastCon 2023, 798-803 , 2023
    2023
    Citations: 4
  • Advancements in Voice Assistants: A Study of Speech Recognition and Emotional Intelligence
    N Jee, S Kumar, RR Patel, R Mandal, RK Singh, H Vardhan
    2024 13th International Conference on System Modeling & Advancement in … , 2024
    2024
    Citations: 3
  • FIR-Robot: A Federated Learning Approach to Information Retrieval in Robotic Edge Devices
    RK Singh, I Siraj, A Kumar, D Singh, R Mandal, P Kumar
    2025 2nd International Conference On Multidisciplinary Research and … , 2025
    2025
    Citations: 2
  • Transforming Algorithmic Trading with AI: Achieving Competitive Market Edge
    H Vardhan, N Sharma, M Kumar, RK Singh, R Mandal, I Siraj
    2024 13th International Conference on System Modeling & Advancement in … , 2024
    2024
    Citations: 2
  • Big IoT data analytics in fog computing
    MK Mondal, R Mandal, U Biswas
    Fog Computing for Intelligent Cloud IoT Systems, 279-307 , 2024
    2024
    Citations: 2
  • Fog assisted visitor identification framework with improved latency and network usage
    MK Mondal, R Mandal, S Banerjee, P Chatterjee, W Mansoor, U Biswas
    2023 Advances in Science and Engineering Technology International … , 2023
    2023
    Citations: 2
  • Enhancing biometric authentication privacy and security: A synergistic approach using cancelable biometrics and federated learning
    VD Katkar, R Mandal, U Biswas, M Lunagaria, GG Tejani, SJ Mousavirad
    Alexandria Engineering Journal 135, 36-63 , 2026
    2026
    Citations: 1
  • An approach towards developments of smart COVID-19 patient's management and triaging using blockchain framework
    PK Lahiri, R Mandal, S Banerjee, U Biswas
    2020
    Citations: 1
  • Artificial Intelligence-Driven Approaches for Proactively Securing Cloud Infrastructure
    MS Bhonsle, R Sajjan, R Mandal, B Anil
    Kiwi International Publishing House , 2025
    2025