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Debanjan Das - IEEE Xplore Author Profile
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Debanjan Das

Publications
68
Citations
299
Publications by Year
20182024
Co-Authors:
Show All Co-Authors (115)
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Debanjan Das

Affiliation

IIT Kharagpur, Centre of Excellence in Affordable Healthcare, India

Publication Topics

Biography

Debanjan Das (Member, IEEE) received the B.Tech. degree in applied electronics and instrumentation engineering from the Heritage Institute of Technology, Kolkata, in 2009, and the M.Tech. degree in instrumentation and the Ph.D. degree in electrical engineering from the Indian Institute of Technology, Kharagpur, in 2011 and 2016, respectively. He is an Assistant Professor with Dr. SPM IIIT Naya Raipur. His current research interests include IoT-smart sensing, signal processing, bioimpedance, and instrumentation.(Based on document published on 14 December 2020).
Publications
68
Citations
299
Publications by Year
20182024
Co-Authors:
Show All Co-Authors (115)
Author's Published Works

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TRFI-Net: Modified TRFI-Based Channel Estimation for Internet of Vehicles

Dipanjan Sar;Debanjan Das;Rajarshi Mahapatra;Venkanna Uduthalapally

2024 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2024 | Conference Paper |
In the evolving landscape of the Internet of Vehicles, ensuring dependable Vehicle-to-Everything communication is imperative for Intelligent Transportation Systems. The prevailing IEEE 802.11p protocol presents formidable obstacles to accurate channel estimation owing to its standardized pilot patterns. Conventional solutions, such as data pilot-aided methods, are encumbered by error propagation i...Show More

TRFI-Net: Modified TRFI-Based Channel Estimation for Internet of Vehicles

Dipanjan Sar;Debanjan Das;Rajarshi Mahapatra;Venkanna Uduthalapally

Year: 2024 | Conference Paper |

Graphical User Interface Aided Intelligent Diagnosis of Stator Faults in Induction Motors

Jitendra Kumar Dewangan;Harsh Patel;Aparna Sinha;Debanjan Das

2024 IEEE 5th India Council International Subsections Conference (INDISCON)
Year: 2024 | Conference Paper |
Induction motors form the backbone of many modern industries; therefore, the performance and safety of these industries rely heavily on motor health. The stator faults account for more than one-third of all motor faults. The existing literature primarily focuses on current/vibration-based models for stator fault diagnosis, without any attention to providing a suitable Graphical User Interface as w...Show More

Graphical User Interface Aided Intelligent Diagnosis of Stator Faults in Induction Motors

Jitendra Kumar Dewangan;Harsh Patel;Aparna Sinha;Debanjan Das

Year: 2024 | Conference Paper |

LSTM-Autoencoder-Based Interpretable Predictive Maintenance Framework for Industrial Systems

Anmol Agrawal;Aparna Sinha;Debanjan Das

2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Year: 2024 | Conference Paper |
The overall efficiency of thermal power plants is largely dependent on the health and performance of its various systems, of which the air pre-heaters (APHs) are one of the most crucial. The existing APH fault diagnosis techniques require labeled data for training, which is challenging to obtain in real-life scenarios. To mitigate the existing drawbacks, this study presents an unsupervised fault d...Show More

LSTM-Autoencoder-Based Interpretable Predictive Maintenance Framework for Industrial Systems

Anmol Agrawal;Aparna Sinha;Debanjan Das

Year: 2024 | Conference Paper |

AnDet: ML-Based Anomaly Detection of UEs in a Multi-cell B5G Mobile Network for Improved QoS

Amar Sinha;Anmol Agrawal;Sandip Roy;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra;Sachin Shetty

2024 International Conference on Computing, Networking and Communications (ICNC)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
The rise of 5G technology has revolutionized wireless communication, ushering in a new era of unparalleled connectivity. Approaching Beyond 5G networks, Software Defined Networks have emerged as a promising paradigm to enhance flexibility and scalability in cellular networks. However, the challenge of 5G is to ensure the network's performance based on the different Quality of Service requirements ...Show More

AnDet: ML-Based Anomaly Detection of UEs in a Multi-cell B5G Mobile Network for Improved QoS

Amar Sinha;Anmol Agrawal;Sandip Roy;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra;Sachin Shetty

Year: 2024 | Conference Paper |

Identifying Oral Carcinoma from Histopathological Image using Unsupervised Nuclear Segmentation

Rahul Shukla;Bhavesh Ajwani;Shubham Sharma;Debanjan Das

2024 IEEE 9th International Conference for Convergence in Technology (I2CT)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
Oral Cancer, a worldwide health concern, highlights the urgent need for accurate and swift detection and cure. Current diagnosing strategies primarily involve pathologists for analyzing tissue biopsy samples, a method that is time-consuming and heavily driven by pathologists’ experience. To address these drawbacks, this study proposes a novel technique that incorporates machine vision for cancer d...Show More

Identifying Oral Carcinoma from Histopathological Image using Unsupervised Nuclear Segmentation

Rahul Shukla;Bhavesh Ajwani;Shubham Sharma;Debanjan Das

Year: 2024 | Conference Paper |

FoodExpert: Portable Intelligent Device for Rapid Screening of Pulse Quality and Adulteration

Harsh Pandey;Subhanshu Arya;Debanjan Das;Venkanna Udutalapally

IEEE Transactions on AgriFood Electronics
Year: 2024 | Volume: 2, Issue: 1 | Journal Article |
Cited by: Papers (1)
Pulses are one of the most important food crops in the world due to their higher protein content, approximately 21%–25%. Therefore, it is crucial to analyze the crop's quality and impurity levels. Stones, pebbles, marble chips, and synthetic dyes, such as lead chromate, metanil yellow, and artificial colors, are some of the impurities added to pulse products, accidentally or on purpose. The existi...Show More

FoodExpert: Portable Intelligent Device for Rapid Screening of Pulse Quality and Adulteration

Harsh Pandey;Subhanshu Arya;Debanjan Das;Venkanna Udutalapally

Year: 2024 | Volume: 2, Issue: 1 | Journal Article |

TSDSI Standards Driven Implementation of Smart Radio Environment

Amit K. Shrivastava;Satish Kumar;Khushboo Sahu;Bhavesh Sonwani;Dixit Sharma;Dipti S. Srivastava;Navneet Garg;Arzad Alam Kherani;Vimal Bhatia;Soumava Mukherjee;Samrat Mukhopadhyay;Priyanka Das;Rajarshi Mahapatra;Debanjan Das;Brejesh Lall

2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
This paper presents a prototype implementation of a smart radio environment (SRE) based communication system. A reflecting plate, reconfigurable intelligent surface (RIS) is placed between the transmitter and receiver to build the SRE. The RIS can rotate to reflect the incident wave to a particular direction. The experimental model consists of a channel estimator (CE), a generic RIS controller (GR...Show More

TSDSI Standards Driven Implementation of Smart Radio Environment

Amit K. Shrivastava;Satish Kumar;Khushboo Sahu;Bhavesh Sonwani;Dixit Sharma;Dipti S. Srivastava;Navneet Garg;Arzad Alam Kherani;Vimal Bhatia;Soumava Mukherjee;Samrat Mukhopadhyay;Priyanka Das;Rajarshi Mahapatra;Debanjan Das;Brejesh Lall

Year: 2023 | Conference Paper |

SDN-Based Seamless Mobility Management for B5G Services in High-Speed Railways

Amar Sinha;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra

2023 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
The emergence of 5G technology has transformed wireless connectivity and ushered in a new era of seamless connectivity while traveling. Enhancing Beyond 5G networks and maintaining a continuous data connection, especially for delay-sensitive applications, requires seamless connectivity and optimized QoS, which is challenging due to frequent service migrations and network management. The existing s...Show More

SDN-Based Seamless Mobility Management for B5G Services in High-Speed Railways

Amar Sinha;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra

Year: 2023 | Conference Paper |

Acoustic Based Chicken Health Monitoring in Smart Poultry Farms

Abhinay Bhandekar;Venkanna Udutalapally;Debanjan Das

2023 IEEE International Symposium on Smart Electronic Systems (iSES)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Poultry farming's pivotal role in meeting global protein demand emphasizes the need for chicken health assurance. This study introduces real-time acoustic monitoring for poultry farms, bridging the gap left by labor-intensive, delayed health issue detection that undermines welfare and profits. We devised a system to capture and analyze farm audio data by harnessing audio analytics and machine lear...Show More

Acoustic Based Chicken Health Monitoring in Smart Poultry Farms

Abhinay Bhandekar;Venkanna Udutalapally;Debanjan Das

Year: 2023 | Conference Paper |

Drone Vision Based Abiotic Stress Monitoring for Smart Agriculture

Gonthina Sai Sriram;S V S Aditya;Gannoju Akshar Teja;Venkanna Uduthalapally;Debanjan Das

2023 IEEE International Symposium on Smart Electronic Systems (iSES)
Year: 2023 | Conference Paper |
In recent years, significant technological advancements have driven innovative solutions across various domains, including agriculture. The compelling requirement to enhance agricultural methods employing state-of-the-art technologies such as Unmanned Aerial Vehicles and Computer Vision has grown with the increasing challenges traditional farming practices face. These technologies offer real-time ...Show More

Drone Vision Based Abiotic Stress Monitoring for Smart Agriculture

Gonthina Sai Sriram;S V S Aditya;Gannoju Akshar Teja;Venkanna Uduthalapally;Debanjan Das

Year: 2023 | Conference Paper |

Automatic Steam Leakage Detection and Prognosis in a Thermal Power Plant

Vishwambhar Reddy;Aparna Sinha;Debanjan Das

2023 IEEE 11th Region 10 Humanitarian Technology Conference (R10-HTC)
Year: 2023 | Conference Paper |
Fault Detection and Diagnosis (FDD) has recently achieved widespread popularity in industrial system monitoring applications. This is mainly due to the potential advantage that is obtained by minimum unplanned downtime, decreased mainte-nance costs, increased productivity, improved safety, and machine availability. This paper proposes a unique data-driven-based FDD approach for Remaining Useful Li...Show More

Automatic Steam Leakage Detection and Prognosis in a Thermal Power Plant

Vishwambhar Reddy;Aparna Sinha;Debanjan Das

Year: 2023 | Conference Paper |

Interpretable Deep Learning Approach for Long Horizon Health Prognosis of a Li-ion Battery

Shiva Teja Rapolu;Umesh Chandra Kadali;Jashwanth Vemula;Aparna Sinha;Debanjan Das

2023 IEEE 20th India Council International Conference (INDICON)
Year: 2023 | Conference Paper |
The safety of a wide range of devices depends on the accurate long-term estimation of the State-of-health (SoH) of Lithium-ion battery. However, the existing techniques have several limitations in terms of prediction accuracy, computational complexity and applicability. To mitigate these drawbacks, a novel Deep learning-based method with low computational complexity has been proposed that can pred...Show More

Interpretable Deep Learning Approach for Long Horizon Health Prognosis of a Li-ion Battery

Shiva Teja Rapolu;Umesh Chandra Kadali;Jashwanth Vemula;Aparna Sinha;Debanjan Das

Year: 2023 | Conference Paper |

Ensemble Learning Approach for Predictive Maintenance in Investment Casting Process

Hima Soni;Aparna Sinha;Vibha Patel;Debanjan Das;Venkanna Udutalapally

2023 IEEE 20th India Council International Conference (INDICON)
Year: 2023 | Conference Paper |
Beyond the Automation Pyramid, industries are currently embracing intelligence. One of the challenges in Industry 4.0 is to conduct Predictive maintenance (PdM) for the Investment Casting Process, which is one of the oldest metal-forming industrial processes. According to the existing works, PdM is achieved by data-driven methods for scheduling just-in-time maintenance. However, traditional Machin...Show More

Ensemble Learning Approach for Predictive Maintenance in Investment Casting Process

Hima Soni;Aparna Sinha;Vibha Patel;Debanjan Das;Venkanna Udutalapally

Year: 2023 | Conference Paper |

WiCare: Accidental Fall Detection for Elderly Care Using Passive Wi-Fi Sensing

Sontu Akshath Rishi;Govindula Srinith;Ummadisetty Dheeraj;Debanjan Das

2023 9th International Conference on Signal Processing and Communication (ICSC)
Year: 2023 | Conference Paper |
Monitoring people’s activities serves various purposes, with accidental fall detection being a significant one. Existing technologies rely on wearable sensors, which are only sometimes practical, and privacy concerns surround camera-based solutions. This study introduces a non-invasive approach using passive Wi-Fi sensing to identify accidental falls, offering a way to detect people and devices in...Show More

WiCare: Accidental Fall Detection for Elderly Care Using Passive Wi-Fi Sensing

Sontu Akshath Rishi;Govindula Srinith;Ummadisetty Dheeraj;Debanjan Das

Year: 2023 | Conference Paper |

XAIA: An Explainable AI Approach for Classification and Analysis of Blood Anemia

Jyoti Prajapati;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra;Preetam Narayan Wasnik

2023 OITS International Conference on Information Technology (OCIT)
Year: 2023 | Conference Paper |
Anemia like blood-borne disease diagnosis is a significant challenge in hematology. Generally, healthcare workers diagnose the Anemia type using a Complete Blood Count (CBC) report but finding the Anemia types and the root cause in a large number of patients is an exhausting task in a resource-constrained setup. The existing artificial intelligence models used to classify these types of anemia are...Show More

XAIA: An Explainable AI Approach for Classification and Analysis of Blood Anemia

Jyoti Prajapati;Venkanna Uduthalapally;Debanjan Das;Rajarshi Mahapatra;Preetam Narayan Wasnik

Year: 2023 | Conference Paper |

Development and Implementation of Natural Language Processing and 3D Virtualization-Based Technologies in Educational Applications

Saurabh Sanjay Saindhane;Debanjan Das;U Venkanna

2023 IEEE Integrated STEM Education Conference (ISEC)
Year: 2023 | Conference Paper |
The introduction of automated speech recognition (ASR) and 3D Virtualization has the potential to revolutionize education, particularly for underprivileged and rural children in India. This research project aims to develop an affordable and accessible artificial educational system, called Response Learning App, which presents students with real-life situations that require them to apply their acqu...Show More

Development and Implementation of Natural Language Processing and 3D Virtualization-Based Technologies in Educational Applications

Saurabh Sanjay Saindhane;Debanjan Das;U Venkanna

Year: 2023 | Conference Paper |

XAI-LCS: Explainable AI-Based Fault Diagnosis of Low-Cost Sensors

Aparna Sinha;Debanjan Das

IEEE Sensors Letters
Year: 2023 | Volume: 7, Issue: 12 | Journal Article |
Cited by: Papers (1)
An accurate technique for early detection of sensor faults proves useful in the uninterrupted supply of correct monitoring data across the Internet of Things (IoT) network. Most of the existing AI-based fault diagnosis techniques have a high computational burden, and their “black-box” nature creates challenges in generating adequate trust in high-risk industrial applications. To address the existi...Show More

XAI-LCS: Explainable AI-Based Fault Diagnosis of Low-Cost Sensors

Aparna Sinha;Debanjan Das

Year: 2023 | Volume: 7, Issue: 12 | Journal Article |

jScan: Smartphone-Assisted Bilirubin Quantification and Jaundice Screening

Jyoti Prajapati;Debanjan Das;Venkanna Udutalapally;Rajarshi Mahapatra;Preetam Narayan Wasnik

IEEE Sensors Journal
Year: 2023 | Volume: 23, Issue: 21 | Journal Article |
Cited by: Papers (1)
Jaundice occurs due to an imbalance in the levels of bilirubin in the body. Various invasive and noninvasive methods are used to identify the bilirubin level. However, the existing approaches are time-consuming, costly, require additional setup, and some are invasive. To address these issues, this article proposes a smart jaundice diagnosis method. The system utilizes a smartphone camera to captur...Show More

jScan: Smartphone-Assisted Bilirubin Quantification and Jaundice Screening

Jyoti Prajapati;Debanjan Das;Venkanna Udutalapally;Rajarshi Mahapatra;Preetam Narayan Wasnik

Year: 2023 | Volume: 23, Issue: 21 | Journal Article |

Explainable AI for Bearing Fault Detection Systems: Gaining Human Trust

Aparna Sinha;Shaik Fayaz Ahmed;Debanjan Das

2023 IEEE Guwahati Subsection Conference (GCON)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
In modern industrial processes, monitoring the health of rotating machinery is an important task. Many machine learning (ML) and deep learning (DL)-based models have shown good fault detection and diagnosis results. However, these models need to provide explanations and insights to users and experts in order to increase the adoption and spread of these technologies. Another common problem is the l...Show More

Explainable AI for Bearing Fault Detection Systems: Gaining Human Trust

Aparna Sinha;Shaik Fayaz Ahmed;Debanjan Das

Year: 2023 | Conference Paper |

Machine Learning-based Explainable Stator Fault Diagnosis in Induction Motor using Vibration Signal

Aparna Sinha;Debanjan Das

2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Year: 2023 | Conference Paper |
Cited by: Papers (2)
The early detection of stator faults in three-phase induction motors is of great importance for modern smart industries' safety, reliability, and performance. The existing stator fault detection techniques are based on voltage-current parameters collected from the motor control system, making the process invasive and complex. To mitigate these drawbacks, a novel non-invasive data-driven-based tech...Show More

Machine Learning-based Explainable Stator Fault Diagnosis in Induction Motor using Vibration Signal

Aparna Sinha;Debanjan Das

Year: 2023 | Conference Paper |

DELiB: Deep Extreme Learning-Based Health Estimation for Lithium-ion Battery

Murukuri S V S V Vasanth;Paul Akash Gunturu;Aparna Sinha;Debanjan Das

2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)
Year: 2023 | Conference Paper |
The accurate estimation of the State of Health (SoH) and Remaining Useful Life (RUL) of Lithium-ion batteries are of great significance for the safety and performance of electric vehicles (EVs), However, the existing SoH estimation techniques involve non-dynamic feature extraction without considering time and computation cost, leading to challenges in real-time implementation on batteries with var...Show More

DELiB: Deep Extreme Learning-Based Health Estimation for Lithium-ion Battery

Murukuri S V S V Vasanth;Paul Akash Gunturu;Aparna Sinha;Debanjan Das

Year: 2023 | Conference Paper |

LoRaute: Routing Messages in Backhaul LoRa Networks for Underserved Regions

Atonu Ghosh;Sudip Misra;Venkanna Udutalapally;Debanjan Das

IEEE Internet of Things Journal
Year: 2023 | Volume: 10, Issue: 22 | Journal Article |
Cited by: Papers (4)
LoRa technology endows unprecedented ability to connect isolated geographical landscapes and build community networks that serve specific purposes. As the network grows, coherent routing of messages becomes imperative to meet the network’s objectives and Quality of Service (QoS) requirements. However, despite the recent rise in research and development centered around LoRa networks, not much resea...Show More

LoRaute: Routing Messages in Backhaul LoRa Networks for Underserved Regions

Atonu Ghosh;Sudip Misra;Venkanna Udutalapally;Debanjan Das

Year: 2023 | Volume: 10, Issue: 22 | Journal Article |

SNRepair: Systematically Addressing Sensor Faults and Self-Calibration in IoT Networks

Aparna Sinha;Debanjan Das

IEEE Sensors Journal
Year: 2023 | Volume: 23, Issue: 13 | Journal Article |
Cited by: Papers (3)
An accurate and robust technique for sensor fault diagnosis proves useful for an uninterrupted supply of correct monitoring data across the Internet-of-Things (IoT) network. The manual checking and calibration of thousands of sensors deployed in the IoT network is a challenging task. Furthermore, most calibration techniques require additional hardware support for calibration. To address these issu...Show More

SNRepair: Systematically Addressing Sensor Faults and Self-Calibration in IoT Networks

Aparna Sinha;Debanjan Das

Year: 2023 | Volume: 23, Issue: 13 | Journal Article |

Skipper: A Federated Siamese Network-Based Group Activity Segregator for IoMT Systems

Vaibhav Kotiyal;Anshita Gupta;Pallav Kumar Deb;Subhas Chandra Misra;Debanjan Das;Venkanna Udutalapally

IEEE Transactions on Computational Social Systems
Year: 2023 | Volume: 10, Issue: 4 | Journal Article |
The social IoMT-based activity-monitoring system comprises several devices with different datasets. It faces challenges like a collection of a global activity dataset which comprises a myriad of activities. In this article, we propose a federated Siamese network-based data-independent group activity segregator—Skipper—which aims to identify anomalies in an activity-monitoring social IoMT system. T...Show More

Skipper: A Federated Siamese Network-Based Group Activity Segregator for IoMT Systems

Vaibhav Kotiyal;Anshita Gupta;Pallav Kumar Deb;Subhas Chandra Misra;Debanjan Das;Venkanna Udutalapally

Year: 2023 | Volume: 10, Issue: 4 | Journal Article |

FedCare: Federated Learning for Resource-Constrained Healthcare Devices in IoMT System

Anshita Gupta;Sudip Misra;Nidhi Pathak;Debanjan Das

IEEE Transactions on Computational Social Systems
Year: 2023 | Volume: 10, Issue: 4 | Journal Article |
Cited by: Papers (14)
In social IoMT systems, resource-constrained devices face the challenges of limited computation, bandwidth, and privacy in the deployment of deep learning models. Federated learning (FL) is one of the solutions to user privacy and provides distributed training among several local devices. In addition, it reduces the computation and bandwidth of transferring videos to the central server in camera-b...Show More

FedCare: Federated Learning for Resource-Constrained Healthcare Devices in IoMT System

Anshita Gupta;Sudip Misra;Nidhi Pathak;Debanjan Das

Year: 2023 | Volume: 10, Issue: 4 | Journal Article |

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