Nilanjan Dey

Techno International New Town · Department of Computer Science and Engineering

The current era witnesses the notable transition of society from an information-centric to a human-centric one aiming at striking a balance between economic advancements and upholding the societal and fundamental needs of humanity. It is undeniable that the Internet of Things (IoT) and artificial intelligence (AI) are the key players in realizing a...

The expected fifth industrial revolution or Industry 5.0 (I-5.0) is human-centered and concerns societal values, and sustainability. I-5.0 focuses on human and machine coworking by augmenting human-collaborative intelligent robots. The current developments in information communications and the increasing market need for high agility and innovative...

Lasts are foot-shaped forms made of plastic, wood, aluminum, or 3D-printed plastic. The last of a shoe determines not only its shape and style but also how well it fits and protects the foot. A weight-updated boosting-based ensemble learning (WUBEL) algorithm is presented in this paper to extract critical features (points) from plantar pressure ima...

This volume comprises of research papers presented at the 4th International Conference on Innovations in Computational Intelligence and Computer Vision (ICICV 2024) organized by Department of Computer and Communication Engineering, Manipal University Jaipur, India during April 4 – 5, 2024. The book includes a collection of innovative ideas from res...

With the recent advancement of the cloud, edge, and fog computing methodology data processing and buffering become more crucial tasks. This is even more critical for real-time applications like the Internet of Drone Things. The traditional edge-fog-cloud methodology highly relays on strong Internet connectivity. In case of a mission-critical situat...

Students are the future of a nation. Personalizing student interests in higher education courses is one of the biggest challenges in higher education. Various AI and ML approaches have been used to study student behaviour. Existing AI and ML algorithms are used to identify features for various fields, such as behavioural analysis, economic analysis...

This work proposes a strategy management technique based on hybrid peer to peer communication system. The main techniques used in the P2PC are: (i) Multi-objective optimization, (ii) Game theory technique, (iii) Non-linear geometric programming, and (iv) Intuitionistic fuzzy logic. Multi-objective optimization is used to design multiple non-linear...

Artificial intelligence (AI) has shown its effectiveness in helping clinical users meet evolving challenges. Recently, ChatGPT, a newly launched AI chatbot with exceptional text comprehension capabilities, has triggered a global wave of AI popularization and application in seeking answers through human-machine dialogues. Gastric cancer, as a global...

Deep learning has revolutionized the detection of diseases and is helping the healthcare sector break barriers in terms of accuracy and robustness to achieve efficient and robust computer-aided diagnostic systems. The application of deep learning techniques empowers automated AI-based utilities requiring minimal human supervision to perform any tas...

Internet of Things application in disaster responses and management is a predominant research domain. The introduction of the consumer drones, flying ad-hoc networks, low latency 5G, and beyond 5G produce significant acceleration of this research. The work proposed the implementation of the Consumer Internet of Drone Things (CIoDT) framework for em...

The performance of load frequency control (LFC) for isolated multiple sources of electric power-generating units with a proportional integral derivative (PID) controller is presented. A thermal, hydro, and gas power-generating unit are integrated into the studied system. The PID controller is proposed as a subordinate controller to stabilize system...

Bird species identification is becoming increasingly crucial for avian biodiversity conservation and assisting ornithologists in quantifying the presence of birds in a given area. Convolutional Neural Networks (CNNs) are advanced deep learning algorithms that have proven to perform well in speech classification. However, developing an accurate deep...

This book presents high-quality, peer-reviewed papers from the International Conference on “Innovations in Computational Intelligence and Computer Vision (ICICV 2022),” hosted by Manipal University Jaipur, Rajasthan, India, on 24–25 November 2022. The book includes a collection of innovative ideas from researchers, scientists, academics, industry p...

Model inversion attack (MIA) is a cyber threat with an increasing alert even for deep-learning-based recognition systems (DLRSs). By targeting a DLRS under a scenario of attacker access to the model structure and parameters, MIA generates a data clone for a certain targeted class label. To avoid the possible threats of such MIA-generated data clone...

Worldwide COVID-19 is a highly infectious and rapidly spreading disease in almost all age groups. The Computed Tomography (CT) scans of lungs are found to be accurate for the timely diagnosis of COVID-19 infection. In the proposed work, a deep learning-based P-shot N-ways Siamese network along with prototypical nearest neighbor classifiers is imple...

In recent years, a considerable number of approaches have been proposed by the researchers to evaluate infectious diseases by examining the digital images of peripheral blood cell (PBC) recorded using microscopes. In this chapter, a semi-automated approach is proposed by integrating the Shannon's entropy (SE) thresholding and DRLS-based segmentatio...

The conversion rate between asymptomatic infections and reported/unreported symptomatic infections is a very sensitive parameter for model variables that spread COVID-19. This is important information for follow-up use in screening, prediction, prognostics, contact tracing, and drug development for the COVID-19 pandemic. The model described here su...

Advancements in cyber–physical systems (CPSs) makes CPSs essential entities in society today, and have made them prominent across all fields. For example, the healthcare industry has evolved technologically and has effectively incorporated CPS into many application areas. While these advancements, involving medical CPSs (MCPS), have been revised ac...

Unmanned aerial vehicle based precision agriculture is a predominant research area. The modern flying ad‐hoc network leverages the advanced low latency vehicular communication and intelligent computing paradigms that help the ecosystem to grow up to the next level. In this work, we propose an ecosystem for precision agriculture that leverages the u...

There are several techniques to support simulation of time series behavior. In this chapter, the approach will be based on the Composite Monte Carlo (CMC) simulation method. This method is able to model future outcomes of time series under analysis from the available data. The establishment of multiple correlations and causality between the data al...

The application of different tools for predicting COVID19 cases spreading has been widely considered during the pandemic. Comparing different approaches is essential to analyze performance and the practical support they can provide for the current pandemic management. This work proposes using the susceptible-exposed-asymptomatic but infectious-symp...

A significant number of people infected by COVID19 do not get sick immediately but become carriers of the disease. These patients might have a certain incubation period. However, the classical compartmental model, SEIR, was not originally designed for COVID19. We used the simple, commonly used SEIR model to retrospectively analyse the initial pande...

The COVID-19 pandemic spread generated an urgent need for computational systems to model its behavior and support governments and healthcare teams to make proper decisions. There are not many cases of global pandemics in history, and the most recent one has unique characteristics, which are tightly connected to the current society’s lifestyle and b...

In clinical examinations, diagnosis, treatment, and decision-making, functional magnetic resonance imaging (fMRI) has been widely used. Intelligently processing large-scale medical image data poses a major scientific challenge; segmenting fMRI images is one way to reduce computational complexity. The majority of deep learning (DL)-based segmentatio...

Telecommunications systems with Multi-Input Multi-Output (MIMO) structure using Orthogonal Frequency Division Modulation (OFDM) has a great potential of efficient application to a network of Internet of Things (IoT) of a high data rate. When the IoT network is amongst the underwater sensory devices known as the Internet of Underwater Things (IoUT),...

Magnetic Resonance Imaging: Recording, Reconstruction and Assessment gives a detailed overview of magnetic resonance imaging (MRI), its applications and challenges. It explores the abnormalities in internal human organs and its diagnosis using MRI techniques. This volume features case studies to illustrate the measures to be used, also exploring th...

Currently, predicting patients with major depressive disorder (MDD) is a challenging task. Meanwhile, magnetic resonance imaging (MRI) data analysis may be able to predict individual patient responses, which may lead to more personalized treatment decisions and better treatment outcomes. This study used a transfer learning (TL) method developed by...

This paper focuses on developing a computationally economic lightweight artificial intelligence (AI) technology for smartphones. Until date, no commercial system is available on this technology. Thus the developed breakthrough technology can enhance the capability of users on the field for monitoring the agricultural vehicles (AgV)s health by analy...

This book gathers selected high-quality research papers presented at the Sixth International Congress on Information and Communication Technology, held at Brunel University, London, on February 25–26, 2021. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agricult...

Glaucoma causes irreversible blindness. In 2020, about 80 million people worldwide had glaucoma. Existing machine learning (ML) models are limited to glaucoma prediction, where clinicians, patients, and medical experts are unaware of how data analysis and decision-making are handled. Explainable artificial intelligence (XAI) and interpretable ML (I...

Electromyography (EMG) signals are gaining popularity for several biomedical applications, including pattern recognition, disease detection, human–machine interfaces, medical image processing, and robotic limb or exoskeleton fabrication. In this study, a two-channel data acquisition system for measuring EMG signals is proposed for human lower limb...

Unstable internet connectivity in aerial interconnection is challenging for the Internet of drone Things. Introducing the low power edge device and caching methodology opens a new challenge to developing an independent computing and communication application for smart cities, the rural sector, industry, and society 4.0. This author proposes a dew-c...

Speech enhancement has substantial interest in the utilization of speaker identification, video-conference, speech transmission through communication channels, speech-based biometric system, mobile phones, hearing aids, microphones, voice conversion etc. Pattern mining methods have a vital step in the growth of speech enhancement schemes. To design...

The behavioral study of animals and especially avians, and the way of their immunization are highly needed to understand the environment in a better way. Automatically classifying bird species by their vocalization is of crucial relevance for the research of ornithologists and ecologists. It was observed that impartial survey information for songbi...

Surface electromyography (sEMG) has been widely used in clinical medicine, rehabilitation medicine, and intelligent robots. While the high rate of emotion recognition is still the key issue for the emotion applications. Employing sEMG to study emotion classification can improve the recognition rate and eliminate subjective interference. In this res...

Surface electromyography (sEMG) signal classification has many applications such as human-machine interaction, diagnosis of kinesiological studies, and neuromuscular diseases. However, these signals are complicated because of different artifacts added to the sEMG signal during recording. In this study, a multi-stage classification technique is prop...

Classification and analysis of surface EMG (sEMG) signals have been of particular interest due to their numerous applications in the biomedical field. They can be used for the diagnosis of neuromuscular diseases, kinesiological studies, and human-machine interaction. However, these signals are difficult to process due to their noisy nature. To over...

Internet of Things (IoT) concepts constitute a predominant area of research in e-healthcare applications, owing to the plethora of opportunities in medical diagnosis. In this work, a ubiquitous computing and communication architecture is proposed through the amalgamation of Internet of Healthcare and Internet of Drone things by leveraging a 5G/6G c...

There are more than 10 million new cases of Alzheimer's patients worldwide each year, which means there is a new case every 3.2 seconds. Alzheimer's disease is a progressive neurodegenerative disease and various machine learning and image processing methods have been used to detect it. In this study, we used machine learning methods to classify Alz...

The number of layers of deep learning (DL) increases, and following the performance of computing nodes improvement, the output accuracy of deep neural networks (DNN) faces a bottleneck problem. The resident network (RN) based DNN model was applied to address these issues recently. This paper improved the RN and developed a rectified linear unit (Re...

The Internet of Things paradigm is a paramount research domain for smart cities, smart villages, society, and industry 4.0. The introduction of Unmanned Aircraft Systems (UAS), ultra-low latency network infrastructure with fog, dew, and edge enabled processing ecosystem gives the researcher ample scope to establish a decentralized architecture for...

This paper presents a deep learning-based machine translation (MT) system that translates a sentence of subject-object-verb (SOV) structured language into subject-verb-object (SVO) structured language. This system uses recurrent neural networks (RNNs) and Encodings. Encode embedded RNNs generate a set of numbers from the input sentence, where the s...

Emotion produces complex neural processes and physiological changes under appropriate event stimulation. Physiological signals have the advantage of better reflecting a person’s actual emotional state than facial expressions or voice signals. An electroencephalogram (EEG) is a signal obtained by collecting, amplifying, and recording the human brain...

Measuring the spread of disease during a pandemic is critically important for accurately and promptly applying various lockdown strategies, so to prevent the collapse of the medical system. The latest pandemic of COVID-19 that hits the world death tolls and economy loss very hard, is more complex and contagious than its precedent diseases. The comp...

With the growing prevalence of Internet connectivity in the civilized world, smart grid technology has become more practically relevant to implement. The smart electric grid is more than just a generation and transmission infrastructure. Modernizing such electric grids to automate the process of tracking the electricity consumption at multiple loca...

Multi-Input Multi-Output (MIMO) telecommunication systems with Orthogonal Frequency Division Modulation (OFDM) scheme support high rate data exchange which can be efficiently applied to the fast-growing networks of Internet of Things (IoT). In the case of Underwater IoT (UIoT) where the strength of electromagnetic waves rapidly falls off, the MIMO...

The underwater sensor network (USN) is used in various domains from surveillance to different monitoring applications like monitoring of gas and oil pipelines, aquatic species or water quality. The usage and increasing demand of UWSN in different fields shows the significance of UWSN and its communication medium. The wireless communication mediums...

“Sensor networks” can be said as a significant part of technology that creates magic of sensing and wirelessly sending information on land and in water. Sensor networks built on land are popularly named as terrestrial sensor networks which are used in many applications from IoT, VANET to smart cities. The underwater wireless sensor networks [UWSNs]...

In this book, we have tried to brief on all topics, relating to use of “Underwater World for the purpose of Digital Data Transmission”. The book chapters are describing a short story on UWSN showcasing from “What is UWSN?” to “Applications of UWSN”. The first introductory chapter speaks about different architecture models in UWSN (1D, 2D, 3D and 4D...

Data security and wireless communications are the two wheels of same vehicle. In today’s era, data is useless if received from any unsecured wireless network may be terrestrial or underwater. In last 30 years, much of research work has been done in the domain of UWSN starting from underwater sensors and robotics developments, to routing and MAC pro...

The growing development and research interest in underwater wireless sensor network have led to the implementation of various underwater applications. The usefulness of applications developed underwater is ranging from underwater surveillance to the development of underwater city. The “Challenges of UWSN” really makes it difficult to architect and...

The data exchanged between sensor nodes is defined by a protocol—set of rules for communication. There are many such protocols developed for UWSN with each handling a particular aspect of communication. These protocols are generally structured together to form a stack commonly known as protocol layers. As studied in second chapter, radio waves cann...

Smart monitoring of off-road vehicles are cursed by their complex and expensive IoT sensors technologies. High dependency on the cloud/fog computation, availability of the network and Expert knowledge make it handicap in the rural off-network areas. Use of edge devices such as smartphones attributed by computation capabilities is the solution that...

The novel discovered disease coronavirus popularly known as COVID-19 is caused due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and declared a pandemic by the World Health Organization (WHO). An early-stage detection of COVID-19 is crucial for the containment of the pandemic it has caused. In this study, a transfer learning–based...

Remote sensing streams continuous data feed from the satellite to ground station for data analysis. Often the data analytics involves analyzing data in real-time, such as emergency control, surveillance of military operations or scenarios that change rapidly. Traditional data mining requires all the data to be available prior to inducing a model by...

The number of layers of deep learning (DL) increases, and following the performance of computing nodes improvement, the output accuracy of deep neural networks (DNN) faces a bottleneck problem. The resident network (RN) based DNN model was applied to address these issues recently. This paper improved the RN and developed a rectified linear unit (Re...

In the current world pandemic situation, the contagious Novel Coronavirus Disease 2019 (COVID-19) has raised a real threat to human lives owing to infection on lung cells and human respiratory systems. It is a daunting task for the researchers to find suitable infection patterns on lung CT images for automated diagnosis of COVID-19. A novel integra...

Pneumonia is one of the major illnesses in children and aged humans due to the Infection in the lungs. Early analysis of pneumonia is necessary to prepare for a possible treatment procedure to regulate and cure the disease. This research aspires to develop a Deep-Learning System (DLS) to diagnose the lung abnormality using chest X-ray (radiograph)...

Two main factors motivate the need for color in image processing. First, color is a strong descriptor frequently simplifying the recognition and extraction of objects from a picture. Second, people can distinguish thousands of tones of color and intensity comparable to just about two dozen tones of gray [1, 2, 3, 4].

Color is an important and the vital visual feature for image recognition. The use of image color is one of the most interesting issues in creation efficient content-based image retrieval. Color feature cannot be defined exactly as defining the likeness among color feature is difficult [1]. Therefore, two steps are needed in color-based image recove...

This chapter delivers an outline of MPEG-7 color descriptors. The choice of these color descriptors is influenced by various factors [1, 2, 3]. These include (a) their capacity to classify the likeness of perceptual colors, assessed by descriptor performance in matching video segments and images using color features, (b) minimum complexity of the r...

A color histogram (CH) in photography and image processing is a depiction of color variation within an image. A color histogram for digital images portrays the pixel number of that have colors in every one of defined color range list, and that include the color model of the image and the collection of all probable colors [1, 2].

Color Coherence Vector (CCV) is a more complicated technique than color histogram. Conceptually, the coherence of color can be described as the degree to which pixels of that color are part of large regions of a similar color [1, 2, 3]. These essential regions can be termed as coherent regions, and they are efficient in image characterization.

Skin melanoma is one of the major cancers in the people with the Caucasian race. Owing to its consequence, a considerable number of research works are proposed by the researchers to develop the probable computer-based assessment technique for the skin melanoma image (SMI). This work aims to develop and implement a computerized tool for the assessme...

Recently, image processing methodologies are extensively adopted in diversity of domains to process gray/RGB-scale images. The essential task is to enhance the information in the existing raw image using a chosen pre-processing method. Multi-thresholding is one of the famous pre-processing practices, normally used to enhance the raw picture by clus...

Internet users’ are carrying several smart devices with them and moves with it in this rapidly changing world of Internet of Things. These smart devices and IT environment have brought up revolutionary changes in the user’s life, businesses, etc. Existing devices and inclusion of computational devices are making a big difference in communication wi...

The technology is taking a brisk pace that the things which were not possible yesterday are possible now. Looking at the recent developments like virtual reality (VR) and augmented reality (AR), it is possible to develop several applications that deal with virtual space and physical space. The physical space around the user is a three dimensional (...

In order to simplify our life, we try to innovate. We make use of technology to make our life easier. IoT and AR will play vital role while in enhancement of IoT services. A few scenarios are studied and presented in this chapter to discover every facet of IoT. For each scenario, study is targeted toward the type of IoT devices needed, method of or...

This book shows a buffet of artificial intelligence applications from drone to deep learning and from data analysis to the prediction of next pandemic disease along with its drug discovery. Today the entire globe is under the threat of COVID-19 affecting around 200 countries. The death toll reported in these highly affected countries has become cat...

Governments and authorities knew little about the virus since the emergency of COVID-19 outbreak. The Chinese government upon the discovery of the early patients in Wuhan, informed WHO on 31 December 2019, as pneumonia of unknown causes. Epidemiologists, data scientists and biostatisticians have been working hand-in-hand for a common mission of try...

Development of innovative designs, new applications, new technologies and heavier investment in AI are continued to be seen every day. However, with the sudden impact of COVID19, so severe and urgent around the world, adoption of AI is propelled to an unprecedent level, because it helps to fight the virus pandemic by enabling one or more of the fol...

A novel coronavirus (CoV) named ‘2019-nCoV’ or ‘2019 novel coronavirus’ or ‘COVID-19’ by the World Health Organization (WHO) is in charge of the current outbreak of pneumonia that began at the beginning of December 2019 near in Wuhan City, Hubei Province, China [1–4]. COVID-19 is a pathogenic virus. From the phylogenetic analysis carried out with o...

Optimization techniques, namely, the swarm intelligence (SI) ones, have a great impact in numerous applications, including image processing and engineering practice. One of the powerful SI algorithms is the cuckoo search (CS) with its variants, which solved various problems. Owing to its ability to solve real-world and non-linear optimisation probl...

This work presents an automated system to recognize human skin disease. In many computer vision and pattern recognition problems, such as our case, considering only a single descriptor to mine one sort of feature vector is not enough to attain the entire relevant information from the input data. Therefore, it is required to apply more than one desc...

Lung abnormality is one of the common diseases in humans of all age group and this disease may arise due to various reasons. Recently, the lung infection due to SARS-CoV-2 has affected a larger human community globally, and due to its rapidity, the World-Health-Organisation (WHO) declared it as pandemic disease. The COVID-19 disease has adverse eff...