Gaurav Singal

Netaji Subhas University of Technology | NSITONLINE · Computer Science and Engineering

The growing popularity of multimedia applications and services needs to support several quality of service metrics such as high throughput, low energy, and jitter, which is a challenging task in mobile ad hoc networks. Because of limited bandwidth, energy constraints, dynamic topology, transmission errors, and fluctuating link stability, the links...

In recent research, link stability is getting tremendous attention in mobile adhoc networks (MANETs), because of several impediments that occur in a reliable and robust network. Link stability metric is used to improve network performance in terms of end-to-end delay, data success delivery ratio (DSDR) and available route time (ART). Energy consump...

In MANETs, real-time multimedia applications make Quality of Service (QoS) support, a crucial issue regarding terms of increased throughput, reduced jitter and available bandwidth. The highly dynamic topology of the network, large variation of received signal strength at nodes and frequently varying link characteristics make QoS provisioning, a cha...

The motivation for this research stems from the need to improve the safety and independence of visually impaired individuals in their daily lives. These individuals face significant challenges in navigating their environments, particularly when it comes to identifying and avoiding hazardous objects that can cause physical harm. Existing assistive t...

Wireless energy transfer (WET) technology has been proven to mitigate the energy shortage challenge faced by the Internet of Things (IoT), which encompasses sensor networks. Exploiting a Mobile Charger (MC) to energize critical sensors provides a new dimension to maintain continual network operations. Still, existing solutions are not robust as the...

Footprint biometrics is one of the emerging techniques, which can be utilized in different security systems. A human footprint has unique traits which is sufficient to recognize any person. Existing work evaluates the shape features and texture features but very few authors have explored minutiae features, hence this article provides a study based...

Software-defined networking will be a critical component of the networking domain as it transitions from a standard networking design to an automation network. To meet the needs of the current scenario, this architecture redesign becomes mandatory. Besides, machine learning (ML) and deep learning (DL) techniques provide a significant solution in ne...

Recently, machine learning methods have been successfully used for the prediction of cardiovascular disease. Early diagnosis and prediction is necessary for giving effective treatment to avoid higher mortality rates. Several classification algorithms have been developed recently which satisfy the need, but show limited accuracy while predicting the...

In today’s world, as each aspect of our lives is becoming more and more enhanced, IoT plays a major role in all development areas. However, the same has not been implemented on a major scale for interior and exterior lighting systems. A plethora of research is being carried out and people are looking for a clean and better solution for the next gen...

The rapid growth of the Internet of Things (IoT) in the early twenty-first century has introduced complexities in delivering various services, including quality of service (QoS) management for smart agriculture sensors. Selecting optimal IoT nodes considering QoS parameters such as energy consumption, latency, and network coverage area has become c...

Artificial agents are used in autonomous systems such as autonomous vehicles, autonomous robotics, and autonomous drones to make predictions based on data generated by fusing the values from many sources such as different sensors. Malfunctioning of sensors was noticed in the robotics domain. The correct observation from sensors corresponds to the t...

As the ground-based instruments for measuring net radiation are costly and need to be handled skillfully, the net radiation data at spatial and temporal scales over Indian subcontinent are scanty. Sometimes, it is necessary to use other meteorological parameters to estimate the value of net radiation, although the prediction may vary based on seaso...

In this paper, we introduce Fuzzy-MAC protocol to facilitate the uniform transmission of the multi-constrained data generated by the sensor devices in a wireless body area network (WBAN). A physiological sensor device allows us to monitor various health-related parameters. In the process, the sensed data become associated with diverse Quality of Se...

Medical Internet of Things (MIoT) is an emerging area of IoT comprising of wearable sensor nodes having low-powered processors. Wearable nodes gather the physiological data of a patient and transmit this real-time information to the user over an insecure channel. There is a possibility that an attacker might gather the personal or medical informati...

Physiological measurements are an important parameter of a person’s health. Therefore, we must take the information about our body’s physiological measurements to remain updated with our health status. There are a huge number of patients and few physicians in this world. This is creating an imbalance in the health industry. To cope with the imbalan...

In developing countries, stray animals can be frequently encountered on the roads, pathways, campuses, and other places. Due to this, the visually impaired (VI) are at more risk than the sighted ones. To gain more security and safety, they need a solution to deal with their problem. This experimentation aims to develop a hardware–software integrate...

The multi-core architecture has revolutionized the parallel computing. Despite this, the modern age compilers have a long way to achieve auto-parallelization. Through this paper, we introduce a language that encouraging the auto-parallelization. We are also introducing Front-End for our auto-parallelizing compiler. Later, we examined our compiler e...

Detection and recognition of military vehicle from a given image or a video frame with the help of unmanned aircraft system is the major issue which we are concerned about. Vehicle identification and classification from a resource constraint device embedded on an aerial vehicle integrated with an intelligent object detection algorithm, is a big sup...

Currency has become absolutely necessary part in human life. At present recognition of counterfeit and real currency notes is very important. If the application learns to classify the denominations of the currency and detect the counterfeit currency then it will improve the accuracy of the recognition and confidence of the people. Implementation of...

Software-Defined Networking (SDN) is a programmable network architecture that allows network devices to be controlled remotely, but it is still highly susceptible to traditional attacks such as Address Resolution Protocol (ARP) Poisoning, ARP Flooding, and others. The classification of benign network traffic from ARP Poison and ARP Flooding attacks...

Scene text detection is a complicated and one of the most challenging tasks due to different environmental restrictions, such as illuminations, lighting conditions, tiny and curved texts, and many more. Most of the works on scene text detection have overlooked the primary goal of increasing model accuracy and efficiency, resulting in heavy-weight m...

Locomotion is basic to all human needs. Modern-day transport has come a long way but still far away from perfection and all-around safety. Lane Detection is a concept of demarcating lanes on the roads while the vehicle is moving. Lane detection algorithm is crucial aspect in making intelligent driving systems that can be used in autonomous self-dri...

The main purpose of this paper is to develop an efficient machine learning model to estimate the electric power load. The developed machine learning model can be used by electric power utilities for proper operation and maintenance of grid and also to trade electricity effectively in energy market. This paper proposes a machine learning model using...

The challenges involved in the traditional cloud computing paradigms have prompted the development of architectures for the next generation cloud computing. The new cloud computing architectures can generate and handle huge amount of data, which was not possible to handle with the help of traditional architectures. Deep learning algorithms have the...

There is a huge concern over privacy of data and security breaches in the upcoming area pertinent to digital services. There is a phenomenal increase in social media sites so as the increase in the volume of data. Therefore, from the linguistic perspective, to understand and analyze the data has become a complex procedure. In this paper, the invest...

Recently introduced deep reinforcement learning (DRL) techniques in discrete-time have resulted in significant advances in online games, robotics, and so on. Inspired from recent developments, we have proposed an approach referred to as Quantile Critic with Spiking Actor and Normalized Ensemble (QC_SANE) for continuous control problems, which uses...

Social media like Twitter, Facebook, Instagram, and LinkedIn are an integral part of our lives. People all over the world are actively engaged in these social media platforms. But at the same time, it faces the problem of fake profiles. Fake profiles are generally human-generated or bot-generated or cyborgs, created for spreading rumors, phishing,...

Image classification is a combination of technologies: Image Processing (IP), Machine Learning (ML), and Computer Vision (CV). The classification of animals has been done in this work that are commonly found in the Indian scenario using two approaches: transfer learning and a custom‐built classification network, i.e., AnimNet. For transfer learning...

In the presented study, the authors have compared the performances of various machine learning and deep learning algorithms on two separate datasets: the Wisconsin Diagnostic Breast Cancer dataset and the Wisconsin Breast Cancer Dataset. We evaluated the extent of their ability to correctly classify the samples as “malignant” or “benign”. The respe...

Electric power load forecasting is an essential task in the power system restructured environment for successful trading of power in energy exchange and economic operation. In this paper, various regression models have been used to predict the active power load. Model optimization with dimensionality reduction has been done by observing correlation...

The proliferation of smartphones equipped with various sensors created a large user base, which includes robots (smartphone controlled) as well. The high processor enabled smartphones are used as software robots to track hour-to-hour activities of users using on-board motion sensors. The magnetometer, accelerometer, and gyroscope are non-permission...

Software-Defined Networking (SDN) is a networking paradigm that has redefined the term network by making the network devices programmable. SDN helps network engineers to monitor the network expeditely, control the network from a central point, identify malicious traffic and link failure in easy and efficient manner. Besides such flexibility provide...

Nowadays Unmanned Aerial Vehicles (UAVs) have tremendous applications to make human life easier or to automate the process, similar to other technologies. In this paper we are developing a vision-based navigation system for UAVs, so that a UAV can follow a human athlete autonomously. This work involves two sub tasks 1) To detect and mark the leadin...

In the light of recent events, an epidemic - COVID-19 which took the world by surprise and continues to grow day by day. This paper describes an idea to control the spread of disease by monitoring Social Distancing. As of now from where we stand, the only way to avoid further spreading is to maintain proper social distance. Combining the advanced d...

The COVID-19 pandemic has rendered social distancing and use of face masks as an absolute necessity today. Coming out of the epidemic, we're going to see this as the new normal and therefore most workplaces will require an identification system to permit employees based on the compliance of protocols. To ensure minimal contact and security, automat...

There have been tremendous improvements in deep learning and reinforcement learning techniques. Automating learning and intelligence to the full extent remains a challenge. The amalgamation of Reinforcement Learning and Deep Learning has brought breakthroughs in games and robotics in the past decade. Deep Reinforcement Learning (DRL) involves train...

Borders play an integral part in a country's security, but Borders are extremely vulnerable and prone to terrorist assaults, illegal smuggling of drugs, and unauthorized immigration. To achieve improved situation analysis, it is essential to fuse sensor-based detection with drone surveillance system to aid the present surveillance system. A wide ra...

Biometrics is the study of unique characteristics present in the human body such as fingerprint, palm-print, retina, iris, footprint, etc. While other traits have been explored widely, only a few people have been considered the foot-palm region, despite having unique properties. Prior work has explored the foot shape features using length, width, m...

Software defined networking is going to be an essential part of networking domain which moves the traditional networking domain to automation network. Data security is going to be an important factor in this new networking architecture. Paper aim to classify the traffic into normal and malicious classes based on features given in dataset by using v...

Visually impaired face various difficulties in their daily routine tasks. Though there are several modern assistive devices available in the market, they are not meeting the consumer requirements in terms of the level of assistance. We are providing an assistive solution for visually impaired that reduces the fraud cases (such as expired medicine)...

Internet of Things (IoT) refers to a wide variety of embedded devices connected to the Internet, enabling them to transmit and share information in smart environments with each other. The regular monitoring of IoT network traffic generated from IoT devices is important for their proper functioning and detection of malicious activities. One such cru...

In recent years, the Indian economy has shown rapid growth among all other major economies. India has been tragically reviled with issues like corruption and black currency, fake money notes is additionally major issues to it, in spite of a strong security feature are endorsed by RBI to print original currency. The advancement of color printing tec...

In India, nearly 12 million visually impaired people had difficulty in identifying the currency notes. There is a need to develop an application that can recognize the currency note and provide a vocal message. In this paper, a novel lightweight Convolutional Neural Network (CNN) model is developed for efficient web and mobile applications to recog...

Corridor segmentation is an essential component of the Indoor Navigation System (INS) for robotic activity. It is required for navigation from one place to another in the indoor environment for different applications such as autonomous corridor cleaning, robot-based customer service in hotels, malls, and hospitals. Global Positioning System (GPS) d...

One-Sixth of the world population is suffering from vision impairment, as per WHO’s report. In the past decades, many efforts have been done in developing several devices to provide support to visually blind and enhance the quality of their lives by making them capable. Many of those devices are either heavy or costly for general purposes. In this...

An Electronic Travel Aid (ETA) has become a necessity for visually impaired to provide them proper guidance and assistance in their daily routine. As the number of blind persons are gradually increasing, there is a dire need of an effective and low-cost solution for assisting them in their daily tasks. This paper presents a cane called R-Cane which...

Detecting a specific person from the crowd using drone along with some resource constraint device is a major concern which we are discussing in the paper. Combining the advanced algorithms and some smart hardware material, we will be finding a way to search for a missing individual in a crowd or at some location. We can also search for a person at...

Fruits are common items bought by every household. They are delicious to eat and rich in nourishment. However they may also adversely affect health if the fruits are from a diseased tree/plant. Moreover, Farmers may also loose lot of amount of profit if their plants get affected by some disease. In this article, the main objective/goal is to develo...

Automatic parallelization is necessary for all system. Every person wants the program to execute as soon as possible. Now Days, programmer want to get run faster the sequential program. Automatic parallelization is the greatest challenge in now days. Parallelization implies converting the sequential code to parallel code to getting better utilizati...

A vehicular ad hoc network (VANET) is the network of mobile devices as well as stationary objects that can communicate with each other. This technology comprises of both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) data transmission links. At present, vehicular mobility framework has a lot of limitations, which includes lack of real...