Professor Piyush Maheshwari
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Professor Piyush is a recognized technology leader, educationist and distributed systems researcher, with many years of academic and corporate R&D experience. His current research interests are IoT- and cloud-based software systems, enterprise architecture, and smart city applications. He had worked as an academic at UNSW-Sydney, Griffith University-Australia, and Amity University Dubai. He had also extensively contributed to R&D and innovation management of centers of excellence in companies like IBM, Ericsson, and DELL.
Professor Piyush is a senior member of The Institute of Electrical and Electronics Engineers (IEEE).
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Item A Framework to Implement Blockchain in Higher Education Institutions(British University in Dubai, 2021) Al Mansoori, Suaad; Maheshwari , PiyushThis paper presents a framework to implement business solutions based on blockchain technology (BCT) for the higher education institutions (HEIs). The first part of the paper provides an overview of the blockchain technology, its im-plementation in the sector, and its advantages. The second part discusses the common challenges of implementing technology and then identifies higher educa-tion stakeholders' insights. Getting stakeholders' insights is the root of creating a comprehensive framework to help higher education institutions successfully im-plement the solutions based on BCT.Item A Correlational Investigation of Personal Medical Data Safety and Blockchains(IEEE, 2022) Louis, Vernon; Maheshwari, PiyushAny emerging technology needs a catalyst to help its adoption into mainstream utilization. The blockchain has been around for over 10 years now and although it has been widely adopted in the crypto asset world, its real-world implementation in the healthcare domain has been relatively slow. Considering the advantages possessed inherently by blockchains, it is perplexing as to why it has not found widespread acceptance. With most of the proposed implementations focusing on health records and patient centered access control, it was necessary to gain status of public perception of firstly, their health records, secondly, their outlook on the security aspects of their health data and finally understand to what extent have blockchains and its existence has infiltrated into the general populous. The Box’s M test significance value, p-value= 0.613, helps establish a correlation between an individual knowledge of blockchains and their ease in use of electronic devices. The ANOVA test was used to reject any correlation between an individual’s age and their perception of healthcare data safety and accessibility. The results of this analysis would help provide understanding on the feasibility of healthcare blockchain implementationsItem AGENT-BASED SIMULATION FOR UNIVERSITY STUDENTS ADMISSION: MEDICAL COLLEGES IN JORDAN UNIVERSITIES(SSRN, 2023) Khalil Assayed, Suha; Maheshwari, PiyushMedical colleges are considered one of the most competitive schools compared to other university departments. Most countries adopted the particular application process to ensure maximum fairness between students. For example, in UK students apply through the UCAS system, and most of USA universities use either Coalition App or Common App, on the other hand, some universities use their own websites. In fact, a Unified Admission Application process is adopted in Jordan for allocating the students to the public universities. However, the universities and colleges in Jordan are evaluating the applicants by using merely the centralized system without considering the socioeconomics factor, as the high school GPA is the essential player their selection mechanism. In this paper, the authors will use an Agent Based model (ABM) to simulate different scenarios by using Netlogo software (v. 6.3). The authors used different parameters such as the family-income and the high school GPA in order to maximize the utilities of the fairness and equalities of universities admission. The model is simulated into different scenarios. For instance, students with low family income and high GPA given them the priority in studying medicine comparing with same high school GPA and higher family-income, as a results, after several rotations of the simulation the reputation of medical schools are identified based on students’ preferences and seats’ allocated as it shows that high ranking universities are mainly allocated with have high cut-off GPA score.Item Agent-Based Modelling and Simulation of Crowd Evacuation: Case Study for Electric Train Cabin(IEEE, 2023) Maghaydah, Safwan; Maheshwari, Piyush; Mohammad Alomari, KhaledThe agent-based simulation is a cutting-edge example of a fresh and clever technique intended to fulfil these goals. Numerous academics and researchers investigated the crucial merits, applicability, and contributions of this approach in a range of extreme situations and catastrophic scenarios. Their numerical analysis and mathematical simulations showed that the agent-based simulation framework is essential for providing a thorough knowledge of pedestrian behavior and human mobility in difficult emergency conditions. This work uses egress modelling to explore crew procedures' impact on evacuating train cabins under different fire scenarios. Based on the numerical simulations and analyses conducted via the Netlogo software package, Author’s found that two employees (contracted by the railroad company) in the lounge coach and two train hosts in the first-class coaches under emergencies achieve an efficient step toward evacuating a larger number of passengers. Nonetheless, passengers should be aware and familiar with the locations of these exit points, emergency signs, and egress paths to avoid any congestion, stampedes, and social attachment that may contribute to losses of life and delay the evacuation process. Also, an agent-based simulation is remarkably practical for determining intelligent practices and effective methods that can be adopted and followed to accelerate the evacuation process compared with other methods that are very difficult or unethical to apply, such as subjecting a group of people to a real fire event and predicting some methods to evacuate them based on the results.Item A survey on Augmented Virtual Reality: Applications and Future Directions(IEEE, 2020) Sirohi, Preeti; Agarwal, Amit; Maheshwari, PiyushAugmented Reality (AR) is an evolving technology that reforms different fields like education and learning, manufacturing, health, etc. Companies are experiencing new changes in their process due to the adoption of new technology for their performance improvement and cost reduction. Therefore, research made on AR must consider an interdisciplinary review to understand its role as a hybrid model and generate an organized framework. The integration of emerging technologies has helped in the overall transformation of the business for a better chance. The research investigates the existing integration of innovative augmented reality (AR) technology, which has different application areas. Based on the literature survey, future research directions can be derived for the researchers and practitioners.Item Blockchain in Emission Management: Opportunities and Trends(IEEE, 2023) Ali, Tagreed; Maheshwari, PiyushThe emergence of blockchain technology in different use cases is remarkable. Blockchain has the potential of transforming global business, particularly in the field of emission management. The unique features of blockchain technology encouraged scholars and startups to invest in utilizing blockchain within emission management, however, there is a need to review the literature related to blockchain and its potential to advance emission management and climate change. Hence, this paper provides an overview of the current trends as well as future opportunities that can be pursued in this space.Item Blockchain Technology for Hospitality Industry(Springer, 2011) Khanna, Abhirup; Sah, Anushree; Choudhury, Tanupriya; Maheshwari, PiyushBlockchain technology and its economic, social, and technological implications, have seen significant upsurge among researchers across the globe. Blockchain has revolutionized the concept of transactions by enhancing their security and efficiency. The blockchain technology is primarily associated with Bitcoin but however, the technology has the potential to go far beyond crypto currencies across various verticals. In a recent survey performed by Deloitte, more than 53% of the responds across various industries see blockchain tech nology as a critical requirement for their respective organizations[4]. The hospitality industry is one such domain where blockchain can prove enormously beneficial. The paper explores major application areas that involve the applicability of blockchain technology in the hospitality industry. The work investigates the implications of blockchain technology in enhancing operational efficiency, in creased revenue and improved security and privacy for the hospitality industry. The paper establishes a link between blockchain technology and the hospitality sector and subsequently analyses recent works and case studies. A two-step research study has been introduced to present a systematic review of some of the main contributions in the literature that focuses on the integration of the blockchain technology and hospitality industry. The article adds to an interesting concept of blockchain technology, and its current research trends with respect to the hospitality industry and their various areas of application.Item HEI-BCT: A Framework to Implement Blockchain-Based Self-Sovereign Identity Solution in Higher Education Institutions(IEEE, 2022) Al Mansoori, Suaad; Maheshwari, Piyush— Blockchain Technology, a decentralized and distributed ledger, has received extensive attention of industries to revamp operations and functionality of organizations. Implementing smart technologies such as Blockchain is an attractive solution for organizations, including the Higher Education Institutions (HEIs). Self-Sovereign Identity is one of Blockchain applications that promises to provide a more efficient management systems for organizations. This paper explained how a Self-Sovereign Identity using Blockchain technology can be used to manage students’ credentials in HEIs. It also proposes a framework to successfully implement the solution. This paper answers two questions: “How to use Self-Sovereign Identity as credentials management system” and “What are the major steps to be followed when implementing a BCT-based solution?”Item Blockchain-Powered NFTs: A Paradigm Shift in Carbon Credit Transactions for Traceability, Transparency, and Accountability(Springer, 2023) Khanna, Abhirup; Maheshwari, PiyushThe adoption of carbon credit systems has emerged as a pivotal strat egy in addressing climate change and promoting sustainable environmental prac tices. This research paper delves into the multifaceted landscape of carbon credit systems, specifically focusing on the challenges inherent in their design and im plementation. We investigate the innovative use of Non-Fungible Tokens (NFTs) as a transformative approach to carbon credits, exploring the intricacies of NFT structures tailored for carbon credit trading. Furthermore, the paper presents a comprehensive examination of the system architecture underpinning a block chain-enabled NFT trading platform for carbon credits. The architectural frame work's design and components are meticulously scrutinized to ensure transpar ency, security, and efficiency in the trading ecosystem. The research also dissects the intricate functionalities that empower the blockchain-NFT trading system, fa cilitating seamless transactions and traceability. A pivotal facet of this study is a compelling case study spotlighting the application of a Blockchain-NFT trading system for Agricultural Carbon Credits within a rural farming community. The case study highlights the tangible benefits reaped by farmers through the innova tive system, shedding light on how the technology incentivizes sustainable farm ing practices and offers an additional revenue stream.Item Heartbeat Abnormality Detection in Phonocardiogram Signals using Wavelet Time Scattering and Optimized KNN Classification(2023) Tiwari, Shamik; Maheshwari, PiyushHeart auscultation continues to play an essential role in heart health diagnosis. However, many places worldwide have a shortage of suitably qualified medical practitioner’s adept at this ability. This highlights the critical need to develop accurate automated systems for evaluating Phonocardiogram (PCG) data. PCGs are acoustic recordings that capture the noises made by the heart during its systolic and diastolic cycles. To solve this issue, we suggest using Wavelet Time Scattering with an optimized XGBoost classifier and K-Nearest Neighbors (KNN) classifier to detect irregular heartbeats in PCG signals. The results are promising, as the optimized KNN classifier obtains an impressive accuracy rate of 92.5% when combined with five-fold cross-validation, which is better than XGBoost classifier, which gains 87.93%. This demonstrates the efficacy of the optimized KNN in improving the automated interpretation of PCG data and assisting in the early diagnosis of heart-related problems.Item Immersive Learning in Higher Education Institutions(2022) Almehrzi, Mouza; Maheshwari, PiyushDistance education is one of the techniques that the Ministry of Education provides for students to pursue study, especially in the COVID-19 pandemic. So, the initial experiences of distance education proved several problems, including lack of understanding of the subjects which impact students' performance, lack of collaboration among students, and the massive information students obtain daily. The idea of an immersive learning environment emerged as an educational tool that supports and assists distance learning by using virtual world methods and modern applications to support virtual learning. The study plan of the learners should be modified to align with the Immersive Learning Environment. This research addresses how distance learning and the immersive learning environment affect students' learning, as well as how students benefit from the application of immersive learning in developing the level of academic performance.Item MPox-DenseConvNet: A Transfer Learning Based Convolutional Neural Network for Monkeypox Detection and Assessment using Color Models(IEEE, 2023) Tiwari, Shamik; Maheshwari, PiyushMonkeypox, a zoonotic orthopoxvirus, unintentionally produces smallpox-like sickness in people, though with a far lower death rate. Despite the fact that Deep Networks have been extensively used for visual inspection of such diesases, the majority of works have frequently relied their analysis on the results produced by a particular network without taking the response of the colour channels to classification findings into account. Deep learning has recently shown to have enormous potential for image based diagnosis, including the detection of skin cancer, the identification of tumour cells, and the COVID-19 patient diagnosis through chest radiography. As a result, a similar application may be used to identify the sickness associated with monkeypox as it impacted human skin. This image can then be obtained and employed to identify the illness. This work focused on investing the prominent color channel for Convolution Neural Network (ConvNet) based monkeypox classification using skin images. For this purpose, a transfer lerning based classification architecture named MPox-DenseConvNet with fine tuning is designed. Three colour channels namely RGB, HSV and YCbCr are analyzed using proposed MPox-DenseConvNet. The outcomes demonstrated that the colour channel employed had an impact on the performance of the classification. The results also confirmed that the HSV color channel has outperformed of all the colour channels taken into consideration.Item Polycystic Ovarian Syndrome Identification through Self-Attention Guided Convolutional Neural Network(Institute of Electrical and Electronics Engineers Inc., 2023) Tiwari, Shamik; Maheshwari, PiyushPolycystic Ovarian Syndrome (PCOS) is a hormonal disorder that impacts women during their reproductive years, marked by indicators like multiple ovarian follicles or cysts that can be visualized through ultrasound imaging. Convolution Neural Networks (ConvNets) have been enhanced with self-attention mechanisms to improve their efficacy across a variety of computer vision applications, according to researchers. This study uses self-attention to improve the effectiveness of a ConvNet classifier in classifying PCOS, yielding a superior 99% accuracy, exceeding the 96% accuracy of a regular ConvNet classifier.Item PCOS-WaveConvNet: A Wavelet Convolutional Neural Network for Polycystic Ovary Syndrome Detection using Ultrasound images(IEEE, 2023) Tiwari, Shamik; Maheshwari, PiyushWomen of reproductive age are susceptible to polycystic ovarian syndrome (PCOS), a hormonal condition. Multiple small follicles or cysts on the ovaries are one of the symptoms of PCOS and can be found using ultrasound imaging. Wavelet ConvNets have been applied in various applications, including image classification, object detection, and biomedical signal analysis. A Wavelet ConvNet is a type of deep learning model that applies wavelet transformation to input data before feeding it into a convolutional neural network. The wavelet transform is a mathematical technique that breaks down a signal or image into a series of sub-bands, each representing different frequency components of the original data. In this work, A 2D Discrete Wavelet Transform (2D-DWT) with the Haar wavelet is applied to each image. The resulting sub-bands namely Low-Low (LL), Low-High (LH), High-Low (HL), and High-High (HH) are concatenated to create a 4-channel feature map. Further, this concatenated feature map is fed into the ConvNet for classification. The PCOS-WaveConvNet classifier has attained 99.7% accuracy which is better than a usual ConvNet model.Item Precision Agriculture for Medicinal Plants: A Conjunction of Technologies(IEEE, 2022) Khanna, Abhirup; Jain, Sapna; Maheshwari, PiyushRecent advancements in the fields of artificial intelligence (AI) and blockchain technology have paved the emergence of new-age agricultural practices. Deep learning, one of the subsets of AI has shown remarkable results in cases of crop classification, disease detection and pest identifications whereas blockchain technology has enabled the creation of trusted supply chains and maintains a balance between the demand and supply of agricultural products. The two new age technologies when combined with the existing infrastructure of IoT and Cloud computing create a formidable alliance for precision agriculture. In this work of ours, we propose a conjunction of all four technologies as one single solution for the cultivation of medicinal plants. The industry for medicinal plants still hasn’t seen the impact of Agriculture 4.0 and is most dependent on traditional practices. Bringing along the practices of precision agriculture supported by ICT technologies has the potential to solve problems pertaining to environmental conditions, accessibility to the global markets, plant growth monitoring, non-uniformity of ingredients, and pre and post harvest data processing.Item Predicting Cardiovascular Disease in Patients with Machine Learning and Feature Engineering Techniques(IEEE, 2022) Tyagi, Sapna; Sirohi, Preeti; Maheshwari, PiyushCardiac disease prediction and detection are among the most difficult and important jobs encountered by medical practitioners. Heart disease can be caused by a range of factors, including a sedentary lifestyle, stress, alcohol, cigarette intake, and so on. The current prediction algorithms focus on forecasting the illness label though the likelihood of getting the condition is still unknown. This study is conducted to forecast the heart disease progression well in advance so that essential action can be taken before the condition becomes severe. As a result, the research proposes a model for predicting the likelihood of heart disease incidence using logistic regression capabilities.Item Reading Political Sentiment and mood of the Electorate through Twitter Data(IEEE, 2020) Khanna, Abhirup; Bansal, Ananya; Agarwal, Amit; Maheshwari, PiyushIn this day and age of social media, Twitter plays an important role when it comes to election campaigning. Twitter has been seemingly popular among leaders of the western world, but the advent of accessible and affordable internet connectivity had led to its inroads in the India electoral ecosystem. Major political parties have their twitter accounts with millions of active followers. Government departments and respective ministers are now using Twitter as a means of publicizing public interest schemes among their followers. Twitter is being used as a tool for addressing current followers and appealing to potential future voters. In this paper, we present a popularity analysis between two national parties, i.e. BJP and INC. The work discusses the extent of positive popularity each party enjoys in various cities in India. Twitter data is harvested for analysis from seventeen different cities spread across four different zones in India. We examine the growth of BJP and its prominence in certain social groups. The paper talks about the rise of Prime Minister Narendra Modi and his emergence as a nationwide leader. Finally, we present positive takeaways from our analysis that may interest any political pundit of Indian democracy.