@chitkara.edu.in
Associate Professor
Chitkata Business School, Chitkara University, Punjab, India
Ph.D, MBA with more than fourteen years of academic and four years of corporate experience
Ph.D, MBA
Neuromarketing, Consumer Behaviour, Marketing Management, Strategic Management, Services Marketing, Retail Marketing, Digital Marketing, Metaverse, Industrial Marketing, Customer Satisgaction, Customer Loyalty, Customer Relationship Management, Sales and Distribution Management, Brand Management
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Binay Kumar Pandey, Vinay Kumar Nassa, Digvijay Pandey, A. Shaji George, Monika Gupta, Pankaj Dadheech, and A. S. Hovan George
IGI Global
Population growth, urbanisation, industry, modernization, and digitalization increase residential, industrial, commercial, mining, radioactive, agricultural, hospital, and electronic wastes in the 21st century. Waste management is becoming the biggest global challenge. Waste management includes collecting, transporting, sorting, destroying, processing, recycling, controlling, monitoring, and regulating garbage, sewage, and other waste. Waste management preserves the environment, prevents pollution, and protects health. Global waste management is modern. Biological reprocessing, recycling, composting, waste-to-energy, bioremediation, incineration, pyrolysis, plasma gasification, ocean/sea disposal, etc. Waste management enhances life. This ensures future peace and wellness. Global health depends on waste management. This optimises waste management. This document discusses worldwide garbage management. It also offers the best waste management approach by critically reviewing previous researchers' findings.
Monika Gupta, Arshya Garg, and Anu Garg
IGI Global
The advent of technology backed by digitalization is bringing innovative and new ways in imparting higher education. The high speed of the internet readily available in the higher education institutions is further supporting such activities. Especially post-COVID-19, parents who used to keep an eye on children towards usage of smartphones began to provide such devices themselves to children for educational purposes. The AI-supported technology facilitated the process by creating artificial environment to understand the real-world. It provides a shield to adversities of the real situations. With the further advancement in the emerging field of metaverse, learners can view themselves as one of the participants on screen in the form of an avatar. Since the students are not aware of the challenges and limitations of such emerging areas, the responsibility of educationists is on the rise. The researchers have tried to review the scope of higher education resting on metaverse as one of the major aspects in the near future.
Monika Gupta, Maria Sugiat, Neeraj Anand, and Nitin Patwa
IEEE
The apparel market in India expanded by fifteen percent in 2022-23 as per a report by Economic Times indicating the growth in sales but this is merely due to increase in price. In actual, the volume has decreased by three percent (according to Clothing Manufacturers Association of India). With the increased usage of online shopping especially during and post Covid-19, led to an increase of product return too. The researchers have tried to analyze the factors responsible foe the return of various types of products in the e-commerce industry. For this, they have gathered responses of 132 undergraduate management students in Punjab on a five-point Likert scale using a structured questionnaire. The measurement scale comprising twenty-three items has been used to frame the questionnaire. Factor analysis technique has been applied and five dimensions have been evolved as ‘User Friendly’, ‘Customer Expectations’, ‘Return Service Process’, ‘Returns of Promotion Items’ and ‘Shipping Fee of Returns’ respectively.
Kushagra Gupta, Anushka Anushka, Manesh Ramkrishna Palav, Rajitha Jasmine R, V. Bharathi, and Monika Gupta
IEEE
Because of the progression of AI procedures, information is presently handled nearly proficiently. Such information extraction methods are many times utilized in a scope of situations, like web-based entertainment, business, casting a ballot, betting, foreseeing, and that’s only the tip of the iceberg. One of these significant spaces where displaying and information examination are vigorously used is healthcare. This network’s information assortment and handling are utilized to screen an individual’s normal exercises, confirm the information’s exactness, choose when a health related crisis is important, and that’s just the beginning. There are bounty research that pre-owned this methodology; a few utilized their own strategies, while others utilized pre-laid out techniques like AI, brain networks, profound learning, and others. In this paper, different methodologies that have been introduced in a couple of picked research articles are contrasted all together with break down sensor information. Both the examination procedures and the review’s decisions are incredibly changed and have various particular highlights.
Manikandan Rajagopal, Keyurkumar M Nayak, K. Balasubramanian, Irfan Abdul Karim Shaikh, Sunil Adhav, and Monika Gupta
IEEE
Artificial intelligence (AI) has numerous applications in supply chain finance, including the ability to streamline processes, improve decision-making, and reduce costs. This abstract will discuss some of the key ways in which AI is being used in supply chain finance. One major Using AI in the Supply Chain finance is in risk management. By analyzing data from a variety of sources, including historical transaction data and external market data, AI can identify potential risks and suggest strategies for managing them. For example, AI can be used to predict which suppliers are at the greatest risk of financial distress, allowing companies to take proactive measures to minimize the impact of any disruptions. Another key Using AI in the Supply Chain finance is in fraud detection. By analyzing large volumes of data in real-time, AI can spot deviations from the norm that may point to fraud. This can help companies to prevent fraud and minimize losses. AI can also be used to optimize working capital management. By analyzing data on inventory levels, order volumes, and payment terms, AI can help companies to optimize their cash flow and improve their working capital position. For example, AI can help companies to identify opportunities to negotiate more favorable payment terms with suppliers or to optimize their inventory levels to minimize the amount of cash tied up in inventory. Finally, AI can be used to improve supply chain efficiency and reduce costs. By analyzing data on order volumes, shipping times, and other factors, A.I. may aid businesses in identify opportunities to their supply network needs improvement processes and reduce costs. For example, AI can aid businesses in determining opportunities to consolidate shipments or to optimize their routes to reduce transportation costs. Now a days AI has numerous applications in supply chain finance, including risk management, fraud detection, working capital management, and supply chain optimization. By leveraging the power of AI, companies can improve their financial performance, reduce costs, and enhance their overall competitiveness.
P.G. Thirumagal, Aqeel Hadi Abdulwahid, Ali HadiAbdulwahid, Deepak Kholiya, Raji Rajan, and Monika Gupta
IEEE
An breakthrough technology called the Internet of Things (IoT) provides workable and dependable solutions for the modernization of a few locations. Systems based on the Internet of Things are being created to monitor and maintain horticulture farms with the least amount of human intervention. The proposed model is a framework for a smart water system that predicts how much water will be needed for a harvest using machine learning analysis. The three most crucial factors to consider when estimating how much water will be present in a given farming area are wetness, temperature, and moistness. Agriculture is one of the most important factors in the economic development of any country. In many non-industrialized nations, horticulture plays a significant and critical role in the development of their economies. India, one of the world's top producers of vast quantities of various harvests, genuinely employs conventional agricultural methods. Ranchers must increasingly produce more food of the highest quality while simultaneously coping with challenges associated to climate change adaptation. IoT-based and machine learning-based smart horticulture would help ranchers by continuously monitoring their crops and providing advice on harvesting and composting. This study's major objective is to provide a Smart Agribusiness framework based on the Internet of Things (IoT) that would help ranchers by providing recommendations based on a variety of variables, such as temperature, pH, wetness, and precipitation.
Keyurkumar M Nayak, P. Kiran Kumar Reddy, Sweta Priya, T Srinidhi, Galiveeti Poornima, and Monika Gupta
IEEE
Machine learning is particularly crucial in the context of fraudulent messages in virtual entertainment due to the degree of biological and cultural concerns. Anyone can make a message that becomes a web phenomenon, whether it is real or phoney. Considering countries like India, the ideological organisations during general decisions actually act in this way by disseminating false information around the nation through online entertainment events. While some of the communications may be genuine, the majority are false. Spam communications and phoney messages carrying false information can propagate across online social networks. Several machine learning techniques are used by analysts to differentiate between spam communications and fake news. Customers are creating and sharing more data than ever before as a result of the continuous usage of virtual entertainment platforms, some of which are ludicrous and unrelated to the actual world. Computerizing the classification of text as false information could be challenging. Our study looks at a number of print characteristics that can be utilized to tell real text from phone. Based on these qualities, we train various machine learning algorithms using various training methodologies and assess their efficacy using four real-world datasets. According to an exploratory assessment, the student's technique in our suggested group is better than it was during her one-on-one tuition.
Anganabha Baruah, Valli Madhavi Koti, Vivekanand Pandey, Savita Mohan Gungewale, N Srikanth Reddy, and Monika Gupta
IEEE
A recommendation system's goal is to expect client interests and derive their points of view. This system can furnish clients with the data they require in light of their necessities and keeping in mind that thinking about their inclinations. To improve recommendations, the information should be all the more completely dissected. At the point when individuals take in critical chilly, their safe systems can be hindered. At the point when there is no physical movement during the day, flu occasionally influences invulnerability and respiratory lot infection. Physical movement fortifies an individual's insusceptible system. The people who overchill are more inclined to infections since it requires more work to keep them at an ordinary internal heat level. This study made a system for anticipating physical fitness utilizing information on calorie consumption, race, orientation, inclinations, and medical issue. The proposed recommendation system makes practice recommendations in light of the client's inclinations while considering comorbidities, geographic areas, and exercise and eating ways of behaving.
K V Nagesha, G. Yedukondalu, Prashant Atmakuri, S B G Tilak Babu, Pulluri Sreenivasgoud, and Monika Gupta
IEEE
Since artificial intelligencetechnology has been developing recently, it is clear that many industries are benefiting from it. In this occasion, artificial intelligence has demonstrated pivotal to the sports area. It has been urgent in guaranteeing that the business changes from obsolete practices to additional contemporary ones. Artificial intelligence (computer-based intelligence) can be seen as a supporting innovation that explicitly upholds competitors' actual instruction preparing through strategies like information examination and recreation of preparing situations. Albeit however research on artificial intelligence is still in its beginning phases, it is critical to examine how it very well might be utilized in sports preparing on the grounds that this state-of-the-art innovation might here and there at any point make it more straightforward for people to truly prepare. This study starts by inspecting the earlier work on computer-based intelligence applications. This paper explores three explicit circumstances of man-made intelligence application in sports preparing and depicts the key ideas in view of the fundamental thought and related research discoveries of computer-based intelligence. This study centers around the nearby association between artificial intelligence (simulated intelligence) and actual schooling guidance and underlines the advantages of simulated intelligence, like its utilization, straightforwardness, and development.
Rajni Bala, Shilpi Harnal, and Monika Gupta
IEEE
These days, QR codes are more widely used. Numerous benefits, including quick reading speed, error correction, 360-degree reading, multilingual support, robustness, and a broad range of applications, are offered by QR codes. The education industry is using QR codes on a large scale to make teaching and learning effective. In a few universities and colleges, faculties are using QR code technology in the classroom as well. The use of QR codes dramatically increased during COVID 19. It was the time when the whole world was trying to discover the potential of QR codes in different sectors. Now, QR codes have become an essential part of our lives. Almost every industry uses QR codes, including entertainment, education, sports, FMCG, textiles, restaurants, healthcare, and tourism. The objective of the study is to determine the different ways to use QR code in classroom and to find the factors that develop teachers’ perception of use of QR codes in the classroom. The study also determines the role of QR code in making teaching learning effective. The data was collected from 50 faculty members of randomly selected five private universities of Haryana region through an online survey. The study found that in spite of multiple uses of QR codes in teaching, only a limited number of faculty members are using this technology in the classroom. The reason is that many teachers are not aware of different ways of using QR code in classroom. The study comes up with different factors that play an important role in developing teachers’ perception of use of QR code in classroom.
Shubhi Bansal and Monika Gupta
IGI Global
AI, when applied to the domain of neuromarketing, can help to model consumers' preferences, which can be leveraged by marketers in creating products or brand strategies that yield a good market value. Unlike focus groups and surveys where there is a possibility of masking the actual opinions and feelings of people to certain products and stimuli, AI can help to effectively capture data regarding impact of brain signals in response to certain stimuli. This study will be largely focused on connecting the dots between/forming linking/developing a connection between artificial intelligence and neuromarketing. Using artificial intelligence (AI) can help to bring personalization instead of standardization, which when combined with neuromarketing, can help to build effective advertising campaigns and influence customers' buying decisions. The content posted by consumers on social media, browsing behavior, and online shopping provides valuable personal information. This data when mined and processed using AI technologies can help to recognise patterns in consumer behavior.
Lalitha Krishnasamy, Rajesh Kumar Dhanaraj, Monika Gupta, Priti Rai, K. Sruthi, and Gopika T
IEEE
Diabetic retinopathy is one of the diabetes consequences that affects the eyes. This is caused by damage to the blood vessels in the retina, the light-sensitive tissue in the rear of the eye. It may create no symptoms at first, or it may cause minor eyesight difficulties. When the blood vessels become damaged, they may leak and this leakage can cause dark spots on our vision. The DR can be detected by finding the Hard Exudate present in it. The deep networks are becoming deeper and more complex. So that adding more number of layers to a neural network can make it stronger for image related tasks. But the main disadvantage in adding more layers is that, it may greatly reduces the accuracy of the image and also the data models are complex. In order to overcome this drawback, Recurrent Neural Network can be introduced. The fundamental benefit of using a recurrent neural network is that it can represent a collection of data in such a way that each pattern may be presumed to be reliant on the one before it. It can process inputs of any length. Even if the input size is large, the model size will not change. It makes the training process faster and attains more accuracy while compared to other neural networks. This method greatly reduces the loss of accuracy because each layer knows the information of the top layers while updating the weights. This Recurrent Neural Network has more number of parameters , so it is obvious that it can produce better result as compared to other net.
Monika Gupta, Sandhir Sharma, and Shubhi Bansal
IEEE
Neuromarketing is an emerging area of interest to big corporates. The companies are investing huge capital in neuroscientific technologies to understand the impact of branding, advertising and other external stimuli on human brain and formulating the marketing strategies accordingly to influence the perceptions of customers in the target market. This is creating the need for certified professionals both on provider side as well as client side such as data analysts, consultants and managers in neuromarketing. This has motivated the researcher to analyze the current and future scenario of formal education in neuromarketing. The study is based primarily on information available online during the Covid times. The researcher has also made an attempt to know the viewpoints of youth as well as educationists in this context.
Monika Gupta, Manikandan Thirumalaisamy, Salim Shamsher, Anamika Pandey, Deepa Muthiah, and Nakirekanti Suvarna
IEEE
The healthcare sector is under pressure to embrace new technologies that are available on the market in order to enhance the overall quality of their services. Telecommunications systems are combined with computers, interconnection, mobility, data storage, and information analytics. Technology that is centred on the Internet of Things (IoT) is the order of the day. Because of the limited availability of human resources and infrastructure, it is becoming more necessary to monitor chronic patients on a continual basis as their conditions worsen. A cloud-based architecture, which can handle all of the aforementioned concerns, may offer effective solutions to the health-care sector. In order to create software that combines cloud computing and mobile technologies for health care monitoring systems, we have set a goal of developing software. A technique developed by Higuchi is used to extract steady fractal values from electrocardiogram (ECG) data, which has never been tried before by any other researcher in the area of creating a computer-aided diagnostic system for arrhythmia. Based on the findings, it can be concluded that the support vector machine has achieved the highest possible classification accuracy for fractal features. While being compared to the other two classifiers, which are the feed forward and feedback neural network models, the support vector machine outperforms them both. In addition, it should be highlighted that the sensitivity of the feed forward neural network and the support vector machine provide results that are comparable (92.08 percent and 90.36 percent, respectively).
Monika Gupta, Salim Shamsher, Manikandan Thirumalaisamy, Anamika Pandey, and Nakirekanti Suvarna
IEEE
The most challenging problem in today's technologically advanced society is how to enhance the health of the elderly. Falling is the most frequent cause of serious injury and early mortality among elderly people. As wearable sensors improve their capacity to detect falls, the demand for these devices has grown. This implies that the system has a low social and financial effect on society. This means that automated fall detection systems and vital signs assessment systems are now required for even basic daily tasks carried out by the elderly. Healthcare solution is split into three sections: sensing, querying, and storing amongst others. RF transceivers are employed in the sensing section to detect the presence of tagged patients nearby. An SMS is used to transmit a request to the querying service, which then receives it from the GSM network. In the storage space, the patient information is well organised. According to the results, the proposed method was 96.43 percent accurate, 94.06% precise, 94.62% recall, and 94% Fl-score effective. The system's ability to be tracked through low-cost GSM technology greatly increases the system's use. A multifaceted and flexible system with easy access has been shown. It has the ability to make daily tasks simpler and more efficient as a consequence of its unique design.
Monika Gupta Vashisht and Vishal B. Soni
Springer Singapore
Monika Gupta Vashisht and Reena Grover
IEEE
Increasing unemployability of engineering graduates motivated the researcher to conduct the research. An attempt has been made to profile employable engineering students on the basis of demographic variables. Data has been collected using convenience and judgment sampling via a structured questionnaire in Mohali (Punjab) and Ghaziabad (U.P.). Clustering has revealed a group of students focused on learning employability skills (Practicable Students) on one hand and a group of students not focused on learning employability skills (Impracticable Students. The study can be further conducted in other cities and in other discipline too.
Monika Gupta Vashisht and Vishal B. Soni
IEEE
Shifting behavior of farmers from agriculture to other fields is alarming. The study undertaken is focused on inculcating agripreneurial skills for better farming environment. For this, the major factors affecting farming were identified. Farmers residing in rural areas have been approached by a team of management graduates based on convenience and judgment. Initiatives taken by central and state government from time to time in this context were also taken into consideration. Factor Analysis, a regression based data mining technique, has been applied to find major dimensions causing farming distress. Based on these dimensions, innovative ways to manage agripreneurship have been analysed. Besides this, other areas such as farm tourism have also been explored. An attempt has been made to motivate youth and women in family of farmers to provide support in this initiative.
Students and their parents have become more and more aware of the importance of gaining higher education in India. Government of India, as well as state governments, has been framing various policies to promote higher education in various fields such as engineering, management, and hotel management, medical and allied disciplines. An attempt has been made to analyze the expectations of students pursuing higher education in the state of Punjab and Haryana in India. For this, Clustering approach has been used. Students studying in selected engineering colleges have been approached. Two clusters have been evolved: Career-Oriented Students and Society Conscious Students. This research gives further directions for the future as the same can be conducted in other institutes and in other cities, states, and countries too.