Category Archives: Uncategorized

Authors:-Bhavesh Gattani, Shamik Saha, Komal Gill

Abstract- In FMCG e-commerce, digital tactics are crucial in changing customer purchasing trends and behaviours. This study emphasises advertising strategies and the tactical application of consumer data as it investigates the significant effects of digital marketing and AI-driven tools on consumer patterns. By utilising cutting-edge technologies like chatbots, complex algorithms, and user behaviour analysis, businesses may gain profound insights into their clientele, facilitating customised and customer- focused online shopping experiences. This shift mostly depends on customised digital tactics that use customer data to design distinctive e-commerce experiences. This strategy also applies to advertising, using data-driven techniques to provide pertinent and compelling advertisements that are tailored to the unique requirements and tastes of FMCG customers. When it comes to FMCG e-commerce advertising, the use of digital and AI techniques has a big impact on customer engagement and purchasing behaviours. Businesses may maximise the impact of their ads by optimising the selection and delivery of their ads with the help of these tools’ insights. This study examines the impact of digital strategies on FMCG e-commerce customer behaviours by combining consumer data with insights from these strategies. Interestingly, these tactics—which are especially noticeable in social media postings and pop-up advertisements—stimulate instant wants, enable interactive interfaces, and encourage higher spending in the FMCG e-commerce space.

DOI: 10.61137/ijsret.vol.9.issue6.113

Published by: vikaspatanker

Authors:-Nripendra Singh, Himanshi Sankhla, Lalit Singh, Vartika Mudgal

Abstract- In the contemporary landscape of financial services, the convergence of finance and technology has ushered in a transformative era, prominently manifested in the phenomenon of Open Banking. This study seeks to unravel the intricate dynamics between finance and technology and their collective influence on the swift evolution of Open Banking.
The research engages in a comprehensive exploration of the symbiotic relationship between finance and technology, examining how technological innovations act as catalysts for financial sector advancements. Emphasizing the pivotal role of digitalization, artificial intelligence, block chain, and other cutting-edge technologies, our investigation delves into their collaborative impact, fueling the rapid expansion and adoption of Open Banking models across the global financial ecosystem.
Furthermore, the study critically analyses the implications of Open Banking on traditional financial institutions, fintech disruptors, and, most importantly, the end-users. Through empirical evidence and case studies, we aim to illuminate the tangible benefits and challenges posed by this paradigm shift, shedding light on how Open Banking fosters competition, enhances financial inclusion, and redefines customer-centric financial services.
The findings of this research not only contribute to the academic understanding of the subject but also offer valuable insights for industry stakeholders, policymakers, and practitioners. By elucidating the synergistic dynamics of finance and technology in the context of Open Banking, this study provides a roadmap for navigating the evolving financial landscape, fostering innovation, and ensuring a resilient and inclusive financial future.

DOI: 10.61137/ijsret.vol.9.issue6.112

Published by: vikaspatanker

Healthcare Transformation: The Synergy between Big Data and AI/strong>
Authors:-Kranthi Godavarthi

Abstract- Big data is another emerging modernization approach in healthcare that is changing the way patient care, streamlines the processes of healthcare facility management, and approaches disease control. When integrated with Artificial Intelligence (AI), it is revolutionizing how healthcare outfits process information, foresee outcomes and administer care. This article is dedicated to the promotion of modern big data, its use in the healthcare industry and how artificial intelligence strengthens its effectiveness.

DOI: 10.61137/ijsret.vol.9.issue6.462

Published by: Kajal Tripathi

Authors:-Madhur Narang, Kushagra Sahani,Asso. Prof. Dr. Neha Agrawal, Asst. Prof. Ms. Meenu Garg

Abstract- The stock market is the platform where anyone can buy and sell or trade shares of public companies, and for that predicting the stock price helps us to forecast the future value of the company shares, derivatives, and mutual funds. So, while doing predictions of the stock market we have to keep some key points in our mind such as No one can accurately predict the future movement of the stock market because the stock market is a composite and volatile system, and many factors can affect its performance.
To evaluate a company’s financial stability and performance, fundamental analysis is used. On the other hand, for reviewing historical price and bulk data, technical analysis has been carried out to recognize tendencies and patterns. Risk management, while investing in the stock market carries inherent risks, and to mitigate those risks, it is crucial to spread out investments and establish stop-market orders, and other techniques.
The aim of this paper is to suggest deep learning techniques in order to predict the stock prices of different companies such as AAPL(Apple), BAM (Brookfield Asset Management), and UBER and using two different models such CNN (Convolutional Neural Network) in CNN the paper uses One -Dimensional CNN (1D CNN) and LSTM (Long Short-Term Memory) uses Bidirectional LSTM.

DOI: 10.61137/ijsret.vol.9.issue6.111|

Published by: vikaspatanker

Authors:- Geofrey Mwamba Nyabuto

Abstract- The Internet as loosely defined, is a network of networks (Kumar & Deepa, 2015). Behind these networks are many social and economic opportunities that have become key enablers on many fronts. It is through the Internet that social media has become a possibility and whose use has directly or indirectly led to either the inclusion or exclusion of individuals from one or more aspects of social life. With inclusion, the use of social media has ensured that individuals have equal opportunities, access to resources and chances of participation regardless of their background and location. On the other hand, in exclusivity, social media or the Internet denies some of its users a chance to be part of the bigger picture due to one or more reasons.
This paper does a systematic review of the literature on the Internet, what it is and the different theories that seek to explain its originality or existence. The paper also reviews social media as a product of the Internet and how it has been used to enhance inclusivity and exclusivity in the same measure. It further discusses some of the contributions social media has made to societies as well as how it has been used to enhance inclusion and exclusion. With examples, the paper shows how social media has been incorporated and become part of our normal life. Lastly, it summarizes some of the strategies that can be implemented to minimize exclusion and how society plays a pivotal role in achieving this.

DOI: 10.61137/ijsret.vol.9.issue6.110

Published by: vikaspatanker

Authors:- Yash Jain, Srishti Mishra, Sparsh Jain, Pritish Kumar

Abstract- Carbon credits have had a significant positive impact on the financial performance of Tesla Inc. In 2021, carbon credit sales generated $1.58 billion in revenue, representing 3.3% of Tesla’s total revenue. In 2022, carbon credit sales generated $1.78 billion in revenue, representing 5% of Tesla’s total revenue. This revenue has helped to offset the rising costs of raw materials and other expenses and has contributed to Tesla’s record-breaking profitability in recent years. Carbon credit sales have also helped to improve Tesla’s profitability. In 2021, Tesla’s net income margin was 12.6%, significantly higher than the average net income margin for automakers. In 2022, Tesla’s net income margin was 14.7%, the highest in the company’s history. The impact of carbon credits on Tesla’s financial performance is expected to continue to grow in the coming years. Governments around the world are implementing carbon pricing policies to reduce greenhouse gas emissions. Carbon pricing policies can increase the cost of production for automakers. However, Tesla can offset these costs by selling carbon credits. Overall, carbon credits have had a positive impact on Tesla’s financial performance. They have helped to increase revenue, improve profitability, and reduce risk.

DOI: 10.61137/ijsret.vol.9.issue6.109

Published by: vikaspatanker

Authors:-Vishal Gangwani, Sumit Kumar Singh, Prathmesh Jadhav, Ayush Singh

Abstract- Virtual interviews have become a well-liked replacement for conventional in-person interviews in the ever-changing world of recruitment. This study explores the issue of whether virtual interviews are more effective than in-person ones. This study seeks to thoroughly examine the advantages and disadvantages of both interview formats by looking at various aspects, including candidate experience, hiring results, cost-efficiency, and environmental impact. The results of this study provide useful information for businesses looking to improve their hiring procedures and choose the interviewing technique that best suits their objectives. This research contributes to a comprehensive understanding of each format’s benefits by analyzing the distinct advantages and disadvantages of virtual and in-person interviews, eventually assisting organisations in making wise decisions about their interview tactics.

DOI: 10.61137/ijsret.vol.9.issue6.108|

Published by: vikaspatanker

Invoice Processing Using Robotic Process Automation
Authors:-M. Tech. Scholar Srishti Kaushik, Asst. Prof. Sushil Sharma

Abstract- This paper describes our recent effort to develop an automatic application to transform invoice processing in Finance operations. As a prime example of the technology’s potential for driving efficiency, Robotic Process Automation (RPA) can be applied to a number of finance and accounting operations, invoice processing. RPA Data Bot can automate data input, error reconciliation, and some of the decision-making required by finance staff when processing invoices. At the same time, automation is able to limit errors in such processes and reduce the need for manual exception handling. UiPath’s RPA Data Bot are able to constantly monitor a dedicated folder where invoices are saved by employees (or other Data Bot) in PDF format. Once robots detect the presence of an invoice in the folder, they begin to extract information from the document. Using intelligent Optical Character Recognition i.e., FOTT and natural language processing capabilities, Data Bot are able to read out the information that is visible on the invoice. After robots extract the key information from each invoice, they use their credentials to open the company’s database or enterprise resource planning system, if not already open. The robots then start processing the invoices one-by-one by transferring over the relevant invoice information. During this whole process, the Data Bot are also running background activities such as monitoring the dedicated invoice folder or its email address, performing basic checks to see if the company’s database is open, and verifying whether vendor information (e.g. VAT number) on the invoice matches what is already in the database.

DOI: 10.61137/ijsret.vol.9.issue5.107

Published by: vikaspatanker

Driver Dizziness Monitoring and Alert System
Authors:-Prateek Raj, Kinshuk Aneja , Seema Kalonia , Ajay Kumar Kaushik , Sunil Maggu

Abstract- The majority of accidents that have been reported in our nation are the result of drivers becoming distracted or feeling sleepy. Major accidents are often the result of driver fatigue that often results in the driver becoming drowsy and falling asleep. Nevertheless, there are early signs of exhaustion that can be identified before a serious situation arises, therefore identifying and detecting driver fatigue remains a research problem. Most traditional tiredness detection techniques rely on behavioral characteristics; others require expensive sensors, and others are intrusive and could distract drivers. In this research, we have developed a Dlib model and Python Driver Drowsiness Detection System. This approach can lower the amount of traffic accidents, and it is also simple to adopt because it doesn't call for direct interaction between the driver and the vehicle. The system uses adaptive thres holding to determine the driver's level of tiredness and recognizes facial landmarks. It also computes the Eye Aspect Ratio (EAR). The suggested strategy has been put to the test using machine learning techniques.

DOI: 10.61137/ijsret.vol.9.issue5.106

Published by: vikaspatanker

Automated Segregation Of Physical Loads Using PLC

Authors- Associate Prof. Mr. M. Rajashekar, Aavula Deepthi, Alle Abhilash, Kondaparthy Vamshi

Abstract- -This paper presents an automatic load segregation using plc. Heavy loads are often transported and handled in various industrial applications, such as manufacturing, mining, construction, and logistics. However, different types of heavy loads may require different methods of processing, storage, or disposal. Therefore, it is important to segregate heavy loads according to their characteristics, such as size, shape, weight, material, or function. This proposes an automatic material segregation system using PLC (programmable logic controller) to achieve this task. The system consists of three main components: a sensor unit, a controller unit, a relay unit and a segregation unit. The segregation unit performs the output actions based on the commands from the controller unit and directs the heavy loads to the corresponding bins or conveyors using actuators, such as DC motors, relays, solenoids, etc. The system is designed and implemented using SELPRO Version 5.4.3 and we can also implement by using software’s like Allen Bradley PLC and GX Works3 software. The system is tested and evaluated using different types of heavy loads and shows satisfactory performance in terms of accuracy, efficiency, and reliability. The system can be applied to various industrial scenarios where heavy load segregation is needed.

DOI: 10.61137/ijsret.ncascte-2023.105

Published by: vikaspatanker