Dr.(Mrs.)Varsha Ganatra

Ms. Mahika Bhaven Shah

Artificial Intelligence has gained immense attraction across diverse fields such as healthcare, finance and education (Marr, 2020). Cybercriminals increasingly leverage AI to enhance their malicious activities. This research examines various forms of digital crimes facilitated by AI including identity theft, deepfake technology and automated phishing attacks highlighting the challenges & gaps posed by these technologies to traditional legal frameworks. This research paper explores the pressing need for ethical intervention in the context of AI- driven digital crime focusing on the implications for security, privacy and societal norms. It aims to explore the necessity of ethical intervention in mitigating these risks and ensuring that AI serves the public good rather than enabling criminal activities. Descriptive research is conducted for this research as it seeks to provide an overview of issues, identify concerns and outline the need for ethical standards and interventions. While scholars have examined various dimensions of AI ethics including algorithmic accountability, transparency and bias (Jobin etal., 2019) there remains a scarcity of studies that specifically address the proactive ethical interventions required in combating the detrimental use of AI in digital crime.

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Chapter 1 : A Study on the need for Ethical Interventions in AI wave of Digital Crimes

ABSTRACT

Author Biography

Dr.(Mrs.)Varsha Ganatra
Associate Professor and Head of Department

Department of Commerce

Vivekanand Education Society’s College of Arts, Science and Commerce (Autonomous) Sindhi Society, Chembur, Mumbai - 400071.

Ms. Mahika Bhaven Shah

M.COM - 2 (Accountancy), Vivekanand Education Society’s College of Arts, Science and Commerce (Autonomous), Sindhi Society, Chembur, Mumbai - 400071.

KALAISELVI R

KALASALINGAM ACADEMY OF RESEARCH AND EDUCATION

BERLIN JOSHUA SP

KALASALINGAM ACADEMY OF RESEARCH AND EDUCATION

JAYA SHREE K

KALASALINGAM ACADEMY OF RESEARCH AND EDUCATION

Rural healthcare continues to be a pressing issue in many developing countries, where limited infrastructure, a shortage of healthcare professionals, and insufficient medical supplies hinder the delivery of quality healthcare services. Geographic isolation, poor transportation facilities, and low health awareness among rural populations add to the complexity of the problem. These issues result in delays in diagnosis, treatment, and follow-up care,further increasing health disparities between urban and rural communities.

This research paper aims to explore both the challenges and the emerging opportunities in rural healthcare delivery. Through qualitative analysis of recent academic literature, the study evaluates the impact of innovative solutions such as telemedicine, mobile health (mHealth) applications, electronic health records, and government health schemes. It highlights how these technologies and policy initiatives can significantly improve accessibility, efficiency, and patient engagement when properly implemented. Furthermore, the paper emphasizes the importance of culturally appropriate care, local workforce training, and digital literacy to ensure sustainable improvements in rural health systems.

The findings suggest that overcoming rural healthcare barriers requires a collaborative approach involving government agencies, healthcare providers, technology developers, and local communities. While there are significant hurdles, the integration of digital tools, targeted policies, and capacity-building programs opens up new possibilities for strengthening healthcare delivery in rural areas. This paper contributes to ongoing research by offering insights and recommendations for creating inclusive, affordable, and technology-driven rural healthcare solutions.

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Chapter 2 : Challenges and the opportunities in rural healthcare

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Dr. Rampravesh R. Yadav, Dr. Aruna J. Singham

Asst. Prof. Roopa Kulkarni, Asst. Prof. Pratiksha Pawar

Bhavna Trust Degree College, Chembur, University of Mumbai

The accessibility of the internet has greatly increased the issue of child pornography. A report released by Interpol has recorded 2.4 million cases of child abuse during the pandemic 2022.It clearly shows that sexual abuse of children on the internet is widespread. Artificial intelligence has numerous applications these days. This has helped business organizations read their clients and better serve them. In today's world, the accuracy of age prediction by artificial intelligence is only a few years different from the actual age. Artificial intelligence can also be used to detect obscene images of children. The current state of artificial intelligence in detecting pornographic images and the parameters used to determine age by analysing images are presented in this paper. It also tackles laws related to sexual abuse, child abuse and deepfakes.

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Chapter 3: Legal protection of child from sexual abuse and pornography through social media

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CA DHVANI SHAH - ASSISTANT PROFESSOR OF LALA LAJPATRAI COLLEGE OF COMMERCE AND ECONOMICS.

MR JAINISH GOTECHA - ASSISTANT PROFESSOR OF PRAHLADRAI DALMIA LIONS COLLEGE OF COMMERCE AND ECONOMICS.

MR PRATHIK SHETTY - VISITING FACULTY OF BSS FOUNDATION.

The research examines and analyzes people's perceptions regarding the demand for cabs in India, such as Ola and Uber. The primary data was used to analyze the data through a questionnaire. A sample of 100 customers availing this cab service was taken. It was conducted among those individuals who have used private cab services in Mumbai, India. The analysis was done to find out why and when they use these cab services. Why do they prefer this service? What are the factors they take into consideration when booking a cab service like Ola or Uber in Mumbai, India? Private cab companies have undergone an evolution in the taxi industry and the transportation industry of the country. During the earlier years, people used to prefer their vehicles or public transport like an auto rickshaw, a bus, a public taxi, etc. After the entry of these private cab companies, there is a drastic change in the mindset of the consumer to avail of their private transport because they have better facilities to provide.

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Chapter 4 : Comparative analysis of Ola and Uber

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Shubhangi Gupta, Research scholar,

Dr.Ganesh sambhaji Lande, Research guide, Dr DY Patil School of Management

Retail investors rely on financial models to make sound investment decisions, with traditional models such as Markowitz Mean-Variance Optimization, Capital Asset Pricing Model (CAPM), and Discounted Cash Flow (DCF) analysis serving as foundational tools for portfolio management and valuation. However, as artificial intelligence (AI) and machine learning improve, AI-driven financial models emerge as an alternative, providing data-driven, adaptive, and predictive capabilities that challenge the static and assumption-driven character of traditional models. This research paper compares traditional financial models to AI-based financial models in the context of retail investor decision making. The study compares the effectiveness, accuracy, flexibility, and risk-adjusted returns of both methodologies under different market scenarios. This article compares the effectiveness of traditional financial models, such as the Markowitz Mean-Variance Model and the Capital Asset Pricing Model, to AI-based financial models in supporting retail investors. The study looks at their efficiency, accuracy, and risk-adjusted returns. The study examines historical performance, real-time applications, and investor preferences to determine whether AI-driven models outperform traditional investment approaches.

Traditional models are based on historical data and theoretical frameworks, which makes them ideal for stable markets but less effective in capturing non-linear correlations and real-time market movements. In contrast, AI- driven models use machine learning algorithms, big data analytics, and alternative data sources (such as social media sentiment, macroeconomic indicators, and news analysis) to deliver more personalized, real-time investment recommendations. This study uses quantitative back testing and empirical analysis to compare the risk-return profiles, efficiency, and practical applicability of AI-based models to traditional financial models.

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Chapter 5: Comparing Traditional Financial Models vs. AI-Based Financial Models: Recommendations for

Retail Investors

ABSTRACT

Ms Yaseera Anware

Maharashtra College of Arts,Science and Commerce

In the midst of a bustling metropolis like Mumbai, where every second counts in the face of potential disasters like arson, inadvertent fires, or unforeseen blazes, there's an urgent need for innovative solutions to mitigate the impact of these emergencies. Traditional fire-fighting responses often grapple with the relentless traffic snarlsthat can impede the rapid arrival of fire engines at critical scenes. Introducing the IoT Based Flame Fighter, a revolutionary solution poised to revolutionize the way we combat urban fires. My IoT Fire Fighting device represents a cutting-edge fusion of technology and safety, embodying a fleet of unmanned drones designed to be remotely controlled via Wi-Fi or mobile data networks. These agile drones serve as first responders, bridging the critical gap between the onset of a fire and the arrival of conventional firefighting teams.

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Chapter 6: IoT- Based FIRE FIGHTER

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Shalini kumari, Dr.Pravin Kulurkar, Dr. Priti bihade

G H Raisoni college of engineering and management

The exponential growth of information shared on the internet, particularly through social media platforms, has made distinguishing between authentic and fake news increasingly challenging. With the proliferation of web- based networking media, a significant portion of smartphone users now prefer reading news on social media rather than traditional websites. However, the authenticity of information published on these platforms oftenremains unverified, leading to the rapid dissemination of misinformation.

This ease of sharing has exacerbated the problem, contributing to the exponential spread of fake news. As a result, fake news has emerged as a critical issue, especially with the internet's widespread accessibility and its pivotal role in shaping public opinion. Addressing this challenge requires robust mechanisms to categorize news as either legitimate or illegitimate.To tackle this issue, we developed a framework leveraging various machine learning (ML) techniques. Python, chosen for its versatility and extensive libraries, served as the primary scripting language for implementation.The framework employs several ML methods, including K-Nearest Neighbors (KNN) and Decision Trees(DT), complemented by an integrated approach using advanced ensemble techniques such as Random Forest (RF), Gradient Boosting (GB), and custom ensemble methods. These custom methods, including Stacking and Maximum Voting Classifiers, demonstrated superior performance in identifying fake news.

Notably, the Stacking approach, combining classifiers like KNN, Support Vector Classifier (SVC), and Logistic Regression (LR) in a custom ensemble, achieved the highest accuracy in categorizing news. This integrated methodology underscores the potential of combining multiple ML techniques to enhance the efficiency and reliability of fake news detection systems.

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Chapter 7: On cloud computing systems, machine learning techniques are used to detect fake news.

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Dr. Rashmi

Assistant Professor at Sree Narayana Guru College of Commerce, Chembur, Mumbai, 400089

This paper provides an insightful exploration of the morally significant landscape surrounding AI (AI) and ML (ML). Beginning with an introduction to AI and ML, the discussion delves into morally significant issues such as bias, fairness, transparency, and privacy. Real-world case studies exemplify solutions and pitfalls in addressing these concerns, emphasizing the need for responsible AI frameworks. Emerging issues in Autonomous Weapons and Deepfakes are scrutinized, highlighting the imperative role of international agreements and proactive measures. The abstract concludes by emphasizing the crucial balance between technological innovation and morally significant considerations in navigating the dynamic realm of AI and ML.

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Chapter 8: RESPONSIBLE AI: ETHICAL FRONTIERS AND REAL-WORLD CHALLENGES

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Dr. Kirti Virendra Varma, Assistant Professor, Department of Commerce, Changu Kana Thakur Arts, Commerce & Science College, New Panvel (Autonpmous)

Varma Sakshi Virendra, Assistant Professor, Department of Commerce, B.K. Birla College Kalyan of Arts, Commerce & Science Kalyan (Empowered Autonomous)

E-banking is a major advancement in modern banking that provides customers with unparalleled efficiency, accessibility, and convenience. People may now do many types of banking transactions at any time and from any location, which greatly lessens the need for physical banks. This paper aims to evaluate the challenges faced by e-banking users. The findings of the study indicated that Security concern, Data breaches, Device security, Transaction errors, Poor user experience, Hidden fees, Biometric authentication issues, Dependency on mobile network, Multiple deduction in transaction and Multiple currency and payment method are major challenges faced by the e-banking users.

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Chapter 9: A STUDY ON CHALLENGES FACED BY E-BANKING USERS

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Ms. Priyanka G. Londhe , Ms. Vasudharaje P. Salunkhe, Mr. Likhit A. Raut, Prof. Pooja U. Shinde Department of Electrical Engineering Jspm’s Bhivarabai Sawant Institute of Technology & Research Wagholi, Pune, India

ABSTRACT—This project focuses on the design and development of a borewell rescue system aimed at efficiently rescuing objects or trapped entities from borewell holes. The system is built using a sturdy tripod frame equipped with a top- side pulley, which allows for the smooth movement of the rescue mechanism. The primary lifting mechanism involves a wiper motor attached to a steel strip, which operates a specialized arm gripper designed to retrieve objects from deep inside the borewell. The system is controlled wirelessly via an Arduino microcontroller interfaced with an HC-05 Bluetooth module, enabling remote operation of the motors. Motor drivers are used to control the wiper motor and other necessary components for precision movement. Additionally, the setup includes an Arduino camera for real-time monitoring of the borewell interior, and an IR sensor for obstacle detection, ensuring safe and efficient operation. This innovative rescue system is portable, user friendly, and provides a cost-effective solution to the growing issue of borewell accidents, offering both enhanced safety and precision during the rescue process.

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Chapter 10: Designing Of A Borewell Rescue Machine

ABSTRACT

Author’s Name: Sakshi Virendra Varma

Designation: Assistant Professor (Department of Commerce)

College: B. K. Birla College of Arts, Science and Commerce,(Empowered Autonomous) Kalyan (W),Maharashtra

Co-Author’s Name: Dr. Kirti Virendra Varma

Designation: Assistant Professor (Department of Commerce)

College: Changu Kana Thakur Arts, Commerce & Science College, New Panvel (Autonomous)

Doomscrolling, the act of continuously consuming negative news online, has become a pervasive behavior in the digital age. This study explores the relationship between Big Five personality traits and doomscrolling behavior, with a focus on mental health outcomes. A quantitative correlational design was employed, with a sample of 73 young adults completing a structured questionnaire assessing personality traits, doomscrolling behavior, and mental health outcomes. The results indicate that individuals with higher levels of openness, conscientiousness, extraversion, agreeableness, and neuroticism tend to engage in more doomscrolling behavior. Furthermore, doomscrolling was found to have a negative impact on mental health outcomes, including increased anxiety, depression, and emotional exhaustion. The findings suggest that personality traits play a significant role in shaping doomscrolling behavior and subsequent mental health outcomes.

This study contributes to the growing body of research on the psychological effects of doomscrolling and highlights the importance of considering individual differences in personality traits when examining the impact of doomscrolling on mental health. The findings have implications for the development of targeted intervention aimed at mitigating the negative effects of doomscrolling on mental health.

Overall, this study provides insight into the complex relationship between personality traits, doomscrollingbehavior, and mental health outcomes, and highlights the need for further research in this area. In the past few years, the concept of "doom-scrolling," which is completely new in the field of mental health research, has gained a great deal of public interest. The phenomenon of enhanced negative affect following excessive exposure to pandemic-related media has been dubbed "doom scrolling."

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Chapter 11: The Psychological Toll of Doomscrolling: Big Five Personality Traits as Predictors of Mental Health Outcomes

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