Today many countries are doing their efforts in advancing healthcare systems and medical mechanism and do for this several projects are going on. Among the information technology emerging areas cloud computing, big data analytics, internet of things, blockchain technologies, cyber security technologies, artificial intelligence, machine learning, and so on. Big Data is dedicated in managing large amount ofdata and managing complex, unstructured data using scientific principles, mechanism and modern tools. AI integrated technologies are required in enhancing Data Driven mechanism for sophisticated healthcare practices using predictive modeling for proper and effective decision-making.

Adoption of the use of artificial intelligence (AI) in agricultural disease control has proven to be efficient

in terms of technical improvement but economic justification has proved to be a foundation pillar in

implementation strategies. This is a review article, which summarizes the existing approaches to measuring

the financial changes brought about by AI-based crop disease detection and mitigation systems. The

authors focus on the schemes of yield losses estimation, methods to value economic types of returns, and

modelling, methods of return on investment (ROI) evaluation in varying agricultural application situations.

By systematically reviewing the current body of such literature and case studies, this review confirms in

part that AI- based early disease detection can yield losses of 15-40% of the end yield dependent on type

of crop and time of intervention with the same investment returning on investment in the range of 150,

400% on a 3-year deployment period. But even there, there are major discrepancies in methodology in

the area of impact assessment, especially in setting up of baseline, modelling attribution and long-term

measures of sustainability. The current paper suggests the system of integrating the disease incidence

modelling with the market-responsive economic valuation with the incorporation of AI model performance

measures and the measures of the regional variability.

Smartphones have become deeply integrated into daily life, offering constant connectivity, convenience,

and access to information. However, alongside these benefits, a growing body of research points to harmful

effects associated with excessive and compulsive use. Physical issues such as musculoskeletal strain and

eye fatigue, along with psychological concerns like anxiety, depression, sleep disturbances, and attention

problems, are becoming increasingly linked to problematic smartphone behavior. The severity of the

issue is now such that clinical tools like the Smartphone Addiction Inventory (SPAI) have been developed

to assess the condition, underscoring its recognition as a legitimate public health concern. Traditional

interventions-ranging from digital wellness apps to screen time limits, have shown only limited success,

often falling short due to lack of personalization, low adherence, and the general tendency to bypass them

after implementation. This paper proposes two informatics-driven strategies designed to interrupt habitual

device use in subtle, non-intrusive ways: Delayed Response Input, which introduces brief feedback delays

to disrupt the instant-reward loop, and Memory Recall Interruption, which asks users to reflect on their

intentions before proceeding. Both interventions aim to slow down impulsive interaction patterns, increase

user awareness, and ultimately reduce mindless screen time.

The swift digitisation of banking services has transformed financial accessibility while simultaneously

increasing vulnerability to cyber threats, resulting in significant socio-economic repercussions. This mixedmethods

study examines the evolving landscape of cyber-security threats in digital banking, encompassing

phishing, ransomware, malware, data breaches, insider threats, and DDoS attacks. It assesses their impact

on institutions, customers, and the economy. A quantitative analysis of a decade-long dataset indicates a

marked increase in cyber incidents, with reported attacks on financial institutions escalating from 1,500 in

2019 to 3,348 in 2023, accompanied by considerable economic disruptions, including GDP contractions

(–1% to –2%), surges in unemployment (+2.8 percentage points), and a decline in customer trust (–45%).

Qualitative views from cyber-security experts, policymakers, and financial regulators underscore organisational and regulatory hurdles in addressing these threats. The study introduces the CUBE Security

Model, which incorporates Continuous AI-driven detection, Unified threat intelligence, Blockchain-secured

transactions, and Encrypted cloud-based protection, in conjunction with advanced technologies such as zero-trust architectures, quantum-resistant encryption, and decentralised identity systems. Comparative case studies highlight regional differences in cyber-security resilience, emphasizing the importance of governance and innovation in maintaining socio-economic stability. This research integrates cyber-security with socio-economic analysis to provide practical frameworks that enhance digital banking resilience, foster public trust, and promote global financial stability in an interconnected environment. The swift digitisation of banking services has transformed financial accessibility while simultaneously revealing significant vulnerabilities to cyber threats.

The rapid advancement of Artificial Intelligence (AI) and Natural Language Processing (NLP) is

transforming financial sector, enabling the delivery of highly personalized services powered by predictive

intelligence. This study explores emerging trends in AI and NLP that are reshaping financial services by

enhancing customer interactions, risk assessment, and decision-making processes. Cutting-edge machine

learning models, such as deep learning and reinforcement learning, are powering real-time analysis

and customized financial solutions. NLP techniques, including sentiment analysis, chatbots, and voice

recognition, are improving customer interactions by more effectively interpreting and reacting to natural

language inputs. Additionally, predictive intelligence is being utilized for fraud detection, credit scoring,

and investment strategies, enhancing accuracy and efficiency in financial activities. The combination

of AI and big data analytics enables financial institutions to predict customer needs, enhance portfolio

management, and automate advisory services. This research also identifies challenges like data privacy,

regulatory compliance, and ethical concerns when implementing AI-powered financial solutions. As AI

and NLP advance, the future of finance is poised for greater automation, enhanced personalization, and

broader financial inclusivity. The study underscores the importance of responsible AI adoption, emphasizing

transparency, fairness, and security in financial applications. This paper explores current trends and possible

future advancements, providing insights into how AI-powered predictive intelligence is revolutionizing

the future of financial services, ultimately enhancing user experience and operational efficiency in the

financial industry.

India’s economic landscape has undergone a profound transformation over the past two decades, evolving

from a knowledge-driven economy to a digitally empowered one. This review paper explores the continuum

between Knowledge Management (KM), the Knowledge Economy, and the Digital Economy within the

Indian context, highlighting how KM frameworks have both shaped and adapted to this transition. Drawing

on interdisciplinary literature, policy analysis, and sectoral case studies, the paper examines the strategic

role of KM in enabling innovation, institutional learning, and technology-enabled collaboration across

industries. It critically assesses the integration of KM practices in digital platforms, government initiatives

(e.g., Digital India), and emerging technologies such as AI, IoT, and blockchain. The review also identifies

gaps in semantic interoperability, equity, and organizational readiness, proposing a contextualized KM

model to support inclusive digital transformation. By mapping India’s trajectory along the knowledge-digital

continuum, the paper offers actionable insights for policymakers, educators, and practitioners seeking to

leverage KM for sustainable economic development.

Education 4.0 has made learning more engaging for students through the modernization of the education

system. The key feature of Education 4.0 is personalized learning. Since every learner is different, their

learning patterns also vary. One of the significant features of Education 4.0 is presenting education to

each learner according to their individual needs and learning difficulties. Generating customized learning

materials for every learner is another important aspect of Education 4.0. Education 4.0 is a completely

student-cantered learning system, where learners must play an active role in the learning process. It is an

interactive learning platform, enabling learners, teachers, and the system to technologically interact with

one another. Education Technology is the application of Information Technology in Education Sector

supported by various technologies, systems and tools. The role of AI and allied technologies are impactful

and growing rapidly. This Paper is about the application of AI and allied Technologies in support of

Education 4.0 which is about bringing of new age educational practices and development.

Blockchain technology is emerging as a significant disruptive force, offering decentralized, secure, and

transparent systems for both higher education and corporate management. In academia, institutions like

MIT and Harvard are using it to revolutionize credential verification and secure student records, reducing

fraud and improving accessibility. In the corporate world, companies such as IBM and JPMorgan leverage

blockchain to enhance supply chain management and financial transactions, gaining efficiency and trust

through real-time tracking and fraud prevention. Furthermore, smart contracts are streamlining operations

by automating agreements and removing intermediaries. Despite challenges like high implementation costs,

scalability, and regulatory uncertainty, its future seems inevitable. Rapid advancements in AI integration,

interoperability, and hybrid models are paving the way for widespread adoption, positioning blockchain

as a true game-changer for the modern era. Blockchain technology is changing how universities and

companies operate by creating secure, transparent systems that aren’t controlled by one single entity. In

higher education, schools like MIT and Harvard are using it to protect student records and verify degrees,

making fraud much harder. In the business world, companies like IBM and JPMorgan use it to track products

in a supply chain or secure financial transactions. While it’s still expensive and faces challenges with

scaling up, new advancements (like combining it with AI) show it’s well on its way to becoming a core,

game-changing technology. Blockchain technology is building a new foundation of trust and efficiency for

universities and companies.

Neuromorphic Computing is the recent and emerging computing trends as revolutionary approach in advance

technologies invention. Nowadays, computer and computing technologiesare transforming in new direction

that is more advance and faster than the traditional computing system. Neuromorphic computing is one

of the recent emerging computing systems which perform high computational tasks very efficiently with

minimum time. This computing system developed by the inspiration from the human brain computation

as per human nervous system. As the human can think and take decisions instantly with support of the

brain. Neuromorphic computing build with the enormous neural network architectures according to the

human brain biological structure. This computing technology has high performance with less energy

utilization. Sustainable computing technology is another advance computing system that enable computers

to perform task by consuming less energy. In this technological era, power consumption enhances in

terms of high computation and increasing utilization of computing systems. Due to the increasing energy

consumption and emission of CO2 and other harmful gases, it is highly recommended to build energy

efficient computing system.

The popularity of virtual classes and internet-based teaching is increasing rapidly. The learners are excited

to attend the virtual classes and internet-based teaching. Virtual classes has some advantages over the

traditional classes but still it has some challenges too. The virtual classroom cannot fully substitute the

traditional classroom environment. This paper provides a comparative analysis of virtual and traditional

classrooms with a focus on students’ cognitive development. The overall growth and development of a

student are addressed in this discussion. The features, benefits, and challenges of traditional and virtual

classroom settings are examined here. This review paper deals with both classroom scenarios with

respect to physical competition, social competition, psychological comparison, cognitive development,

communication modes, attention span, and the overall development of a student.

In India, for improving the transparency, efficiency, and accessibility of the country’s education system

with the integration of digital technologies, educational E-Governance has emerged as a vital framework.

With the government placing digital transformation at the prioritizes of different sectors, the education field

has also experienced considerable reforms driven by information and communication technologies enabled

platforms, innovative policies, and decisions driven by data. This paper investigates the implementation,

advancement, and influence of Educational E-Governance projects in India. This study analyzes various

important Educational E-Governance initiatives which play a crucial role in educational field. It also

plays an essential role in academic record management, teacher training, online learning, and real-time

data monitoring. By using digital technologies like big data analytics, cloud computing, blockchain,

artificial intelligence, machine learning, and IoT, these platforms have improved policy implementation,

service delivery, and equitable access to learning resources across socio-economic and regional divides.

Nevertheless, there are challenges associated with the adoption of Educational E-Governance. Problems

like the digital divide, lack of sufficient ICT infrastructure in rural regions, limited digital literacy, worries

about data security, and interoperability gaps persistently impact broad implementation. This paper indicates

these obstacles and also suggests strategic solutions to increase the effectiveness of digital governance

in the education sector. This study concludes that Educational E-Governance holds immense potential to

transform India into a digitally empowered knowledge society.