Precision Agriculture (PA) has emerged as a transformative approach to modern farming by integrating advanced digital technologies with agricultural management to improve crop productivity, optimize resource utilization, and promote long-term farm sustainability. Rapid population growth, climate change, declining natural resources, and increasing food demand have intensified the need for efficient agricultural production systems capable of maximizing yields while minimizing environmental impacts. Precision Agriculture utilizes technologies such as the Global Positioning System (GPS), Geographic Information Systems (GIS), Remote Sensing, Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML), drones, satellite imagery, robotics, and variable-rate technology (VRT) to monitor crop growth, soil conditions, nutrient status, and environmental parameters in real time. These technologies enable site-specific management of irrigation, fertilization, pest control, and harvesting, thereby improving input-use efficiency and reducing production costs. This study examines the role of Precision Agriculture technologies in enhancing crop productivity and farm sustainability. It explores the principles and components of precision farming, evaluates the impact of digital technologies on crop management and resource conservation, analyzes emerging technological innovations supporting sustainable agriculture, and discusses future policy interventions for promoting widespread adoption of precision farming. The study concludes that integrating digital technologies, climate-smart agricultural practices, and data-driven decision-making can significantly enhance agricultural productivity while conserving soil, water, energy, and biodiversity. Strengthening research, digital infrastructure, farmer training, and supportive policies will be essential for realizing the full potential of Precision Agriculture in achieving sustainable and climate-resilient agricultural development.
Research Author· American Journal of Multidis...· 0 citations
The present study examines the influence of social media usage on psychological well-being, self-esteem, and interpersonal relationships among adolescents and young adults. Social media has become an important part of daily life, offering opportunities for communication, self-expression, social connection, and information sharing. However, excessive or problematic use of social media may affect emotional health, body image, self-worth, sleep patterns, and social behaviour (Keles, McCrae, & Grealish, 2020). The study explores how frequency of use, online comparison, feedback-seeking, cyberbullying, and digital interaction patterns influence users’ mental well-being and self-esteem. It also analyses the role of social media in shaping interpersonal relationships, including friendship quality, family communication, peer interaction, and social support. Previous studies suggest that social media can provide belongingness and emotional support, but it may also increase anxiety, loneliness, and depressive symptoms when used excessively or negatively (Primack et al., 2017; Woods & Scott, 2016). The study highlights the need for balanced social media use, digital literacy, positive online behaviour, and supportive family and institutional environments to promote healthy psychological and social development among adolescents and young adults.
Research Author· European Journal of Integrat...· 0 citations
Artificial intelligence-driven digital learning platforms are transforming contemporary education by enabling personalized learning, adaptive feedback, learning analytics, and flexible access to academic resources. These platforms support learners by identifying individual learning needs, improving instructional delivery, and promoting self-paced learning (Zawacki-Richter et al., 2019; Holmes et al., 2022). The present study examines the impact of AI-driven digital learning platforms on academic achievement, learning engagement, and educational equity among secondary and higher education students. It explores how AI-based tools influence students’ performance, motivation, participation, and access to quality learning opportunities. The study also considers challenges such as unequal digital access, limited digital literacy, data privacy concerns, and institutional readiness, which may affect equitable learning outcomes (UNESCO, 2021). The study highlights that AI-enabled platforms can enhance academic achievement and learner engagement when supported by inclusive policies, teacher training, ethical data use, and adequate digital infrastructure.
Research Author· International Journal of Inn...· 0 citations
The rapid advancement of digital technologies has fundamentally transformed labour markets, employment relationships, and the regulation of work across the globe. Digital platforms, artificial intelligence, automation, cloud computing, and algorithm-driven management systems have facilitated the emergence of the gig economy, enabling flexible, on-demand employment through platforms such as Uber, Swiggy, Zomato, Amazon Mechanical Turk, and Upwork. While these innovations have expanded employment opportunities and increased economic efficiency, they have also created significant legal challenges concerning worker classification, social security, fair wages, occupational safety, collective bargaining, data privacy, algorithmic decision-making, and employment rights. Traditional labour laws, primarily designed for standard employer-employee relationships, often fail to adequately protect gig workers who are frequently classified as independent contractors rather than employees. This classification limits their access to statutory benefits including minimum wages, paid leave, health insurance, pensions, maternity protection, and workplace safety. International organizations, including the International Labour Organization (ILO), have emphasized the need to modernize labour regulations to address evolving forms of digital employment. This paper critically examines the legal implications of digital technologies on labour laws through a comparative analysis of international labour standards and selected national legal frameworks. It explores the challenges associated with platform work, artificial intelligence, algorithmic management, and cross-border digital labour while evaluating recent judicial developments and legislative reforms. The study concludes that ensuring fair labour conditions in the digital economy requires adaptive legal frameworks, stronger social protection systems, algorithmic transparency, effective platform accountability, and international cooperation to safeguard workers' rights without hindering technological innovation and economic growth.
Research Author· American Journal of Multidis...· 0 citations
The global agricultural sector faces significant yield losses due to the emergence and rapid evolution of plant pathogens, including fungi, bacteria, viruses, and oomycetes. Conventional diagnostic methods, while foundational, often lack the sensitivity and speed required for early detection and strain-level identification. Molecular characterization has emerged as a transformative approach, enabling the precise identification, classification, and understanding of pathogen virulence mechanisms at the genetic level. This paper explores advanced molecular diagnostic and analytical frameworks, including Next-Generation Sequencing (NGS), polymerase chain reaction (PCR)-based diagnostics, and CRISPR-based detection systems. By analyzing the genetic diversity and evolutionary dynamics of major crop pathogens—such as Magnaporthe oryzae and Fusarium species—researchers can track the spread of resistant strains and develop targeted control strategies. The discussion examines how molecular insights facilitate the characterization of effector proteins and host-pathogen interactions, which are critical for breeding durable disease resistance in staple crops. Furthermore, the analysis addresses the challenges of integrating these high-throughput molecular tools into field diagnostics and the importance of global surveillance networks in mitigating transboundary disease outbreaks. Ultimately, the molecular characterization of plant pathogens is a fundamental necessity for modern, sustainable crop protection, providing the diagnostic accuracy and evolutionary insights required to safeguard food security against an increasingly complex and dynamic landscape of agricultural pathogens.
Research Author· European Journal of Food, Fa...· 0 citations
The present study examines how people understand, accept, and respond to the growing use of artificial intelligence in modern society. Artificial intelligence technologies are increasingly used in education, healthcare, banking, transport, communication, agriculture, security, business, entertainment, and public services. These technologies have created new opportunities for efficiency, innovation, automation, decision-making, and problem-solving. The study focuses on public awareness, attitudes, trust, expectations, and concerns regarding artificial intelligence. It examines whether people perceive AI as a useful tool for social and economic progress or as a source of risk related to job loss, privacy, data misuse, bias, surveillance, misinformation, and reduced human control. The study also explores the influence of factors such as age, education, occupation, digital literacy, income, media exposure, and personal experience with technology on public perception. In contemporary communities, artificial intelligence has both positive and negative societal implications. On one hand, it can improve healthcare diagnosis, personalized education, smart governance, financial services, disaster management, and accessibility for differently abled persons. On the other hand, it may create ethical challenges, social inequality, digital divide, algorithmic discrimination, and dependence on machines. The study is significant because public perception plays an important role in the acceptance and responsible use of artificial intelligence. The findings may help policymakers, educators, technology developers, social researchers, and community organizations design awareness programmes, ethical guidelines, and inclusive AI policies for the benefit of society.
Research Author· American Journal of Multidis...· 0 citations
Artificial Intelligence (AI) has emerged as a transformative technology in the healthcare sector, revolutionizing medical diagnosis, treatment planning, disease prediction, robotic surgery, personalized medicine, and healthcare administration. AI-driven technologies improve clinical efficiency, reduce human error, accelerate drug discovery, and enhance patient outcomes through data-driven decision-making. However, the widespread adoption of AI in healthcare has introduced complex legal, ethical, and regulatory challenges that existing healthcare laws often struggle to address. Issues relating to patient privacy, informed consent, algorithmic transparency, liability for medical errors, data ownership, cybersecurity, bias in AI algorithms, and cross-border data governance have become central concerns in contemporary health law. As AI systems increasingly participate in clinical decision-making, determining accountability among healthcare professionals, software developers, medical institutions, and regulatory authorities becomes legally complex. Several jurisdictions, including the European Union, the United States, India, and the United Kingdom, have introduced regulatory frameworks to ensure the safe, ethical, and responsible deployment of AI-powered healthcare technologies. This paper critically examines the legal regulation of Artificial Intelligence in healthcare through a comparative analysis of international legal frameworks, judicial developments, and ethical principles governing AI-enabled medical systems. It explores the opportunities AI presents for improving healthcare delivery while evaluating the legal challenges surrounding privacy, liability, fairness, transparency, and patient rights. The study concludes by proposing future regulatory reforms aimed at establishing comprehensive, accountable, and human-centric governance frameworks that promote innovation while protecting fundamental rights and ensuring ethical healthcare delivery in the digital era.
Research Author· European Journal of Law, Int...· 0 citations
Soil fertility is a fundamental component of sustainable agricultural production, ecosystem functioning, and environmental conservation. Different land use systems significantly influence soil physical, chemical, and biological properties, thereby affecting nutrient availability, crop productivity, and long-term soil health. Rapid urbanization, deforestation, intensive agriculture, industrialization, and climate change have altered natural land use patterns, resulting in soil degradation, nutrient depletion, erosion, and declining agricultural productivity. Understanding soil fertility status and nutrient dynamics across various land use systems—including agricultural land, forests, grasslands, wetlands, agroforestry systems, and fallow lands—is essential for developing effective soil management strategies. Soil nutrients such as nitrogen, phosphorus, potassium, sulfur, calcium, magnesium, and micronutrients undergo continuous transformation through biological, chemical, and physical processes influenced by vegetation, land management, climate, and microbial activity. Modern technologies including Geographic Information Systems (GIS), Remote Sensing, Artificial Intelligence (AI), Internet of Things (IoT), precision agriculture, and digital soil mapping have improved the assessment of soil fertility by enabling accurate spatial analysis and real-time nutrient monitoring. This study evaluates soil fertility status and nutrient dynamics under different land use systems by examining soil properties, nutrient cycling processes, technological innovations, and sustainable land management practices. The study concludes that appropriate land use planning, integrated nutrient management, precision agriculture, and conservation practices are essential for maintaining soil fertility, improving crop productivity, conserving natural resources, and ensuring sustainable agricultural development under changing environmental conditions.
Research Author· Europian Journal of Agricult...· 0 citations
Digital governance has become a defining feature of modern public administration, transforming the relationship between governments, citizens, and public institutions through the use of information and communication technologies (ICTs). E-governance initiatives have enhanced the efficiency, transparency, accountability, and accessibility of public services by enabling online delivery of governmental functions, digital identity systems, electronic records, e-courts, digital taxation, e-procurement, and citizen participation platforms. These technological advancements contribute significantly to good governance and sustainable development while reducing administrative delays, corruption, and bureaucratic inefficiencies. However, the rapid digitalization of governance also presents substantial legal and constitutional challenges concerning the rule of law, data protection, privacy, cybersecurity, digital inclusion, algorithmic decision-making, administrative accountability, and access to justice. The rule of law requires that governmental actions remain lawful, transparent, accountable, and subject to judicial oversight regardless of whether they are conducted through traditional or digital mechanisms. Consequently, digital governance must operate within a comprehensive legal framework that protects constitutional rights while encouraging technological innovation. Emerging technologies such as artificial intelligence, blockchain, cloud computing, big data analytics, and automated public administration further complicate legal regulation by introducing issues related to transparency, fairness, discrimination, and procedural due process.
Research Author· European Journal of Law, Int...· 0 citations
The present study examines how digital technologies are changing human resource functions and organizational practices in modern corporate institutions. Digital transformation refers to the integration of technologies such as artificial intelligence, cloud computing, data analytics, automation, digital communication platforms, HR information systems, e-recruitment, online training, and performance management software into business operations. The study focuses on the impact of digital transformation on human resource management practices such as recruitment, selection, onboarding, training, employee engagement, attendance management, payroll, performance appraisal, and talent development. It also examines how digital HR practices influence employee performance by improving efficiency, communication, skill development, transparency, feedback, and productivity. Further, the study explores the role of digital transformation in organizational sustainability through cost reduction, paperless processes, flexible work systems, innovation, data-based decision-making, and long-term competitiveness. In the contemporary corporate world, digital transformation has become essential for improving speed, accuracy, adaptability, and organizational growth. However, it also creates challenges such as employee resistance, digital skill gaps, data privacy concerns, cybersecurity risks, job insecurity, and technological dependence. Therefore, the study is significant because it highlights the need for balanced digital adoption, employee training, ethical technology use, and sustainable HR policies.
Research Author· Global Insights Journal· 0 citations
Cropping system diversification has emerged as an essential strategy for achieving sustainable agricultural production by improving crop productivity, enhancing soil fertility, conserving natural resources, and increasing resilience to climate change. Continuous cultivation of monocrops has contributed to soil degradation, nutrient depletion, pest outbreaks, biodiversity loss, and declining farm profitability in many agricultural regions. Diversified cropping systems, including crop rotation, intercropping, relay cropping, mixed cropping, agroforestry, and integrated farming systems, provide ecological and economic benefits by promoting efficient resource utilization and reducing production risks. These systems improve nutrient cycling, increase soil organic matter, enhance water-use efficiency, suppress weeds and pests naturally, and strengthen ecosystem resilience. Advances in precision agriculture, remote sensing, Artificial Intelligence (AI), Geographic Information Systems (GIS), and Internet of Things (IoT) technologies further support diversified farming by enabling site-specific crop planning and efficient resource management. This study assesses the role of cropping system diversification in promoting sustainable agricultural production. It examines the principles and types of diversified cropping systems, evaluates their impact on crop productivity, soil health, biodiversity, and farm income, explores technological innovations supporting diversified agriculture, and discusses future policy interventions for promoting climate-resilient farming systems. The study concludes that cropping system diversification represents a sustainable agricultural approach capable of improving productivity while conserving environmental resources and strengthening food security. Effective policy support, scientific research, digital technologies, and farmer participation are essential for promoting diversified farming systems capable of meeting future agricultural challenges under changing climatic conditions.
Research Author· American Journal of Advanced...· 0 citations
The convergence of precision agriculture and artificial intelligence (AI) has revolutionized the monitoring and management of crop health, offering transformative solutions to the perennial challenge of pest and disease outbreaks. Traditional scouting methods, characterized by their time-intensive nature and susceptibility to human error, are increasingly being superseded by AI-driven systems capable of real-time, large-scale detection. This paper explores the architecture and application of AI-based pest and disease detection systems, emphasizing the integration of computer vision, deep learning, and remote sensing technologies. By leveraging Convolutional Neural Networks (CNNs) and high-resolution imaging from drones and ground-based sensors, these systems facilitate the early identification of biotic stresses, enabling precision interventions that drastically reduce pesticide usage and operational costs. The analysis delves into the technical frameworks of data acquisition, image processing, and predictive modeling, while addressing the critical challenges of data labeling, model generalization, and real-time processing requirements. Furthermore, it highlights the transition from manual, reactive management to proactive, data-driven agricultural systems. Ultimately, AI-based detection is positioned as a pivotal component of sustainable, high-productivity agriculture, essential for mitigating food insecurity and enhancing climate resilience through optimized resource application and ecologically conscious crop protection strategies.
Research Author· American Journal of Advanced...· 0 citations
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