Daily Archives: December 4, 2025

Authors: Dr. Goldi Soni, Reddi Rishitha, Karri AmruthaVarshini

Abstract: The review highlights the significant impact of artificial intelligence (AI) on agriculture, showcasing its ability to enhance efficiency, productivity, and sustainability in response to global food scarcity and a rising population. Key applications of AI include advanced soil, crop, weed, and disease management, facilitated by technologies such as automated irrigation, drones, and data analytics. Despite these advancements, challenges such as uneven distribution of mechanization, the necessity for big data, complexities in soil treatment, pest control issues, and gaps in farmers' technological knowledge hinder widespread adoption. The integration of AI with vertical farming presents a promising solution for urban land and water scarcity by significantly improving crop monitoring and yield predictions through machine learning and IoT technologies. As the agricultural sector faces pressure to increase production by 70% by 2050 amid limited resources and climate change, AI emerges as a crucial element in developing expert systems for crop management and enhancing overall economic efficiency while supporting sustainable farming practices. Nevertheless, significant hurdles remain, including high implementation costs, privacy concerns, and the need for interdisciplinary collaboration to develop holistic AI applications that consider economic, social, and environmental impacts alongside ethical implications. Overall, AI is positioned as a transformative force that could revolutionize agriculture, addressing core challenges and paving the way for smarter, more sustainable farming methods.

Published by: vikaspatanker

Authors: Dr. C.K. Gomathy, VD Sasank, R Srishreya

Abstract: Big Data in healthcare leverages advanced analytics on massive, heterogeneous datasets (electronic health records, medical images, genomics, wearable sensor streams, etc.) to improve patient outcomes and operational efficiency. Traditional healthcare IT systems cannot cope with the volume, velocity, and variety of these data. Modern distributed platforms (Hadoop, Spark, cloud) and AI methods (machine learning, deep learning) are therefore crucial for enabling real-time predictive modeling and trend analysis in medicine. This paper reviews recent (2015–2025) developments in healthcare-focused Big Data analytics, including architectures, algorithms, and applications. A comprehensive end-to-end methodology is proposed, comprising data ingestion, preprocessing, distributed model training, and deployment via containerized services. We describe the implementation of a prototype healthcare analytics system and present experimental results demonstrating its scalability and accuracy for real-time patient risk prediction. The findings underscore that Big Data analytics has become a foundational tool in healthcare, enabling evidence-based clinical decision support, disease surveillance, and personalized medicine.

DOI: http://doi.org/10.5281/zenodo.17813444

Published by: vikaspatanker

Authors: Rachna Chandra, Manoj Mittal, Anmol Dobriyal, Suneet Bhalla, Utsav

Abstract: We analysed the peer-reviewed literature published between 2021 and 2025 focusing on smart agriculture techniques which integrates advanced technologies such as the Internet of Things (IoT), wireless sensor networks (WSN), machine learning, artificial intelligence (AI), unmanned aerial vehicles (UAVs), remote sensing, edge–fog–cloud computing, and renewable energy systems to enhance farming efficiency and sustainability. Recent research shows significant progress in precision irrigation, automated monitoring, and data driven decision support systems that optimize water usage and improve crop yield. This paper presents a comprehensive review of forty research papers focused on smart agriculture techniques, highlighting IoT-based soil moisture monitoring, LoRaWAN enabled long-range communication, machine learning-based disease detection, UAV assisted irrigation planning, and solar powered intelligent water systems. The findings show that integrating smart technologies enables resource optimization, climate resilience, and scalable automation across diverse agricultural scenarios. The study contributes a consolidated view of recent advancements to support the development of sustainable agriculture.

Published by: vikaspatanker

Authors: Sharda Nand Mishra

Abstract: The integration of Artificial Intelligence (AI) into educational practices offers transformative potential for teaching and learning processes. AI tools can make education more personalized, efficient, and accessible by adapting to individual student needs, providing real-time feedback, and automating administrative tasks. This paper explores the role of AI technologies as effective teaching aids, focusing on their alignment with the objectives of India’s National Education Policy (NEP) 2020. The NEP 2020 emphasizes the use of technology to promote personalized learning, improve teacher effectiveness, enhance access to quality education, and bridge existing educational gaps, particularly in rural and under-resourced areas. The study analyzes current initiatives such as adaptive learning platforms, intelligent tutoring systems, virtual reality applications, and automated assessment tools, illustrating their contribution toward achieving NEP’s goals of learner-centered education and digital literacy. It also highlights challenges faced in implementation, including insufficient infrastructure, lack of digital skills among educators, and ethical concerns regarding data privacy. Finally, the paper proposes actionable recommendations like continuous professional development for teachers, strategic investment in technology infrastructure, and developing policy frameworks for responsible AI use. These measures aim to foster a more interactive, inclusive, and future-ready education system in India.

DOI: http://doi.org/10.5281/zenodo.17812055

Published by: vikaspatanker

Authors: Mr. Vivek Kumar

Abstract: The integration of technology and innovation in teacher education has become imperative for preparing teachers for 21st-century classrooms. This paper studies the role of technology in reshaping teacher training, focusing on innovative technologies such as Virtual Reality (VR), online learning platforms, and Artificial Intelligence (AI). It discusses the benefits and challenges of adopting technological tools in teacher education and emphasizes the need to balance technological proficiency with pedagogical skills. Finally, it provides recommendations for policymakers and educational institutions to ensure the effective integration of technology in teacher training programs.

DOI: http://doi.org/10.5281/zenodo.17812024

Published by: vikaspatanker

Authors: Om Prakash Yadav

Abstract: Artificial Intelligence (AI) has become one of the most discussed and applied technologies in modern education. It is slowly changing the way teachers teach and the way learners learn. Traditional methods of education were mostly based on fixed textbooks, classroom lectures, and standard examinations. While these methods shaped generations, they often failed to give personal attention to learners with different learning speeds and styles. AI has entered this space as a supportive tool that can overcome many of these gaps. AI-powered systems can provide personalized learning by understanding the strengths and weaknesses of each learner. For example, adaptive learning platforms can suggest exercises to slow learners while giving advanced tasks to quick learners. This ensures that no student is left behind or feels unchallenged. Similarly, AI-based chatbots can answer student queries at any time, giving them round-the-clock academic support. In teacher practices, AI reduces repetitive tasks like checking objective-type papers, managing attendance, or recording marks. This saves teachers’ time and allows them to focus more on creative teaching methods. Another benefit is the role of AI in inclusive education. Students with visual, hearing, or learning disabilities can be supported with AI- based applications like speech-to-text, text-to-speech, and virtual sign language interpreters. In this way, AI is not just a tool for efficiency but also for equity. AI can also help educational institutions manage large amounts of data. For example, analyzing student performance records helps teachers predict who may drop out or need extra help. This early identification makes interventions timely and useful. However, while AI brings many opportunities, it also brings challenges. Teachers fear over- dependence on machines, loss of human values, and even job insecurity. There are also ethical issues like data privacy and bias in algorithms. To move beyond traditional methods effectively, education needs to balance human touch with AI support. AI should not replace teachers but assist them in becoming more effective mentors. This paper explores how AI is shaping education beyond traditional boundaries. It studies different case examples, reviews existing literature, and proposes a simple framework for blending AI tools with human-centered teaching. The aim is to show that AI is not just about technology but about creating smarter, fairer, and more engaging learning environments.

DOI: http://doi.org/10.5281/zenodo.17811976

Published by: vikaspatanker

Authors: Shilnidhi

Abstract: Artificial Intelligence (AI) has moved far beyond being an abstract or futuristic idea and has established its presence in everyday educational contexts. Increasingly, schools and higher education institutions are witnessing the integration of AI-powered tools, particularly in the form of assistants and chatbots. These technologies are not confined to automating routine tasks but are gradually transforming teaching and learning practices. This paper investigates the progressive role of AI chatbots as they transition from supportive tools to becoming virtual co-teachers in contemporary classrooms. The exploration draws upon existing academic literature, classroom case studies, and theoretical frameworks to examine the educational implications of this shift. Initially, AI chatbots were developed to simplify administrative duties, such as answering queries, grading assignments, and managing schedules. However, their evolving capacity has extended to instructional domains, where they can facilitate personalized learning experiences, provide instant feedback, and support differentiated teaching methods. By functioning as interactive learning companions, these AI tools hold the potential to supplement teachers in addressing diverse learner needs and enhancing student engagement. Adopting a qualitative perspective, the study delves into how both teachers and students perceive and interact with AI assistants. It highlights the dynamics of setting up meaningful interactions, the pedagogical strategies employed, and the challenges encountered in classroom environments. Students, on the other hand, experience a redefined learning process where immediacy of responses and adaptive support from AI can foster deeper engagement. Nonetheless, the integration process is not free from challenges. Technical limitations, ethical dilemmas concerning data privacy, and pedagogical concerns related to over-dependence on technology emerge as significant issues requiring critical reflection. The findings suggest that AI, when thoughtfully implemented, should not be viewed as a replacement for human educators but as a complementary partner that enriches the teaching-learning ecosystem. Teachers continue to provide emotional intelligence, contextual understanding, and mentorship, while AI contributes efficiency, scalability, and personalized assistance. The symbiotic relationship between human educators and AI has the potential to foster inclusive and effective classroom environments that are responsive to the diverse needs of learners. In conclusion, this research emphasizes that the real strength of AI in education lies not merely in automating tasks but in reimagining the role of teachers and students in the digital age. By addressing ethical, technical, and pedagogical challenges, AI can evolve into a reliable co-teacher that enhances human potential rather than diminishing it. The study argues for a balanced and reflective integration of AI, one that safeguards human agency while embracing technological advancement. Ultimately, AI in classrooms represents not the end of traditional teaching but the beginning of a collaborative model where human and machine intelligence work together to enrich education.

DOI: http://doi.org/10.5281/zenodo.17811902

Published by: vikaspatanker

Authors: Swati Kumari

Abstract: In the present era, Artificial Intelligence (AI) has become a revolutionary force in the education sector. This advanced technology is transforming the teaching-learning process by making it more efficient, personalized, and data-driven, thereby significantly improving educational quality. AI-based technologies such as Intelligent Tutoring Systems, Adaptive Learning Platforms, Automated Grading Systems, and Virtual Classrooms are assisting educators in designing curricula tailored to individual student needs, providing precise feedback, and effectively tracking their progress. These tools empower educators to deliver highly customized learning experiences that adapt in real-time to the student’s learning pace and capabilities.Moreover, AI plays a pivotal role in making education more accessible, enabling schools in remote and under-resourced areas to receive technological support that was previously unavailable. Despite these advantages, several challenges persist, such as the lack of digital infrastructure, high implementation costs, data privacy concerns, and a general lack of technical literacy among teachers and students.This research paper presents a comprehensive analysis of the primary methods through which AI is applied in education, the various benefits achieved through its application, and its broader impacts on the education system. The conclusion emphasizes that with appropriate policies, training programs, and technological support, AI can make education systems more effective, inclusive, and innovative.

DOI: http://doi.org/10.5281/zenodo.17811846

Published by: vikaspatanker

Authors: Raegan Alex. A, Jyothi Gupta

Abstract: Aim: This paper reviews urban expansion through space and time in Chennai city (a megapolis of India) based on GIS technology etc, and investigates ways to integrate blue-green infrastructure, i.e., wetlands, riverscapes, greenscapes into the development for climate adaptation, resilient cities & sustainable growth. Research Question: What can GIS show us about Chennai’s ancient land use changes and urban expansion? What are the possibilities of climate-proofing resilience and promoting sustainable urban development with blue-green infrastructure? Methodology: Ten research papers were analyzed, and core concepts were determined as well as gaps identified. The Shapefile/GIS data was obtained and studied to observe the pattern of city growth. For identifying potential areas for BGI and urban resilience interventions, the land use/land cover changes were mapped. Results: GIS based analysis identified speedy urbanization in and around OMR and GST Road at the cost of wetlands, agricultural land, and open spaces. Map of vegetation, water bodies showed areas to reclaim for restoration. The rivers, sewers, sumps and metro lines became avenues for blue-green infrastructure projects. Zones for planning interventions were determined using highway networks and administrative boundaries. A mapping of priority areas for flooding, urban cooling and sustainable development was conducted. Conclusion and Limitation: Urbanization of Chennai has shrunk green and blue spaces, a situation that emphasizes the urgency for incorporating blue-green infrastructure to improve climate resilience. Challenges that people faced around the country included access to up-to-date ward boundaries, transforming shapefiles and high prices of datasets. Sensitve areas for restoration and management had been successfully mapped if imperfectly served by maps

DOI: http://doi.org/10.5281/zenodo.17878089

Published by: vikaspatanker