Introduction: this review paper provides a comprehensive examination of the applications and impact of artificial intelligence (AI) in the field of education. With advancements in AI technologies, the educational landscape has witnessed significant transformations. This review aims to explore the diverse AI techniques employed in education and their potential contributions to teaching, learning, assessment, and educational support. Objective: this research article aims to tracing the development of AI in education from its early beginnings to its current state. It highlights key milestones and breakthroughs that have shaped the field, including the emergence of intelligent tutoring systems and expert systems. Methods: the article provides a comprehensive overview of the various AI techniques utilized in education, such as machine learning, natural language processing, computer vision, and data mining. Each technique is discussed in detail, showcasing the algorithms, models, and methodologies used within each approach. Results: while the benefits of AI in education are substantial, the paper also addresses the challenges associated with its integration. Ethical considerations, privacy concerns, and the need for effective human-AI collaboration are discussed in-depth. Conclusion: this review underscores the transformative potential of AI in education. By harnessing AI technologies effectively and responsibly, educators and policymakers can unlock new possibilities for enhancing teaching and learning experiences, fostering personalized instruction, and driving educational advancement.

Introduction: the Metaverse, a virtual space where users can engage with each other in a variety of experiences, has gained significant attention in recent years. With the advent of advanced technologies like Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR), the possibilities of the Metaverse have expanded to create new opportunities for learning and education. Objective: this research article aims to explore the potential of the Metaverse for higher education, including its opportunities, challenges, and implications. Methods: the article provides a comprehensive overview of the Metaverse, its history, and its key components. It then examines the potential of the Metaverse for higher education by reviewing relevant literature and analyzing the benefits that it can offer. These benefits include increased accessibility, flexibility, and interactivity, as well as the potential for immersive and personalized learning experiences. Results: the article also identifies the challenges and limitations of the Metaverse, such as technical limitations, privacy and security concerns, and the need for digital literacy skills. It further discusses the implications of using the Metaverse for higher education, including its impact on teaching and learning, curriculum design, and student engagement. Conclusions: finally, the article proposes some recommendations for educators and institutions interested in exploring the use of the Metaverse for higher education. These recommendations include developing a clear understanding of the educational goals, selecting appropriate technologies and platforms, and providing training and support for both educators and students.

E-Learning Education systems are gaining attention day-to-day because of their inclusive pertinence in the distance education system. Due to COVID-19, the online learning education system has become very popular. Most probably, all education systems have been using the IoT-based E-Learning system to continue the students’ education without hindrance during the COVID lockdown. Several E-Learning IoT schemes are explored that reflect privacy and security, but still, there is no detailed scheme; hence, it needs a sustainable, secure E-Learning IoT system. The characteristics and prospects of the Internet of Things are discussed in this article. By analyzing the various functions and capabilities of the Internet of Things, this article aims to provide an overview of the various advantages and challenges of using the platform for e-learning. This paper proposed the E-Learning IoT architecture with Blockchain technology, with layers of different IoT and Blockchain concepts to secure the online education system. Also, the block diagram of the proposed architecture demonstrates how students can securely access or interact with the online learning system through Blockchain technology. By implementing the proposed e-learning IoT architecture, universities and colleges can improve their distance learning programs and increase efficiency without affecting their academic activities. Finally, the study found that e-learning positively impacts students' learning experience and overall quality of education. It also exhibited a significant positive impact on their flexibility and academic productivity.

Machine learning techniques are essential for processing the vast volume of IoT data efficiently, improving performance, and managing IoT applications effectively. Machine learning algorithms play a crucial role in detecting malicious attacks and anomalies in real-time IoT data analysis, thereby enhancing the security of IoT devices. The integration of big data analytics methods with machine learning techniques can further enhance IoT data analysis, improving the performance of IoT applications and overcoming related challenges. Real-time data collection using sensors like DHT11 and Gas level sensors, coupled with machine learning algorithms, enables efficient analysis of IoT data, aiding in the identification of anomalies and attacks. The comprehensive overview of enhancing IoT data analysis with machine learning provides insights for future research, including exploring advanced machine learning algorithms and optimizing data preprocessing techniques to enhance IoT data analysis capabilities.

Introduction; The global demand for food production continues to rise due to the growing population and changing consumption patterns. Traditional agricultural practices often fail to meet this demand efficiently, leading to the exploration of innovative technologies to enhance crop productivity. Wireless sensor technology (WST) has emerged as a promising tool to monitor and optimize agricultural practices, providing real-time data on various environmental parameters crucial for crop growth. Objective; This study aims to evaluate the effectiveness of wireless sensor technology in increasing crop production. By integrating WST into conventional farming practices, we seek to optimize resource usage, reduce waste, and improve crop yields. Methods; We have proposed an IoT-enabled soil nutrient classification and crop recommendation model to recommend crops. By incorporating machine learning, artificial intelligence (AI), the cloud, sensors, and other automated equipment into the decision-assisting system, farmers will be able to take decisive actions without relying entirely on regional farming offices. Results; The analysis showed that the plot using wireless sensor technology exhibited a significant increase in crop yield compared to the traditional plot. Soil moisture levels were maintained within optimal ranges, leading to better water usage efficiency. Additionally, the automated system adjusted fertilizer application based on real-time soil nutrient data, resulting in improved plant health and productivity. Conclusions; The integration of wireless sensor technology in agriculture presents a practical and effective approach to increase crop production. This technology enables precise monitoring and management of critical growth parameters, resulting in higher yields and more efficient resource use. Adopting WST can significantly contribute to meeting the global food demand while promoting sustainable farming practices.

The onset of the COVID-19 pandemic prompted a profound reconsideration of our approaches to teaching and learning. The metaverse, blending 3D digital realms with the intersection of reality and the virtual landscape, has emerged as a prospective frontier in education, offering substantial promise. Despite its potential, scant attention has been devoted in current research to examining the metaverse through the lens of education, marking it as a relatively unexplored domain. In this article, we commence by presenting the conceptualizations of the metaverse, delving into its inception, definitions, and common attributes. Subsequently, a precise delineation of the metaverse in an educational context is articulated, accompanied by an elaborate framework that undergoes thorough exploration of its distinctive features. We expound upon four conceivable applications of the metaverse in education, elucidating the rationale and providing illustrative cases for each: blended learning, language acquisition, competence-based education, and inclusive educational practices. Our primary discoveries indicate that the terms "education," "application," and "metaverse" appeared with the highest frequency and demonstrated interconnectedness. Upon analysis, it becomes evident that concepts like "challenge," "teaching," and "knowledge" have not received exhaustive research attention. Concluding our exploration, we put forth a spectrum of research topics that are pertinent to the intersection of the metaverse and education, serving as potential avenues for future scholarly investigations.