In the modern era, many terms related to artificial intelligence, machine learning, and deep learning are widely used in domains such as business, healthcare, industries, and military. In these fields, the accurate prediction and analysis of data are crucial, regardless of how large the data are. However, using big data is confusing due to the rapid growth and massive development in public life, which requires a tremendous human effort in order to deal with such type of data and extract worthy information from it. Thus, the role of artificial intelligence begins in analyzing big data based on scientific techniques, especially in machine learning, whereby it can identify patterns of decision-making and reduce human intervention. In this regard, the significance role of artificial intelligence, machine learning and deep learning is growing rapidly. In this article, the authors decide to highlight these sciences by discussing how to develop and apply them in many decision-making domains. In addition, the influence of artificial intelligence in healthcare and the gains this science provides in the face of the COVID-19 pandemic are highlighted. This article concludes that these sciences have a significant impact, especially in healthcare, as well as the ability to grow and improve their methodology in decision-making. Additionally, artificial intelligence is a vital science, especially in the face of COVID-19.

ChatGPT is a state-of-the-art language model developed by OpenAI. It is part of the GPT (Generative Pre-trained Transformer) series, which are designed to generate human-like language output based on large amounts of input data. ChatGPT is one of the largest and most advanced language models to date, with 175 billion parameters. The article aims to examine the impact of artificial intelligence tools and techniques on academic research and their potential implications for academic ethics. In particular, this article will focus on the practices of ChatGPT in generating scientific research within the context of academic ethics. ChatGPT is a powerful tool that can generate text in different formats, conduct literature searches, and suggest titles for the created text. However, using ChatGPT to select topics with a low similarity score in similarity checkers may lead to ethical violations. This article finds that the use of artificial intelligence applications in academic research may raise concerns about academic ethics, and the limited availability of technologies that can detect such violations poses a significant challenge to academic writing.

Sustainable forest management is vital for addressing climate change, biodiversity loss, and deforestation. Human-induced stresses on forest ecosystems demand innovative approaches to ensure long-term health and productivity. This study explores how cutting-edge technologies, including the Internet of Things (IoT), remote sensing, and artificial intelligence (AI), enhance sustainable forest management practices. Researchers reviewed 196 studies published between 2021 and 2024 from IEEE Xplore Digital Library, MDPI, Taylor & Francis, ScienceDirect, Frontiers, Springer, SAGE, Hindawi, Nature, Wiley Online Library, and Google Scholar. The findings highlight IoT devices like drones, enabling real-time data collection on temperature, humidity, soil moisture, and tree growth, facilitating continuous forest monitoring. Remote sensing technologies, utilizing satellite imagery and aerial surveys, deliver high-resolution data for large-scale forest assessments, including forest cover changes, biomass estimation, and early detection of illegal logging. When integrated with AI, these tools enhance predictive modeling, data analysis, and decision-making, leading to more effective forest management strategies. The study also identifies challenges such as data security concerns, bandwidth limitations, interoperability issues, and high costs. Despite these barriers, IoT, remote sensing, and AI present transformative potential for improving forest resilience, carbon sequestration, and biodiversity conservation. These technologies are crucial in preserving forest ecosystems and mitigating climate change impacts by advancing real-time monitoring, optimizing resource allocation, and enabling data-driven decisions.

Brain tumors are among the most dangerous diseases that lead to mortality after a period of time from injury. Therefore, physicians and healthcare professionals are advised to make an early diagnosis of brain tumors and follow their instructions. Magnetic resonance imaging (MRI) is operated to provide sufficient and practical data in detecting brain tumors. Applications based on artificial intelligence contribute a very large role in disease detection, provide incredible accuracy and assist in creating the right decisions. In particular, deep learning models, which are a significant part of artificial intelligence, have the ability to diagnose and process medical image datasets. In this concern, one of the deep learning techniques (MobileNetV1model) is utilized to detect brain disease from 1265 images gathered from the Kaggle platform. The behavior of this model is studied through four main metrics. This article deduced that this model has a significant effect in diagnosing these images from the most important metric, which is accuracy, as it gained an accuracy result of more than 97%, which is an excellent effect.

Wireless sensor networks and Internet of Things devices are revolutionizing the smart agriculture industry by increasing production, sustainability, and profitability as connectivity becomes increasingly ubiquitous. However, the industry has become a popular target for cyberattacks. This survey investigates the role of artificial intelligence (AI) in improving cybersecurity in smart agriculture (SA). The relevant literature for the study was gathered from Nature, Wiley Online Library, MDPI, ScienceDirect, Frontiers, IEEE Xplore Digital Library, IGI Global, Springer, Taylor & Francis, and Google Scholar. Of the 320 publications that fit the search criteria, 180 research papers were ultimately chosen for this investigation. The review described advancements from conventional agriculture to modern SA, including architecture and emerging technology. It digs into SA’s numerous uses, emphasizing its potential to transform farming efficiency, production, and sustainability. The growing reliance on SA introduces new cyber threats that endanger its integrity and dependability and provide a complete analysis of their possible consequences. Still, the research examined the essential role of AI in combating these threats, focusing on its applications in threat identification, risk management, and real-time response mechanisms. The survey also discusses ethical concerns such as data privacy, the requirement for high-quality information, and the complexities of AI implementation in SA. This study, therefore, intends to provide researchers and practitioners with insights into AI’s capabilities and future directions in the security of smart agricultural infrastructures. This study hopes to assist researchers, policymakers, and practitioners in harnessing AI for robust cybersecurity in SA, assuring a safe and sustainable agricultural future by comprehensively evaluating the existing environment and future trends.