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117 articles for “Big Data Management”
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Smart City Solutions for Waste Management and Pollution Control
Abstract: Recent trends in the role of artificial intelligence, IoT, and other smart technologies have a critical role toward addressing urban environmental challenges related to air quality and waste management in the context of a smart city. This changes the scope of managing air quality as, with the integration of IoT sensors, big data, and AI, they are able to predict pollution levels through real time monitoring and analysis. These technologies …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 11–22 Read article
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Research Challenges in the Era of AI and Digitization for Sustainable Supply Chains
Abstract: Two main topics have an impact on the adoption of sustainability as a worldwide business mandate. The first is admitting that global supply networks have an impact on sustainability and that "greening" the chain as a whole is necessary. Technology, encompassing "big data," artificial intelligence (AI), and digitization, is the second. These ideas are now widely accepted. These innovations are transforming how firms design and manage their supply chains, which …
Published in Journal of Production Research & Management · Vol. 14, Issue 1, 2024 · pp. 1–10 Read article
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Enhancing Safety Protocols in Industrial Operations
Abstract: Industrial safety is a crucial aspect of maintaining both operational efficiency and protecting the workforce in hazardous environments. Despite significant advancements in safety technologies and regulatory frameworks, industrial accidents remain a persistent problem, often leading to severe injuries, fatalities, and financial losses. Such incidents typically arise from a combination of factors, including human error, equipment malfunctions, and insufficient safety protocols. In response to these challenges, this paper examines key strategies …
Published in Journal of Industrial Safety Engineering · Vol. 11, Issue 3, 2024 · pp. 1–5 Read article
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IoT Meets Cloud: A Smart Integration
Abstract: Digital transformation and industry change are fueled by a combination of cloud computing and the Internet of Things (IoT). While cloud computing gives scalable resources for processing, storage, and advanced analytics, IoT allows devices to gather, distribute, and analyze data in real time. This connection supports big data and machine learning-driven applications and enhances data management and operational efficiency across industries, such as smart cities, industrial automation, healthcare, and agriculture. …
Published in Journal of Web Engineering & Technology · Vol. 12, Issue 3, 2025 · pp. 26–34 Read article
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Digital Growth and Natural Decline: Investigating the Tech-Nature Paradox
Abstract: This paper critically examines the ideology and multifaceted impact of technology on the environment, highlighting both the detrimental consequences and the transformative potential of technological advancement. Technology, generally defined as the application of scientific knowledge for practical human purposes, has dramatically reshaped every aspect of modern life, including communication, healthcare, education, transportation, and industry. While these developments have enhanced the standard of living, they have also contributed significantly to environmental …
Published in Research & Reviews : Journal of Ecology · Vol. 14, Issue 3, 2025 · pp. 6–11 Read article
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Big Data Dimensionality Reduction Technique with Deep Autoencoder
Abstract: Dimensionality reduction refers to the act of narrowing the focus from an abundance of potential variables to a more manageable set. Google created the open-source Flutter framework for creating mobile apps. The issue of high-dimensional data hindered the system's effectiveness in terms of providing correct findings (the quantity of false-positive, negative, true-positive, and negative outcomes). The process of solving a classification problem, carrying out a precise visualization, and transmitting vast …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 2, 2023 · pp. 1–13 Read article
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Industry 4.0 and Smart Supply Chains: Transforming Supply Chain Processes for Enhanced Efficiency and Sustainability
Abstract: The fourth industrial revolution, or Industry 4.0, is an important transformation in how industries function via the use of cutting-edge digital technology. Supply chain management is being substantially altered by integrating technologies like blockchain, big data, automated processes, artificial intelligence, and the internet of things into typical operations of the supply chain. With the help of these technologies, corporations can design intelligent supply chains that are more effective, flexible, and …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 36–41 Read article
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Java’s Enduring Popularity: Unraveling the Factors Behind Its Preference
Abstract: Java remains one of the most widely used programming languages across various industries, owing to its robust architecture, platform independence, and extensive ecosystem. Its versatility, scalability, and security make it a preferred choice for developing a wide range of applications, from enterprise software to mobile and web solutions. This study delves into the key factors contributing to Java’s sustained relevance in software development, highlighting its adaptability to evolving technological trends. …
Published in Recent Trends in Programming languages · Vol. 12, Issue 1, 2025 · pp. 8–15 Read article
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A Survey on Big Data Storage Issues in Cloud Computing Environment
Abstract: AbstractBig data is the collection of large set of data which holds many intelligence and raw information. In the digital world, handling and updating large volume of data in the real-time environment is a challenging task. This paper presents a compressive discussion on analytical techniques and processing methods for analysing the applications of big data with the purpose of constructing valuable information in cloud computing environment. This research aims to …
Published in Journal of Advanced Database Management & Systems · Vol. 4, Issue 3, 2017 · pp. 1–5 Read article
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Comparison Between Machine Learning and Big Data for Spam E-mail Detection
Abstract: AbstractEmail spam is tasks which are sending the unwanted messages to various email customers. Email spam is the ongoing issue for each person. The email spam is nothing but a notice of any organization/item or any sort of infection which is getting by the email customer post box with no warning. To take care of this issue, the diverse spam sifting procedure is utilized. The spam sifting procedures are utilized …
Published in Journal of Advanced Database Management & Systems · Vol. 6, Issue 2, 2019 · pp. 30–35 Read article
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The Review on Big Data Sharding and Replication
Abstract: AbstractSharding is a partitioning pattern that places each partition in potentially separate servers; potentially all over the world. A shard is managed by a single server. Data replication is the process of storing data in more than one site or node. It is useful in improving the availability of data. It is simply copying data from a database from one server to another server so that all the users can …
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 3, 2020 · pp. 1–10 Read article
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The Role of IoT in Sustainable Agriculture: Leveraging Big Data for Precision Farming
Abstract: Precision farming combined with the Internet of Things (IoT) is transforming the agricultural industry by boosting productivity and encouraging sustainable practices.. This paper explores the transformative impact of IoT technologies on modern agriculture, focusing on how big data analytics can be leveraged to optimize farming practices, reduce waste, and conserve resources. The Internet of Things (IoT) offers real-time data on a range of agricultural characteristics, including soil moisture, temperature, humidity, …
Published in Journal of Instrumentation Technology & Innovations · Vol. 14, Issue 2, 2024 Read article
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Decoding Big Data: A Practical Comparison Between Hadoop and Spark
Abstract: This paper conducts a comprehensive comparison of Apache Hadoop and Apache Spark, two essential frameworks in the big data era. The rapid expansion of data possesses challenges in terms of volume, variety, and velocity, which necessitate advanced processing solutions. Hadoop, utilizing its MapReduce paradigm, provides scalable and fault-tolerant storage, whereas Spark, built upon Hadoop, introduces in-memory processing to increase speed and flexibility. This study includes a detailed examination of their …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 3, 2024 · pp. 15–23 Read article
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Python's Applications in the Profession of Data Science
Abstract: Because of its ease of use, adaptability, and huge ecosystem of libraries, Python has become one of the most influential programming languages in the field of data science. Python is highly valued for its straightforward and versatile nature. This study delves into its various uses in data science, including tasks like data preprocessing, exploratory data analysis (EDA), statistical modeling, machine learning, and creating visualizations. Libraries like Pandas and NumPy make …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 23–30 Read article
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Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
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Remote Monitoring Sensor Systems and Applications in Health Informatics: Fostering Shell Programming
Abstract: The fascination of sensor systems has been promising for health informatics as their direct initiative for real-time information by observing its accuracy that was required at the time for data collection, monitoring and analysis to improve patient well-being and health system administering. By integrating these systems with wearable devices, biomedical sensors, and other IoT-enabled technologies, patients can experience continuous health tracking, early disease detection, and remote patient monitoring. For example, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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Advance in Spatial Statistics for Environmental Data Analysis
Abstract: Recent advancements in spatial statistics have significantly enhanced the analysis of environmental data, addressing complex spatial dependencies and offering robust methodologies for environmental monitoring, modeling, and decision-making. This abstract highlights key developments in the field, emphasizing their applications and impact. Geostatistical Methods, Improved geostatistical techniques, such as kriging and co-kriging, provide more accurate predictions of environmental variables by incorporating spatial correlation structures. Advanced kriging variants, including Bayesian kriging and machine …
Published in Research & Reviews : Journal of Statistics · Vol. 12, Issue 3, 2023 · pp. 35–39 Read article
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Employing Cyber Security in Big Data
Abstract: Big data is identified by extreme measure of information generated at a standard premise by devices and internet-based sources. To construct valuable solutions for specific fields, this data can be treated and dismembered. Different techniques of computational and data analysis have been identified for usage in this domain. It has provided upward advancement of voluminous data processing registering models and tools. In traditional systems and innovations, the capability and handling …
Published in Recent Trends in Parallel Computing · Vol. 9, Issue 2, 2022 · pp. 18–21 Read article
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Review Paper on Platform for Big Data Analytics as a Service with Stock Market Prediction and Analysis
Abstract: Petabyte-scale data is referred to as big data. The sum of the data in this quantity, which includes audio files, image files, and many more. Due to the unstructured nature of the data, it is challenging to evaluate the information that is gathered from it. As a result of social networking and cloud computing, data has significantly increased. It is therefore difficult to assess, process, and store. Big data processing …
Published in Journal of Advanced Database Management & Systems · Vol. 10, Issue 1, 2023 · pp. 1–5 Read article
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NoSQL Databases- Analysis, Techniques, and Classification
Abstract: In recent years in big data and real-time web applications, NoSQL database solutions are gaining popularity in handling massive increase in size of data storage. The design of traditional relational database management systems makes it difficult for them to take advantage of virtually unlimited processing power and economical storage available via cloud computing. In contrast to this NoSQL databases support dynamic schemas, auto-sharding, automatic replication and integrated caching capabilities prominently …
Published in Journal of Advanced Database Management & Systems · Vol. 1, Issue 2, 2014 · pp. 13–24 Read article