Pipelines that satisfy k-anonymity alone remain vulnerable to attribute disclosure under skewed sensitive attributes. We studied real-time anonymization of high-throughput data streams under strict delay budgets (β). We jointly enforced k-anonym...
Sensors and other Internet of Things (IoT) technologies are increasingly finding application in various fields, such as air quality monitoring, weather alerts monitoring, water quality monitoring, healthcare monitoring, etc. IoT sensors continuously...
Hand Gesture Recognition (HGR) is a vital technology that enables intuitive human–computer interaction in various domains, including augmented reality, smart environments, and assistive systems. Achieving both high accuracy and real-time perfor...
Today, big data are generated from many sources, and there is a huge demand for storing, managing, processing, and querying on big data. The MapReduce model and its counterpart open source implementation Hadoop, has proven itself as the de facto solu...
Today, the use of digital medicine is becoming more and more common in medicine. With the use of digital medicine, health data can be shared, processed, and visualized using computer algorithms. One of the problems currently facing digital medicine i...
In face-to-face and online learning, emotions and emotional intelligence have an influence and play an essential role. Learners’ emotions are crucial for e-learning system because they promote or restrain the learning. Many researchers have investiga...
This work presents a data-centric strategy to meet deadlines in soft real-time applications in wireless sensor networks. This strategy considers three main aspects: (i) The design of real-time application to obtain the minimum deadlines; (ii) An anal...
In recent years, the application and wide adoption of Internet of Things (IoT)-based technologies have increased the proliferation of monitoring systems, which has consequently exponentially increased the amounts of heterogeneous data generated. Proc...
The integrity of real-time data streams has not been solved for a long time and has gradually become a difficult problem in the field of data security. Most of the current data integrity verification schemes are constructed using cryptographic algori...
The real-time analysis of Big Data streams is a terrific resource for transforming data into value. For this, Big Data technologies for smart processing of massive data streams are available, but the facilities they offer are often too raw to be effe...
Smart logistics systems generate massive amounts of data, such as images and videos, requiring real-time processing in edge clusters. However, the edge cluster systems face performance bottlenecks in reception and forwarding high-concurrency data str...
Scalable real-time processing of large amounts of data has become a research topic of particular importance due to the continuously rising amount of data that is generated by devices equipped with sensing components. While existing approaches allow f...
Nowadays, ubiquitous technology makes life easier, especially devices that use the internet (IoT). IoT devices have been used to generate data in various domains, including healthcare, industry, and education. However, there are often problems with t...
Through social media platforms, massive amounts of data are being produced. As a microblogging social media platform, Twitter enables its users to post short updates as “tweets” on an unprecedented scale. Once analyzed using machine learn...
The rapid expansion of IoT in smart cities has improved traffic management but increased security risks. Traditional IDS struggle with advanced threats, prompting adaptive solutions. This work proposes a framework combining machine learning (ML), Zer...
Owing to the recent advancements in Internet of Things technology, social media, and mobile devices, real-time stream balancing processing systems are commonly used to process vast amounts of data generated in various media. In this paper, we propose...
Modern agricultural operations generate high-volume and diverse data (historical and stream) from various sources, including IoT devices, robots, and drones. This paper presents a novel smart farming architecture specifically designed to efficiently...
The rapid growth of Internet of Things (IoT) devices generates high-dimensional, high-velocity data streams that demand real-time machine learning (ML) inference under strict hardware constraints. We propose the Adaptivecoreset Selection Engine (ACS-...
There is an increasing impetus for the use of digital city models and sensor network data to understand the current demand for utility resources and inform future infrastructure service planning across a range of spatial scales. Achieving this requir...
Most unmanned aerial vehicle (UAV) ground control station (GCS) solutions today are either web-based or native applications, primarily designed to support a single UAV. In this paper, our research aims to provide an open, universal framework intended...
Near real-time data warehousing is an important area of research, as business organisations want to analyse their businesses sales with minimal latency. Therefore, sales data generated by data sources need to reflect immediately in the data warehouse...
The large amount of programmable logic controller (PLC) sensing data has rapidly increased in the manufacturing environment. Therefore, a large data store is necessary for Big Data platforms. In this paper, we propose a Hadoop ecosystem for the suppo...
Distributed stream processing engines (DSPEs) deploy multiple tasks on distributed servers to process data streams in real time. Many DSPEs have provided locality-aware stream partitioning (LSP) methods to reduce network communication costs. However,...
The growing adoption of wearable devices creates a critical need for robust and secure Internet of Things solutions to manage biometric data streams. Current architectures often lack emphasis on seamless data capture, secure cloud storage and integra...
A secure data stream is important for the real time communications of Internet of Things (IoT). A stream cipher with the characteristics of simple and high speed is suitable in the secure communications of IoT for its security. Some stream ciphers ba...
MedROAD V3 is a real-time FHIR R4 streaming platform that turns clinical sensor streams into calibrated deterioration risk, evaluated retrospectively on a cardiac ICU cohort. FHIR event sourcing, Kafka and Faust assemble an 86-element feature vector...
In modern industrial environments, data-driven decision-making plays a crucial role in ensuring operational efficiency, predictive maintenance, and process optimization. However, the effectiveness of these decisions is highly dependent on the quality...
The aboveground fresh weight of weeds is an important indicator that reflects their biomass and physiological activity and directly affects the criteria for determining the amount of herbicides to apply. In precision agriculture, the development of m...
The volume of streaming sensor data from various environmental sensors continues to increase rapidly due to wider deployments of IoT devices at much greater scales than ever before. This, in turn, causes massive increase in the fog, cloud network tra...
The rapid growth of data streams, propelled by the proliferation of sensors and Internet of Things (IoT) devices, presents significant challenges for real-time clustering of high-dimensional data. Traditional clustering algorithms struggle with high...
As a network transmission protocol, Networked Transport of RTCM via Internet Protocol (NTRIP) is widely used in GPS and Global Orbiting Navigational Satellite System (GLONASS) Augmentation systems, such as Continuous Operational Reference System (COR...
Controlling active and passive systems in buildings with the aim of optimizing energy efficiency and maintaining occupants’ comfort is the major task of building management systems. However, most of these systems use a predefined configuration,...
Twitter is a microblogging platform that generates large volumes of data with high velocity. This daily generation of unbounded and continuous data leads to Big Data streams that often require real-time distributed and fully automated processing. Has...
Because of the specific characteristics of Unmanned Aerial Vehicle (UAV) networks and real-time applications, the trade-off between delay and reliability imposes problems for streaming video. Buffer management and drop packets policies play a critica...
Strict air pressure control is paramount in industries such as petroleum, chemicals, transportation, and mining to ensure production safety and to improve operational efficiency. In these fields, accurate real-time air pressure monitoring is critical...
The rich and valuable underwater cultural heritage present in the Mediterranean is often overlooked, if not completely unknown, due to the inherent difficulties in using physical approaches. The iblueCulture project was created to bridge that gap by...
Today, advanced websites serve as robust data repositories that constantly collect various user-centered information and prepare it for subsequent processing. The data collected can include a wide range of important information from email addresses,...
The nature of contemporary spatial data infrastructures lies in the provision of geospatial information in an on-demand fashion. Although recent applications identified the need to react to real-time information in a time-critical way, research effor...
Recent advances in immersive computing and artificial intelligence have enabled the development of adaptive, human-centered digital healthcare systems. This paper presents CareSync, an emotion-aware, data-driven architecture for personalized interven...
Smart mining solutions currently suffer from inadequate big data support and insufficient AI applications. The main reason for these limitations is the absence of a comprehensive industrial internet cloud platform tailored for the coal industry, whic...
Smartphones with the Android operating system can acquire Global Navigation Satellite System (GNSS) raw pseudorange and carrier phase observations, which can provide a new way for the general public to obtain precise position information. However, on...
Time series databases aim to handle big amounts of data in a fast way, both when introducing new data to the system, and when retrieving it later on. However, depending on the scenario in which these databases participate, reducing the number of requ...
The Tactile Internet will require ultra-low latencies for combining machines and humans in systems where humans are in the control loop. Real-time and perceptual coding in these systems commonly require content-specific approaches. We present a gener...
This paper introduces a new and expressive algorithm for inducing descriptive rule-sets from streaming data in real-time in order to describe frequent patterns explicitly encoded in the stream. Data Stream Mining (DSM) is concerned with the automatic...
Ensuring the trustworthiness of data used in real-time analytics remains a critical challenge in smart city monitoring and decision-making. This is because the traditional data validation methods are insufficient for handling the dynamic and heteroge...
Using different statistical analysis methods to examine hydrologic time-series data is the basis of accurate hydrologic status analysis. With the wide application of the Internet of Things and sensor technologies, traditional statistical analysis met...
Several commercial seismometers now support CSTP, the real-time communication protocol used in the China Earthquake Early Warning System, but there is still no simple, flexible, and low-cost solution to archive CSTP streams or integrate them into exi...
Stream processing frameworks have become key enablers of real-time data processing in modern distributed systems. However, robust and scalable mechanisms for verifying temporal properties are often lacking in existing systems. To address this gap, a...
Yunnan Province, residing in the eastern segment of the Qinghai–Tibet Plateau and the western part of the Yunnan–Guizhou Plateau, faces significant challenges due to its intricate geological structures and frequent geohazards. These pose...
Sensor data streams often represent signals/trajectories which are twice differentiable (e.g., to give a continuous velocity and acceleration), and this property must be reflected in their segmentation. An adaptive streaming algorithm for this proble...
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