Deep learning-driven computer vision has become a fundamental enabling technology for agricultural robotics, providing reliable perception capabilities for precision farming and autonomous field operations. Among various object detection frameworks,...
Ensuring the structural integrity and service reliability of railway wheels has become a key challenge in modern manufacturing and maintenance strategies within the railway sector. In this context, Eddy Current (EC)-based Non-Destructive Testing (NDT...
In the big data era, processing large amounts of data imposes several challenges, mainly in terms of performance. Complex operations in data science, such as deep learning, large-scale simulations, and visualization applications, can consume a signif...
Locating petroleum-productive wells using informed geological data, a conventional means, has proven to be tedious and undesirable by reservoir engineers. The former numerical simulator required a lengthy trial-and-error process to manipulate the var...
In order to enhance leakage detection accuracy in water distribution networks (WDNs) while reducing sensor deployment costs, an intelligent algorithm for the optimal deployment of water network monitoring sensors based on the automatic labelling and...
Selecting machine learning algorithms for clinical deployment demands comprehensive evaluation beyond conventional performance metrics. While automated frameworks simplify model generation, identifying algorithms suitable for real-world medical appli...
Emergency communication networks play a crucial role in disaster relief operations. Current automated deployment strategies based on rule-driven or heuristic algorithms struggle to adapt to the dynamic and heterogeneous network environments in disast...
The combination of signal processing and Artificial Intelligence (AI) is revolutionizing the robotics and automation industry by the deployment of intelligent systems and reducing human intervention. Reading human brain signal through electroencephal...
As air traffic control (ATC) automation advances, simulation environments become essential for testing and validating novel solutions before deployment. This study presents a modular framework that integrates real air traffic data to simulate control...
Accurate environmental sensing is pivotal for advancing automation in construction, particularly in autonomous excavation. Precise 3D representations of complex and dynamic site geometries is essential for obstacle detection, progress monitoring, and...
Accurate identification of the sugarcane tail tip is crucial for the real-time automation control of the harvester’s cutting device, improving harvesting efficiency, and reducing impurity rates. This paper proposes Slim-YOLO, an improved YOLO11...
Robotised Non Destructive Testing (NDT) presents multifaceted advantages, saving time and reducing repetitive manual workloads for highly skilled Ultrasonic Testing (UT) operators. Due to the requisite accuracy and reliability of the field, robotic N...
The quality grading of birch (Betula spp.) veneer logs, an economically important raw material in the Baltic region, is still largely manual, causing pricing inconsistencies, and automated grading under industrial conditions remains rarely studied. W...
Electronic manufacturing and design companies maintain test sites for a range of products. These products are designed according to the end-user requirements. The end user requirement, then, determines which of the proof of design and manufacturing t...
Ground-penetrating radar (GPR) is a non-invasive technology that uses electromagnetic pulses for subsurface exploration. In the railroad sector, it is crucial to assessing soil layers and infrastructure, offering insights into soil stratification and...
The increasing demand for real-time, energy-efficient machine learning (ML) models in edge and embedded scenarios highlights the limitations of traditional CPU-based inference pipelines. This work presents a pipeline that integrates Automated Machine...
Presently, the most common technique for maintaining a ship’s location is dynamic positioning, which uses a series of thrusters to hold its position. This method is resilient to moderate hydro-meteorological conditions, eliminating the need for...
For a decade, researchers have focused on the development and deployment of road automated mobility. In the development of autonomous driving embedded systems, several stages are required. The first one deals with the perception layers. The second on...
Olives are a crucial woody oil crop, the harvesting of which predominantly relies on manual labor, which is characterized by high costs, low efficiency, and challenges in ensuring optimal harvesting timing. The development of an automated ripeness-de...
Selective harvesting of Hotan roses requires distinguishing between buds and blooms for different industrial uses. However, balancing detection accuracy and computational efficiency for edge deployment remains a challenge. This study proposes an inte...
This study presents a Wi-Fi-based passive indoor positioning system (IPS) that does not require active collaboration from the user or additional interfaces on the device-under-test (DUT). To maximise the accuracy of the IPS, the optimal deployment of...
With the growing diversity and complexity of marine monitoring requirements, the scientific deployment of moored buoys has attracted increasing attention. To address the limitations of traditional methods—such as inconsistent knowledge represen...
Recent advancements in 3D reconstruction technologies have significantly transformed plant phenotyping, enabling precise, scalable, and automated trait extraction. Traditional manual phenotyping methods are increasingly being replaced by image-based...
Unmanned Underwater Vehicle (UUV) swarms have become increasingly crucial for underwater exploration and applications, where their coordinated operation offers significant advantages over single-vehicle systems. However, unlike single-vehicle systems...
Automated clash detection in Building Information Modelling (BIM) has reached operational maturity; however, subsequent stages of clash management, including filtering, prioritisation, resolution, and prevention, remain largely dependent on manual ex...
Automated harvesting of “Sunshine Rose” grapes requires accurate detection and classification of grape clusters under challenging orchard conditions, such as occlusion and variable lighting, while ensuring that the model can be deployed o...
Emerging low-cost gas sensor technologies have received increasing attention in recent years for air quality measurements due to their small size and convenient deployment. However, in the diverse applications these sensors face many technological ch...
Responding to a natural disaster is a short-lived and complex task requiring fast coordination and analytical skills. Responses to natural disasters must be fast, and resources need to be used in an efficient and effective manner. An automated system...
Closed-loop vasopressor systems integrate real-time blood pressure monitoring with automated decision logic to support hemodynamic stability in perioperative and critical care environments. These technologies sit at the intersection of biomedical sen...
Federated Learning (FL) enables multiple clients to train a shared model collaboratively without sharing any personal data. However, selecting a model and adapting it quickly to meet user expectations in a large-scale FL application with heterogeneou...
This article presents an innovative system for the automated classification of postures of bedridden people using laser technology. The proposed method leverages low-cost structured light hardware and a custom algorithm to determine the side on which...
This paper presents an intelligent surveillance platform based on the usage of large numbers of inexpensive sensors designed and developed inside the European Eureka Celtic project HuSIMS. With the aim of maximizing the number of deployable units whi...
Reinforcement learning (RL) is being used more in medical imaging for segmentation, detection, registration, and classification. This survey provides a comprehensive overview of RL techniques applied in this domain, categorizing the literature based...
Wireless Sensor Networks (WSNs) have emerged as a foundational technology for monitoring and data collection in diverse domains such as environmental sensing, smart agriculture, and industrial automation. Precise node localization plays a vital role...
This paper presents the design, implementation, and experimental validation of a model-free control strategy for greenhouse climate automation. The proposed approach integrates a real-time embedded controller based on a Raspberry Pi within a Cyber-Ph...
Securing critical infrastructures and manufacturing plants in the Industrial-Internet-Of-Things and Industry 4.0 is a challenge today due to the increased number of attacks against automation and SCADA systems. These systems were built without any se...
We developed a machine vision-based robotic system to address automation challenges in pharmaceutical pill sorting and packaging. The hardware platform integrates a high-resolution industrial camera with an HSR-CR605 robotic arm. Image processing lev...
The efficiency and low-carbon operation of automated container terminals (ACTs) are closely related to the coordinated scheduling of quay cranes (QCs), yard cranes (YCs), and automated guided vehicles (AGVs). Under mixed import and export tasks, unre...
Significant improvements in the forest-based industrial sector are expected due to increased digitalization; however, examples of practical implementations remain limited. This study explores the use of an automated algorithm to estimate truckload vo...
Across four decades of AI deployment, the same six human challenges (trust calibration, reliance behavior, cognitive engagement, skill retention, accountability, and transparency) recur, yet fragmentation across research communities obscures this con...
The integration of artificial intelligence (AI) into healthcare represents a paradigm shift in both clinical practice and administrative operations. This narrative review examines the transformative role of large language models (LLMs) and generative...
Industry 4.0, or smart factory, refers to the fourth industrial revolution, as a result of which it is expected that massive sensor deployment, high device connectivity, automation, and real-time data acquisition support improve industrial processes....
The rational assessment of regional energy distribution provides a scientific basis for the selection and siting of power generation units. This study, which focused on the Bohai Sea, set 31 research coordinate points in the Bohai sea for assessing t...
To address the challenges of low manual harvesting efficiency and high difficulty in automated picking of safflower filaments in the unstructured field environments of Xinjiang, this study proposes an intelligent harvesting method that integrates lig...
Location-aware services are one of the key elements of modern intelligent applications. Numerous real-world applications such as factory automation, indoor delivery, and even search and rescue scenarios require autonomous robots to have the ability t...
Photovoltaic (PV) power stations are pivotal for the renewable energy transition, yet their operational efficiency is often compromised by defects such as surface dust accumulation and cracks. Traditional manual inspections are labor-intensive and su...
Path tracking control and algorithm portability for agricultural robots serve as the core technological foundation for achieving precision and automation in farming operations, playing a critical role in ensuring food security and enhancing productio...
In Advanced Driving Assistance Systems (ADAS), Automated Driving Systems (ADS), and Driver Assistance Systems (DAS), RGB camera sensors are extensively utilized for object detection, semantic segmentation, and object tracking. Despite their popularit...
Freezing of gait (FoG) affects 38–65% of advanced Parkinson’s disease patients, yet automated detection algorithms are often validated solely on laboratory datasets. This study quantifies the critical performance gap between laboratory an...
Cloud has become one of the most widely used technologies to store data due to its availability, flexibility, and low cost. At the same time, the security, integrity, and privacy of data that needs to be stored on the cloud is the primary threat for...
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