Predictive business process monitoring is predicting the next stage of the business process based on the sequence of events that have occurred in the business process instance, which is positive for promoting the rational allocation of resources and...
This study addresses the growing need for intelligent monitoring in aquaponic systems by developing a predictive system based on artificial intelligence and environmental sensing. The goal is to improve fish welfare through the early detection of adv...
The analysis of business processes based on their observed behavior recorded in event logs can be performed with process mining. This method can discover, monitor, and improve processes in various application domains. However, the process models prod...
Predictive process monitoring estimates the future behaviour of running process instances based on historical event logs, with typical tasks including next-activity prediction, remaining-time estimation, and risk assessment. Existing recurrent and Tr...
Predictive Process Monitoring (PPM) has been integrated into process mining use cases as a value-adding task. PPM provides useful predictions on the future of the running business processes with respect to different perspectives, such as the upcoming...
This paper is concerned with the implementation and field-testing of an edge device for real-time condition monitoring and fault detection for large-scale rotating equipment in the UK water industry. The edge device implements a local digital twin, p...
Predictive process monitoring (PPM) has been discussed as a use case of process mining for several years. PPM enables foreseeing the future of an ongoing business process by predicting, for example, relevant information on the way in which running pr...
The global effort to manage diabetes effectively is driving continuous innovation in glucose monitoring devices. While current systems have improved patient care, persistent challenges with sensor stability and invasiveness highlight the need for adv...
Predictive process monitoring aims to accurately predict a variable of interest (e.g., remaining time) or the future state of the process instance (e.g., outcome or next step). The quest for models with higher predictive power has led to the developm...
The paper is concerned with a methodological approach to monitoring the state of atmospheric parameters in the catchment area of Lake Baikal, including real-time analysis of actual distributed data with the determination of analog years according to...
In high-stakes decision-making environments, predictive models must deliver not only high accuracy but also reliable uncertainty estimations and transparent explanations. This study explores the integration of probability calibration techniques with...
Rising raw material costs and complex global supply chains have reduced the durability and availability of conveyor belts. In response, condition-based maintenance (CBM) with in situ diagnostics has become essential. This case study from a Polish lig...
The increasing demand for reliable and efficient power electronic systems in critical applications—such as renewable energy, electric vehicles, and aerospace—has intensified the need to understand and predict failure mechanisms in power d...
Advancements in wind turbine condition monitoring systems over the last decade have made it possible to optimise operational performance and reduce costs associated with component failure and other unplanned maintenance activities. While much researc...
Gas turbines play a crucial role in power generation and aviation, where effective maintenance strategies are essential to ensure reliability. Traditional condition monitoring methods often rely on scheduled inspections, leading to potential downtime...
Background: Today’s production facilities must be efficient in both manufacturing and maintenance. Efficiency enables the company to maintain the required output while reducing production effort or costs. With the increasing interest in process...
Underground high-voltage transmission cables, especially high-pressure fluid-filled (HPFF) pipe-type cable systems, are critical components of urban power networks. These systems consist of insulated conductor cables housed within steel pipes filled...
Predictive observation and real-time analysis of the values of biomedical signals and automatic detection of epileptic seizures before onset are beneficial for the development of warning systems for patients because the patient, once informed that an...
Air compressors are vital across various sectors—automotive, manufacturing, buildings, and healthcare—as they provide pressurized air for air suspension systems in vehicles, supply power pneumatic machines throughout industrial production...
The core of the research focuses on analyzing the discharge characteristic of a lithium NMC battery in an autonomous mobile robot, which can be used as a model to predict its future states depending on the amount of missions queued. In the presented...
Cardiovascular diseases (CVDs) are a major cause of global mortality, underscoring the need for intelligent and accessible cardiac health monitoring. This paper proposes a non-wearable Internet-of-Medical-Things (IoMT) system combining real-time sens...
Feature selection (FS) represents an essential step for many machine learning-based predictive maintenance (PdM) applications, including various industrial processes, components, and monitoring tasks. The selected features not only serve as inputs to...
As key components of low-cost sensor systems in air quality monitoring, electrochemical gas sensors have recently received a lot of interest but suffer from unit-to-unit variability and different drift components such as aging and concept drift, depe...
This research combines the application of artificial intelligence in the production equipment fault monitoring of aerospace components. It detects three-phase current abnormalities in large hot-pressing furnaces through smart meters and provides earl...
Mine slope landslides seriously threaten the safety of people’s lives and property in mining areas. Landslide prediction is an effective way to reduce losses due to such disasters. In recent years, micro-deformation monitoring radar has been wi...
Electric motors condition monitoring is a field of paramount importance for industry. In recent decades, there has been a continuous effort to investigate new techniques and methods that are able to determine the health of these machines with high ac...
This research study is part of a therapy development effort in which a novel approach was taken to develop an implantable electroencephalographic (EEG) based brain monitoring and seizure prediction system. Previous attempts to predict seizures by oth...
The development of models for process outcome prediction using event logs has evolved in the literature with a clear focus on performance improvement. In this paper, we take a different perspective, focusing on obtaining interpretable predictive mode...
There is currently no mature calculation theory to accurately predict the settlement of high-fill subgrade. This paper developed an intelligent monitoring system to accurately predict the settlement of high-fill subgrade based on on-site experiments,...
The failure of different chips under working conditions is influenced by various stress states such as different voltages, temperatures, stress durations, and stress variations. Therefore, the failure time has a great degree of dispersion, and simila...
In today’s digital landscape, organizations face significant challenges, including sensitive data leaks and the proliferation of hate speech, both of which can lead to severe consequences such as financial losses, reputational damage, and psych...
Accurate weather data are important for planning our day-to-day activities. In order to monitor and predict weather information, a two-phase weather management system is proposed, which combines information processing, bus mobility, sensors, and deep...
Droughts are one of the costliest natural disasters. Reliable drought monitoring and prediction are valuable for drought relief management. This study monitors and predicts droughts in Xinjiang, an arid area in China, based on the three drought indic...
In order to improve a livestock breeding environment that considers securing safe cattle resources and improving productivity for the intelligent farm, we propose an animal-friendly and worker-friendly intellectual monitoring system with Artificial I...
With increased urbanization, accidents related to slope instability are frequently encountered in construction sites. The deformation and failure mechanism of a landslide is a complex dynamic process, which seriously threatens people’s lives an...
As remote sensing methods have received a lot of attention, ground-based micro- deformation monitoring radars have been widely used in recent years due to their wide range, high accuracy, and all-day monitoring capability. On the one hand, these moni...
HS Solar Energy Company Inc. in Sejong city, Korea, has a big problem on how to monitor heterogeneous inverters with different protocols. Still a current photovoltaic power plant with different inverters, it has attracted significant attention to its...
Oil monitoring for wind turbine gearboxes can reflect wear and lubrication conditions, and better identify pits on the tooth surface, fatigue wear, and other early faults. However, oil monitoring with one or several single predicting models brings in...
Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring....
Hybrid drought prediction models were developed for areas with limited monitoring gauges using the APEC Climate Center Multi-Model Ensemble seasonal climate forecast and machine learning models of Extra-Trees and Adaboost. The models provide spatiall...
Gastrointestinal stromal tumors (GISTs) are rare mesenchymal neoplasms. Tyrosine kinase inhibitor (TKI) therapy is currently part of routine clinical practice for unresectable and metastatic disease. It is important to assess the efficacy of TKI trea...
This article deals with the design of a simple predictive control algorithm applied to a bidirectional DC-DC power converter for the angular speed control of a DC motor. We used the dynamics of a DC motor but mathematically reduced them to arrive at...
Monitoring and predicting land surface phenology (LSP) are essential for understanding ecosystem dynamics, climate change impacts, and forest and agricultural productivity. Satellite Earth observation (EO) missions have played a crucial role in the a...
In recent years, fishery has developed rapidly. For the vital interests of the majority of fishermen, this paper makes full use of Internet of Things and air–water amphibious UAV technology to provide an integrated system that can meet the requiremen...
Seeking a straightforward and efficient method to predict expressway traffic noise, this study selected three expressway segments in Guangdong Province, China and conducted noise monitoring at ten different sites along these expressways. Data analysi...
Mildew infestation is a significant cause of loss during grain storage. The growth and metabolism of mildew leads to changes in gas composition and temperature within granaries. Recent advances in sensor technology and machine learning enable the pre...
Chronic obstructive pulmonary disease (COPD) claimed 3.0 million lives in 2016 and ranked 3rd among the top 10 global causes of death. Moreover, once diagnosed and discharged from the hospital, the 30-day readmission risk in COPD patients is found to...
The aim of manufacturing can be described as achieving the predefined high quality product in a short delivery time and at a competitive cost. However, it is unfortunately quite challenging and often difficult to ensure that certain quality character...
Considering the shortcomings of the current monitoring system for tunnel anchor support systems, a tunnel anchor monitoring system based on LSTM-ARIMA prediction is proposed in this paper to prevent the deformation and collapse accidents that may occ...
Accurate monitoring and prediction of tool wear conditions have an important influence on the cutting performance, thereby improving the machining precision of the workpiece and reducing the production cost. However, traditional methods cannot easily...
of 309