The present study aims to design a low-cost smart AI-powered node to serve as a flood Early Warning System with a complete solution. The node is designed to predict forthcoming flood events by capturing and combining critical data related to such phe...
Natural disasters such as floods and earthquakes cause severe physical, social, and economic losses, highlighting the critical need for timely and reliable early warning systems. Conventional water level and structural health monitoring technologies...
Blind spot road accidents are a frequently occurring problem. Every year, several deaths are caused by this phenomenon, even though a lot of money is invested in raising awareness and in the development of prevention systems. In this paper, a blind s...
Real-time vehicle warning systems are critical for collision prevention, yet they face stringent sub-10 ms latency requirements under severe energy and computational constraints. This review systematically surveys low-latency edge computing architect...
Monitoring soil water content (SWC) can improve the effectiveness of early warning systems (EWSs) designed to mitigate rainfall-induced shallow landslide risk. In extensive areas, like along linear infrastructures, the adoption of cost-effective sens...
Earthquake Early Warning (EEW) was proved to be a potential means of disaster reduction. Unfortunately, the performance of the EEW system is largely determined by the density of EEW network. How to reduce the cost of sensors has become an urgent prob...
The use of dumpers is one of the main causes of accidents in construction sites, many of them with fatal consequences. These kinds of work machines have many blind angles that complicate the driving task due to their large size and volume. To guarant...
Traffic risks on bridge segments exhibit spatiotemporal dependence under congestion, low visibility, and sudden traffic incidents. This study develops and evaluates a reproducible simulation framework that links short-term risk-proxy forecasting with...
The floods triggered by the 29 October 2024 cut-off low in Valencia (Spain) expose a persistent challenge in disaster risk reduction: extensive meteorological and territorial data do not automatically become timely, trusted or actionable public guida...
Seismic instrumentation for earthquake early warnings (EEWs) has improved significantly in the last few years, considering the station coverage, data quality, and the related applications. The official EEW system in Taiwan is operated by the Central...
At the beginning of 2023, the Italian former prime minister, the former health minister and 17 others including the current president of the Lombardy region were placed under investigation on suspicion of aggravated culpable epidemic in connection wi...
Introduction: During the first two years of the COVID-19 pandemic, Australia implemented a series of international and interstate border restrictions. The state of Queensland experienced limited COVID-19 transmission and relied on lockdowns to stem a...
The purpose of the study is to investigate the comparative field performance of Wi-Fi, Bluetooth Classic (Bluetooth) and Bluetooth Low Energy (BLE) signal modes for integration in vehicle–pedestrian collision warning systems. The study compares these...
Reliable photovoltaic (PV) operation requires monitoring strategies that can detect performance degradation before it develops into persistent efficiency loss. This study proposes an interpretable data-driven framework for condition monitoring and ea...
Early warning systems grounded in learning analytics offer a practical route to identifying students at risk of failing, yet their adoption in Chilean undergraduate STEM courses is constrained by limited infrastructure and data availability. This stu...
Black ice poses a serious winter road-safety hazard because its transparent appearance and localized formation make dangerous pavement conditions difficult to detect before vehicles enter affected areas. Converting this hidden low-temperature risk in...
During the last two years, the COVID-19 pandemic continues to wreak havoc in many areas of the world, as the infection spreads through person-to-person contact. Transmission and prognosis, once infected, are potentially influenced by many factors, in...
Road accidents related to long-distance driving remain a major safety concern, primarily driven by fatigue and musculoskeletal discomfort. This study investigates the acceptance of driver assistance technologies, specifically seat adjustment and fati...
This paper presents findings from ongoing research that explores the ability to use Micro-Electromechanical Systems (MEMS)-based technologies and various digital communication protocols for earthquake early warning (EEW). The paper proposes a step-by...
The temperature at the base of the ear is highly correlated with the core body temperature of sheep and responds sensitively to febrile conditions, making it a valuable indicator of sheep health. In northern China, the closed housing environment duri...
14 June 2021
Depression is a common mental health disease, which has great harm to public health. At present, the diagnosis of depression mainly depends on the interviews between doctors and patients, which is subjective, slow and expensive. Voice data are a kind...
Background: Early identification of sepsis is critical for improving outcomes, particularly in low-resource emergency settings. In Thai community hospitals, where physicians may not always be available, triage is often nurse-led. Selecting accurate a...
Early and reliable detection of P-wave arrivals is critical for seismic monitoring and earthquake early warning, particularly under low signal-to-noise ratio (SNR) and non-stationary noise conditions. This study presents an automatic detection method...
With the last decades of development, earthquake early warning (EEW) has proven to be one of the potential means for disaster mitigation. Usually, the density of the EEW network determines the performance of the EEW system. For reducing the cost of s...
8 February 2017
Introduction: The U.S. Food and Drug Administration (FDA) has estimated the economic impact of Graphic Warning Labels (GWLs). By omitting the impact on tobacco consumption by pregnant women, the FDA analysis underestimates the economic benefits that...
Background/Objectives: Since high frequencies are susceptible to disruption in various types of hearing loss, a symptom which is common in people with tinnitus, the aim of the study was to investigate EEG cortical auditory evoked and P300 responses t...
Worldwide, cities with mountainous areas struggle with an increasing landslide risk as a consequence of global warming and population growth, especially in low-income informal settlements. Landslide Early Warning Systems (LEWS) are an effective measu...
Background: Given the rapid global increase in asthma cases, understanding the impact of climate change on respiratory health is necessary for evidence-based policymaking, particularly in low- and middle-income countries (LMICs). Objectives: To estim...
Unstable rock blocks and cliffs pose a widespread geohazard, and their mechanical state can be tracked through their ambient-vibration resonance frequencies, whose decrease anticipates progressive failure. Such monitoring is usually performed with ex...
In response to the critical need for enhanced resource management in the construction industry, this research develops an innovative, integrated methodology that synergistically combines Agent-Based Modeling (ABM), Building Information Modeling (BIM)...
We analyzed a large number (77) of low-to-medium-magnitude earthquakes (M3.5–M6.5) that occurred within a period of three years (2020–2022) in the Southern half of Greece in relation to the ELF activity in that region and time period. In...
To enhance real-time S-wave detection in the railway earthquake early warning (EEW) system, we improved the existing short-term average/long-term average (STA/LTA) algorithm. This enhancement focused on developing a more robust and computationally ef...
Layered sensor networks that monitor low-altitude airspace must detect heterogeneous aerial traffic, yet sensor deployment is usually optimized against a single fixed traffic case and can leave an entire target kind undetected when the composition ch...
Air pollution is a widespread problem due to its impact on both humans and the environment. Providing decision makers with artificial intelligence based solutions requires to monitor the ambient air quality accurately and in a timely manner, as AI mo...
Urban seismic networks are considered very useful tools for the management of seismic emergencies. In this work, a study of the first urban seismic network in central Italy is presented. The urban seismic network, built using MEMS sensors, was implem...
More and more human activities are increasingly dependent on the power quality energy they are supplied. In particular, those loads that have an electronic switching mode power supply (SMPS) and microcontrollers or microprocessors are very susceptibl...
In recent years, the development of low-cost GNSS sensors allowed monitoring in a continuous way movement related to natural processes like landslides with increasing accuracy and limited efforts. In this work, we present the first results of an expe...
Storm Daniel initiated on 3 September 2023, over the Northeastern Aegean Sea, causing extreme rainfall levels for the following four days, reaching an average of about 360 mm over the Peneus basin, in Thessaly, Central Greece. This event led to exten...
Fatalities from landslides are rising worldwide, especially in cities in mountainous regions, which often expand into the steep slopes surrounding them. For residents, often those living in poor neighborhoods and informal settlements, integrated land...
Affected by an insufficient understanding of oxidation characteristics and the CO production mechanism in low-rank coal goaf, the safety management of coal spontaneous combustion (CSC) faces severe challenges. In this study, in-depth research was con...
Xylella fastidiosa is a devastating pathogen that has significantly impacted olive cultivation, particularly in Southern Italy, since 2013. Monitoring and early identification are crucial for managing the spread of this disease and minimising associa...
Discrepancies between announced regional seismic intensity and shaking experienced indoors may affect household mitigation and risk communication. We report a three-year field experiment (2021–2024) in the Greater Tokyo Metropolitan Area combin...
Background/Objectives: In-hospital cardiac arrest (IHCA) remains a devastating event associated with high morbidity and mortality among general ward patients. While Rapid Response Systems (RRS) can help identify deteriorating patients, maintaining th...
In high-altitude trout raceways, dissolved oxygen (DO) declines are brief and start from a narrow margin below saturation. We built a solar-powered floating node with five water-quality channels, a serviceable probe cartridge, switched sensor rails a...
Deaths and serious injuries caused by traffic accidents is a concerning public health problem. However, the problem can be mitigated by the Autonomous Emergency Braking (AEB) system, which can avoid the impact. The market penetration of AEB is expone...
To improve the accuracy of debris flow forecasts and serve as disaster prevention and mitigation, an accurate and intelligent early warning method of debris flow initiation based on the IGWO-LSTM algorithm is proposed. First, the entropy method is em...
2 September 2021
With developments in science and technology, the number of electric vehicles will increase, and they will even replace ICE vehicles. Thus, perceiving the presence of approaching electric vehicles on the road has become an important issue. In this stu...
To ensure the security of mobile payments, anti-fraud warning messages serve as a critical defensive interface between users and potential risks. The effectiveness of their design directly influences users’ risk perceptions and security-related...
Ecologically fragile areas in China account for more than half of its land area. Performing early warning assessments and trend analyses of resource and environment carrying capacity in ecologically fragile areas can lay a scientific foundation for e...
Rear-end collisions often cause serious traffic accidents. Conventionally, in intelligent transportation systems (ITS), radar collision warning methods are highly accurate in determining the inter-vehicle distance via detecting the rear-end of a vehi...
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