Current navigation systems use multi-sensor data to improve the localization accuracy, but often without certitude on the quality of those measurements in certain situations. The context detection will enable us to build an adaptive navigation system...
Conservation detection dogs (CDDs) are trained to locate biological material from plants and animals of interest to conservation efforts and are often more effective and economical than other detection methods. However, the financial costs of develop...
Accurate, ubiquitous and reliable navigation can make transportation systems (road, rail, air and marine) more efficient, safer and more sustainable by enabling path planning, route optimization and fuel economy optimization. However, accurate naviga...
When unmanned aerial vehicles (UAVs) perform transmission line ice cover detection, it is often due to the variable shooting angle and complex background environment, which leads to difficulties such as poor ice-covering recognition accuracy and diff...
Object detection in remotely sensed (RS) satellite imagery has gained significance in smart city concepts, which include urban planning, disaster management, and environmental monitoring. Deep learning techniques have shown promising outcomes in obje...
In the context of environmental monitoring, maximum levels of nitrogen dioxide (NO2) are internationally regulated since long exposure impacts health. In general, very low concentrations in the sub-ppm range are found for NO2, which implies the need...
Environmental monitoring, such as analyses of water bodies to detect anomalies, is recognized worldwide as a task necessary to reduce the impacts arising from pollution. However, the large number of data available to be analyzed in different contexts...
Environmental monitoring is required to understand the effects of various kinds of phenomena such as a flood, a typhoon, or a forest fire. To detect the environmental conditions in remote places, monitoring applications employ the sensor networks to...
Environmental conditions are increasingly recognized as important contributors to the emergence and spread of antimicrobial resistance (AMR), yet early detection of high-risk situations remains difficult. This study developed a data-driven framework...
The PointPillars algorithm can detect vehicles, pedestrians, and cyclists on the road, and is widely used in the field of environmental awareness in autonomous driving. However, its feature encoding network only uses a minimalist PointNet network for...
Policy documents across the globe call for citizen engagement to fight climate change emergencies and build more sustainable societies. They also recognize the key role of formal and non-formal education in preparing citizens to address those challen...
In modern cars, the Passive Keyless Entry and Start system (PKES) has been extensively installed. The PKES enables drivers to unlock and start their cars without user interaction. However, it is vulnerable to relay attacks. In this paper, we propose...
Nowadays, we observe a great interest in air pollution, including exhaust fumes. This interest is manifested in both the development of technologies enabling the limiting of the emission of harmful gases and the development of measures to detect exce...
In the context of improving aircraft safety, this work focuses on creating and testing a graphene-based ice detection system in an environmental chamber. This research is driven by the need for more accurate and efficient ice detection methods, which...
Ensuring the reliability of power transmission systems depends on the accurate detection of defects in insulators, which are subject to environmental degradation and mechanical stress. Traditional inspection methods are time-consuming and often ineff...
With the rapid development of Internet of Things Technology, speech recognition has been applied more and more widely. Chinese Speech Recognition is a complex process. In the process of speech-to-text conversion, due to the influence of dialect, envi...
Technologies for the detection of dim and small targets in infrared images play an increasingly important role in various applications, including military early warning, precise guidance, military reconnaissance, environmental monitoring, and aerospa...
Formaldehyde, a ubiquitous indoor air pollutant, plays a significant role in various biological processes, posing both environmental and health challenges. This comprehensive review delves into the latest advancements in electrochemical methods for d...
Novel methods for species detection based on collection of environmental DNA (eDNA) are not only important in biodiversity assessment in a scientific context, but are also increasingly being applied in conservation practice. The eDNA-based biodiversi...
The wide-spread usage of ciprofloxacin (CIP) resulted in its presence in different parts of the ecosystem. Thus, a simple, reliable, on-spot detection method for CIP is required in environmental context. Herein, a colorimetric assay is developed for...
In the context of rapid advancements in AI, the accuracies and speeds among various AI models and methods are often compared. However, a basic question is rarely asked: is AI better than humans, and if so, under what conditions? This paper investigat...
With the rapid development of deep learning technology in recent years, convolutional neural networks have gained remarkable progress in SAR ship detection tasks. However, noise interference of the background and inadequate appearance features of sma...
Development of a rapid approach for universal microbial detection is required in the healthcare, food and environmental sectors to aid with medical intervention, food safety and environmental protection. This research investigates the use of enzymati...
Environmental monitoring should be minimally disruptive to the ecosystems that it is embedded in. Therefore, the project Robocoenosis suggests using biohybrids that blend into ecosystems and use life forms as sensors. However, such a biohybrid has li...
Functionalizing agents enhance the photophysical properties of nanomaterials, thereby broadening their applications. Among these agents, cysteamine (SH-(CH2)2-NH2) is unique because of its free thiol (-SH) and amino (-NH2) groups. The presence of fre...
Regional sustainability encourages a re-examination of development programs in the context of environmental, social and economic policies and practices. However, sustainability remains a broadly defined concept that has been applied to mean everythin...
Radio frequency (RF) spectrum sensing is critical for applications requiring precise object and posture detection and classification. This survey aims to provide a focused review of context-aware RF-based sensing, emphasizing its principles, advancem...
In hospitals and smart nursing homes, ambient-intelligent care rooms are equipped with many sensors. They can monitor environmental and body parameters, and detect wearable devices of patients and nurses. Hence, they continuously produce data streams...
In real-world applications, autonomous driving systems need to handle a variety of complex scenarios, such as object occlusion and lighting changes. In these scenarios, accurately identifying various objects is crucial for perceiving the surrounding...
The issue of pesticide and chemical residue in food has drawn increasing public attention, making effective control of plant pests and diseases a critical research focus in agriculture. Monitoring of pest populations is a key factor constraining the...
With the recent advancements in automated driving technology, object detection algorithms that can effectively respond to complex and diverse road traffic scenarios are especially important for driving safety during real driving. In this context, we...
Detecting mentions of green waste practices on social networks is a crucial tool for environmental monitoring and sustainability analytics. Social media serve as a valuable source of ecological information, enabling researchers to track trends, asses...
Integrating deep learning for crop monitoring presents opportunities and challenges, particularly in object detection under varying environmental conditions. This study investigates the efficacy of image preprocessing methods for olive identification...
The detection and quantification of nanoplastics in aquatic environments is one of the major challenges in environmental and analytical research nowadays. The use of common analytical techniques for this purpose is not only hampered by the size of na...
The increasing integration of autonomous electric vehicles (EVs) into Intelligent Transportation Systems (ITSs) needs rigorous mechanisms to ensure their safe and effective operation in dynamic environments. The reliability of such vehicles depends n...
With the rapid development of remote sensing technology, optical remote sensing images are increasingly being used in areas such as military reconnaissance, environmental monitoring, and urban planning. Due to the small number of pixels, fuzzy featur...
Molecularly imprinted polymers (MIPs) provide selective, robust, and cost-effective platforms for the detection and removal of small toxic molecules in environmental, food, and biomedical contexts. This review offers a comprehensive overview of recen...
Recent developments in intelligence surveillance camera systems have enabled more research on the detection, tracking, and recognition of humans. Such systems typically use visible light cameras and images, in which shadows make it difficult to detec...
In the realm of autonomous vehicle technology, the multimodal vehicle detection network (MVDNet) represents a significant leap forward, particularly in the challenging context of weather conditions. This paper focuses on the enhancement of MVDNet thr...
Bisphenols (BPs) are ubiquitous environmental endocrine disruptors that cause various human health hazards and pollute water, soil, and the atmosphere to varying degrees. Although various studies have investigated the pollution characteristics and he...
The integration of Artificial Intelligence (AI) into remote sensing data classification has revolutionized agriculture and environmental monitoring. AI is one of the main technologies used in smart farming that enhances and optimizes the sustainabili...
Small mammals, and particularly rodents, are common inhabitants of farmlands, where they play key roles in the ecosystem, but when overabundant, they can be major pests, able to reduce crop production and farmers’ incomes, with tangible effects on th...
The increasing global population and environmental changes pose significant challenges to food security and sustainable agricultural practices. To overcome these challenges, protecting farm animals and effectively detecting potential environmental th...
Thanks to their multiple outstanding features—such as high fluorescence quantum yield, good photostability, and excellent sensitivity—conjugated polymers (CPs) have emerged as a pioneering class of fluorescent materials for sensing applic...
This review aims to explore the literature to assess the potential of artificial intelligence (AI) in environmental monitoring for predicting microbiome dynamics. Recognizing the significance of comprehending microorganism diversity, composition, and...
The usefulness of wastewater-based epidemiology (WBE) was proven during the COVID-19 pandemic, and the role of environmental monitoring of emerging infectious diseases has been recognized. In this study, the prevalence of carbapenem-resistant Enterob...
Aquatic resistomes are important reservoirs of antibiotic resistance genes (ARGs) and their precursors, which can proliferate and dissipate in pathogenic microorganisms that affect humans and animals, especially due to anthropogenic pressures such as...
8 October 2023
Cemeteries can be compared to landfills, as the leachate produced in these areas, also known as necroleachate, can be environmentally transported, polluting groundwater, surface water, and soil. In Brazil, to ensure no negative environmental impacts...
17 August 2022
In the context of the rapid development of the world’s nuclear power industry, it is necessary to establish background data on radionuclides of different samples from different regions, and the premise of obtaining such basic data is to have a...
Smart home technology with situation-awareness is important for seniors to improve safety and security. With the development of context-aware computing, wearable sensor technology, and ubiquitous computing, it is easier for seniors to manage their he...
of 15