scholarly journals Advanced eNose-Driven Pedestrian Tracking Pipeline for Intelligent Car Driver Assisting System: Preliminary Results

Sensors ◽  
2022 ◽  
Vol 22 (2) ◽  
pp. 674
Author(s):  
Francesco Rundo ◽  
Ilaria Anfuso ◽  
Maria Grazia Amore ◽  
Alessandro Ortis ◽  
Angelo Messina ◽  
...  
Keyword(s):  
Air Quality ◽  
Network Architecture ◽  
Assessment System ◽  
Driving Safety ◽  
Physiological Status ◽  
Dynamic Features ◽  
Safe Driving ◽  
Preliminary Results ◽  
Sensing System ◽  
Driving Scenario

From a biological point of view, alcohol human attentional impairment occurs before reaching a Blood Alcohol Content (BAC index) of 0.08% (0.05% under the Italian legislation), thus generating a significant impact on driving safety if the drinker subject is driving a car. Car drivers must keep a safe driving dynamic, having an unaltered physiological status while processing the surrounding information coming from the driving scenario (e.g., traffic signs, other vehicles and pedestrians). Specifically, the identification and tracking of pedestrians in the driving scene is a widely investigated problem in the scientific community. The authors propose a full, deep pipeline for the identification, monitoring and tracking of the salient pedestrians, combined with an intelligent electronic alcohol sensing system to properly assess the physiological status of the driver. More in detail, the authors propose an intelligent sensing system that makes a common air quality sensor selective to alcohol. A downstream Deep 1D Temporal Residual Convolutional Neural Network architecture will be able to learn specific embedded alcohol-dynamic features in the collected sensing data coming from the GHT25S air-quality sensor of STMicroelectronics. A parallel deep attention-augmented architecture identifies and tracks the salient pedestrians in the driving scenario. A risk assessment system evaluates the sobriety of the driver in case of the presence of salient pedestrians in the driving scene. The collected preliminary results confirmed the effectiveness of the proposed approach.

Air quality assessment system based on self-driven drone and LoRaWAN network

2021 ◽  
Author(s):  
Attila Simo ◽  
Simona Dzitac ◽  
Ioan Dzitac ◽  
Mihaela Frigura-Iliasa ◽  
Flaviu Mihai Frigura-Iliasa
Keyword(s):  
Air Quality ◽  
Quality Assessment ◽  
Assessment System ◽  
Air Quality Assessment

scholarly journals A Mobile Sensing System for UrbanPM2.5Monitoring with Adaptive Resolution

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Hongjie Guo ◽  
Guojun Dai ◽  
Jin Fan ◽  
Yifan Wu ◽  
Fangyao Shen ◽  
...  
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Computational Cost ◽  
Estimation Method ◽  
Mobile Sensing ◽  
Prototype System ◽  
Adaptive Grids ◽  
Sensing System ◽  
Adaptive Resolution ◽  
Wide Range

This paper develops a mobile sensing system, the first system used in adaptive resolution urban air quality monitoring. In this system, we employ several taxis as sensor carries to collect originalPM2.5data and collect a variety of datasets, including meteorological data, traffic status data, and geographical data in the city. This paper also presents a novel method AG-PCEM (Adaptive Grid-Probabilistic Concentration Estimation Method) to infer thePM2.5concentration for undetected grids using dynamic adaptive grids. We gradually collect the measurements throughout a year using a prototype system in Xiasha District of Hangzhou City, China. Experimental data has verified that the proposed system can achieve good performance in terms of computational cost and accuracy. The computational cost of AG-PCEM is reduced by about 40.2% compared with a static grid method PCEM under the condition of reaching the close accuracy, and the accuracy of AG-PCEM is far superior as widely used artificial neural network (ANN) and Gaussian process (GP), enhanced by 38.8% and 14.6%, respectively. The system can be expanded to wide-range air quality monitor by adjusting the initial grid resolution, and our findings can tell citizens actual air quality and help official management find pollution sources.

scholarly journals Evaluation of the Policy Effect of China’s Environmental Interview System for Effective Air Quality Governance

2021 ◽  
Vol 18 (17) ◽  
pp. 9006
Author(s):  
Xue Jin ◽  
Ussif Rashid Sumaila ◽  
Kedong Yin ◽  
Zhichao Qi
Keyword(s):  
Air Quality ◽  
Environmental Protection ◽  
Environmental Sustainability ◽  
Local Governments ◽  
Local Governance ◽  
Assessment System ◽  
Control Group ◽  
Short Term ◽  
Interview System

The Ministry of Ecology and Environment of the People’s Republic of China formally proposed an environmental interview system in May 2014, which applies pressure on local governments to fulfill their responsibility toward environmental protection by conducting face-to-face public interviews with their officials. In this paper, 48 cities that were publicly interviewed from 2014–2020 were considered the experimental group and 48 cities surrounding them were the control group. First, the dynamic panel model is applied to initially determine the effect of the policy. Then, a regression discontinuity method (Sharp RD) is used to analyze the short-term and long-term effects and compare the reasons for the differences observed among the estimates of various types of samples. Finally, a series of robustness tests were also conducted. The results show that the environmental interview system can improve air quality. However, because an emergency short-term local governance system exists at present, the governance effect is not long-term and, therefore, not sustainable. Therefore, it suggests that the government should continue to improve the environmental interview system, establish an optimal environmental protection incentive mechanism, and encourage local governments to implement environmental protection policies effectively in the long term. The results of the research are of great significance to the environmental impact assessment system of the world, especially in countries with similar economic systems, which are facing a trade-off between economic growth and environmental sustainability.

An integrated multi-model approach for air quality assessment: Development and evaluation of the OSCAR Air Quality Assessment System

2008 ◽  
Vol 23 (3) ◽  
pp. 268-281 ◽  
Author(s):  
Ranjeet S. Sokhi ◽  
Hongjun Mao ◽  
Srinivas T.G. Srimath ◽  
Shiyuan Fan ◽  
Nutthida Kitwiroon ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Assessment ◽  
Assessment System ◽  
Assessment Development ◽  
Air Quality Assessment ◽  
Model Approach

How sleep problems contribute to simulator sickness: Preliminary results from a realistic driving scenario

2018 ◽  
Vol 28 (2) ◽  
Author(s):  
Ellemarije Altena ◽  
Yannick Daviaux ◽  
Ernesto Sanz‐Arigita ◽  
Emilien Bonhomme ◽  
Étienne Sevin ◽  
...  
Keyword(s):  
Sleep Problems ◽  
Simulator Sickness ◽  
Preliminary Results ◽  
Driving Scenario

A Novel Hierarchical Group-Based Overlay Healthcare Network

2017 ◽  
Vol 8 (4) ◽  
pp. 81-102
Author(s):  
Foteini Andriopoulou ◽  
Konstantinos Birkos ◽  
Dimitrios Lymberopoulos
Keyword(s):  
Network Architecture ◽  
Response Times ◽  
Healthcare Services ◽  
Peer To Peer ◽  
Dynamic Features ◽  
Healthcare Network ◽  
The Social ◽  
Peer To Peer Networks ◽  
Secure Network ◽  
Structured Overlays

In the healthcare domain, there is a challenge on how to design a scalable, dynamic, robust and secure network for provisioning personalized healthcare services remotely with an efficient and accurate manner. In the present work, motivated by innovations in the networking domain and the benefits of clustering in the peer-to-peer networks as well as the group-based approach of the social networks, we propose a novel hierarchical peer-to-peer overlay healthcare network for communication and collaboration among healthcare professionals, paramedical staff and patients. The proposed network includes two types of hierarchy: the first type is used for regular requests and communication while the second type handles emergency requests. The network architecture is based on multiple and enhanced structured overlays that provide scalability, dynamic features, load-balancing and low response times with guaranteed information retrieval. Moreover, a novel and effective lookup mechanism supports complex queries with significantly lower response time and messaging overhead.

A CNN-BASED RETINAL IMAGE QUALITY ASSESSMENT SYSTEM FOR TELEOPHTHALMOLOGY

2019 ◽  
Vol 19 (05) ◽  
pp. 1950030 ◽  
Author(s):  
XUEWEI WANG ◽  
SHULIN ZHANG ◽  
XIAO LIANG ◽  
CHUN ZHENG ◽  
JINJIN ZHENG ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Retinal Image ◽  
Network Architecture ◽  
Image Quality Assessment ◽  
Binary Classification ◽  
Developed Countries ◽  
Assessment System ◽  
Retinal Image Quality Assessment ◽  
Multi Classification

Oculopathy is a widespread disease among people of all ages around the world. Teleophthalmology can facilitate the ophthalmological diagnosis for less developed countries that lack medical resources. In teleophthalmology, the assessment of retinal image quality is of great importance. In this paper, we propose a no-reference retinal image assessment system based on DenseNet, a convolutional neural network architecture. This system classified fundus images into good and bad quality or five categories: adequate, just noticeable blur, inappropriate illumination, incomplete optic disc, and opacity. The proposed system was evaluated on different datasets and compared to the applications based on other two networks: VGG-16 and GoogLenet. For binary classification, the good-and-bad binary classifier achieves an AUC of 1.000, and the degradation-specified classifiers that distinguish one specified degradation versus the rest achieve AUC values of 0.972, 0.990, 0.982, 0.982 for four categories, respectively. The multi-classification based on DenseNet achieves an overall accuracy of 0.927, which is significantly higher than 0.549 and 0.757 obtained using VGG-16 and GoogLeNet, respectively. The experimental results indicate that the proposed approach produces outstanding performance in retinal image quality assessment and is worth applying in ophthalmological telemedicine applications. In addition, the proposed approach is robust to the image noise. This study fills the gap of multi-classification in retinal image quality assessment.

A multi-gas sensing system for air quality monitoring

2018 ◽  
Author(s):  
Chun-Ming Huang ◽  
Yi-Jun Liu ◽  
Yi-Jie Hsieh ◽  
Wei-Lin Lai ◽  
Chun-Ying Juan ◽  
...  
Keyword(s):  
Air Quality ◽  
Gas Sensing ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Sensing System
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