scholarly journals Real-Time In-Vehicle Air Quality Monitoring System Using Machine Learning Prediction Algorithm

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 4956
Author(s):  
Chew Cheik Goh ◽  
Latifah Munirah Kamarudin ◽  
Ammar Zakaria ◽  
Hiromitsu Nishizaki ◽  
Nuraminah Ramli ◽  
...  
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Support Vector Regression ◽  
Real Time ◽  
Monitoring System ◽  
Machine Learning Algorithms ◽  
Quality Monitoring ◽  
Prediction Algorithm ◽  
Support Vector ◽  
Air Quality Monitoring

This paper presents the development of a real-time cloud-based in-vehicle air quality monitoring system that enables the prediction of the current and future cabin air quality. The designed system provides predictive analytics using machine learning algorithms that can measure the drivers’ drowsiness and fatigue based on the air quality presented in the cabin car. It consists of five sensors that measure the level of CO2, particulate matter, vehicle speed, temperature, and humidity. Data from these sensors were collected in real-time from the vehicle cabin and stored in the cloud database. A predictive model using multilayer perceptron, support vector regression, and linear regression was developed to analyze the data and predict the future condition of in-vehicle air quality. The performance of these models was evaluated using the Root Mean Square Error, Mean Squared Error, Mean Absolute Error, and coefficient of determination (R2). The results showed that the support vector regression achieved excellent performance with the highest linearity between the predicted and actual data with an R2 of 0.9981.

scholarly journals A Proposal for Architectural Framework Using Internet of Things with Fog Computing for an Air Quality Monitoring System

2021 ◽  
Vol 2 (2) ◽  
pp. 1-14
Author(s):  
Aarti Rani ◽  
Keyword(s):  
Air Quality ◽  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Fog Computing ◽  
Pollution Monitoring ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Air Pollution Monitoring ◽  
Architectural Framework

Air Monitoring becomes a systematic approach for sensitivity and finding out the circumstances of the atmosphere. The major concern of air quality monitoring is to measure the concentration of pollution and other important parameter related to the contamination and provides information in real-time to make decisions at right time to cure lives and save the environment. This paper proposes an Architectural Framework for the air quality monitoring system based on Internet-of-Things (IoT) and via Fog computing techniques with novel methods to obtain real-time and accurate measurements of conventional air quality monitoring. IoT-based real-time air pollution monitoring system is projected to at any location and stores the measured value of various pollutants over a web server with the Internet. It can facilitate the process and filter data near the end of the IoT nodes in a concurrent manner and improving the Latency issue with the quality of services.

scholarly journals Technical Solution for a Real-Time Air Quality Monitoring System

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Attila Simo ◽  
Simona Dzitac ◽  
Flaviu Mihai Frigura-Iliasa ◽  
Sorin Musuroi ◽  
Petru Andea ◽  
...  
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Monitoring System ◽  
Quality Monitoring ◽  
Real Field ◽  
Technical Solution ◽  
Air Quality Monitoring ◽  
Single Chip ◽  
Communication Module ◽  
Technical Solutions

This article will present a simple technical solution for a low-power and real-time air quality monitoring system. The whole package of software and hardware technical solutions applied for recording, transmitting and analyzing data is briefly described. This original monitoring system integrates a single chip microcon-troller, several dedicated air pollution surveillance sensors (for PM10, PM2.5, SO2, NO2, CO, O3, VOC, CO2), a LoRaWAN communication module and an online platform. This system was tested and applied under real field conditions. Depending on the measured values, it provides alerts, or, it can lead to the re-placement of specific components in the exhaust equipment. This article will pre-sent some experimental results, validated also by official measurements of government operated air quality stations.

scholarly journals A Proposal of Implementation of Sitting Posture Monitoring System for Wheelchair Utilizing Machine Learning Methods

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6349
Author(s):  
Jawad Ahmad ◽  
Johan Sidén ◽  
Henrik Andersson
Keyword(s):  
Machine Learning ◽  
Pressure Distribution ◽  
Real Time ◽  
Monitoring System ◽  
Pressure Ulcers ◽  
Machine Learning Algorithms ◽  
Raspberry Pi ◽  
Support Vector ◽  
Processing Unit ◽  
Posture Recognition

This paper presents a posture recognition system aimed at detecting sitting postures of a wheelchair user. The main goals of the proposed system are to identify and inform irregular and improper posture to prevent sitting-related health issues such as pressure ulcers, with the potential that it could also be used for individuals without mobility issues. In the proposed monitoring system, an array of 16 screen printed pressure sensor units was employed to obtain pressure data, which are sampled and processed in real-time using read-out electronics. The posture recognition was performed for four sitting positions: right-, left-, forward- and backward leaning based on k-nearest neighbors (k-NN), support vector machines (SVM), random forest (RF), decision tree (DT) and LightGBM machine learning algorithms. As a result, a posture classification accuracy of up to 99.03 percent can be achieved. Experimental studies illustrate that the system can provide real-time pressure distribution value in the form of a pressure map on a standard PC and also on a raspberry pi system equipped with a touchscreen monitor. The stored pressure distribution data can later be shared with healthcare professionals so that abnormalities in sitting patterns can be identified by employing a post-processing unit. The proposed system could be used for risk assessments related to pressure ulcers. It may be served as a benchmark by recording and identifying individuals’ sitting patterns and the possibility of being realized as a lightweight portable health monitoring device.

Real-Time Outdoor Air Quality Monitoring System

2021 ◽  
Author(s):  
S M Abiduzzaman ◽  
Hasmah Mansor ◽  
Teddy Surya Gunawan ◽  
Robiah Ahmad
Keyword(s):  
Air Quality ◽  
Real Time ◽  
Monitoring System ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Outdoor Air ◽  
Outdoor Air Quality
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