Distributed System as Internet of Things for a New Low-Cost, Air Pollution Wireless Monitoring on Real Time

2015 ◽  
Author(s):  
Walter Fuertes ◽  
Diego Carrera ◽  
Cesar Villacis ◽  
Theofilos Toulkeridis ◽  
Fernando Galarraga ◽  
...  
Keyword(s):  
Air Pollution ◽  
Internet Of Things ◽  
Real Time ◽  
Distributed System ◽  
Low Cost ◽  
Wireless Monitoring

scholarly journals Development of real time internet of things (IoT) based air quality monitoring system

2019 ◽  
Vol 13 (3) ◽  
pp. 1039 ◽  
Author(s):  
Huzein Fahmi Hawari ◽  
Aideed Ahmad Zainal ◽  
Mohammad Radzi Ahmad
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Internet Of Things ◽  
Real Time ◽  
Low Cost ◽  
Pollution Index ◽  
Real Time System ◽  
Effective Implementation ◽  
Modern Cities ◽  
Monitoring Result

The atmospheric air pollution is a major concern in modern cities, especially in developing countries like Malaysia. In this paper, we have reported an effective implementation for Internet of Things used for monitoring the level of air pollution based on Malaysia Air Pollution Index (API). The low-cost and real time system would be able to monitor regular air quality pollutants including Particulate Matter (PM) of PM2.5, PM10 and Carbon Monoxide (CO) gas as well as the temperatures and humidity of the surroundings. The system has capability to detect Good, Moderate, Unhealthy, Very Unhealthy and Hazardous API status. Based on 5 weeks of experimental API monitoring result on specified test location, the system was able to demonstrate promising results in providing a reliable real time monitoring of the air quality condition.

scholarly journals Design of an IoT based Real Time Environment Monitoring System using Legacy Sensors

2018 ◽  
Vol 210 ◽  
pp. 03008
Author(s):  
Aparajita Das ◽  
Manash Pratim Sarma ◽  
Kandarpa Kumar Sarma ◽  
Nikos Mastorakis
Keyword(s):  
Air Pollution ◽  
Light Intensity ◽  
Real Time ◽  
Environmental Conditions ◽  
Low Cost ◽  
Environment Monitoring ◽  
Time Data ◽  
Graphical Information ◽  
Real Time Data ◽  
Sun Light

This paper describes the design of an operative prototype based on Internet of Things (IoT) concepts for real time monitoring of various environmental conditions using certain commonly available and low cost sensors. The various environmental conditions such as temperature, humidity, air pollution, sun light intensity and rain are continuously monitored, processed and controlled by an Arduino Uno microcontroller board with the help of several sensors. Captured data are broadcasted through internet with an ESP8266 Wi-Fi module. The projected system delivers sensors data to an API called ThingSpeak over an HTTP protocol and allows storing of data. The proposed system works well and it shows reliability. The prototype has been used to monitor and analyse real time data using graphical information of the environment.

scholarly journals REAL-TIME ENVIRONMENTAL SENSORS TO IMPROVE HEALTH IN THE SENSING CITY

2016 ◽  
Vol XLI-B2 ◽  
pp. 729-733 ◽  
Author(s):  
L. Marek ◽  
M. Campbell ◽  
M. Epton ◽  
M. Storer ◽  
S. Kingham
Keyword(s):  
Quality Of Life ◽  
Air Pollution ◽  
Air Quality ◽  
Real Time ◽  
Low Cost ◽  
Monitoring Network ◽  
Environmental Data ◽  
Chronic Obstructive ◽  
Actual Usage

The opportunity of an emerging smart city in post-disaster Christchurch has been explored as a way to improve the quality of life of people suffering Chronic Obstructive Pulmonary Disease (COPD), which is a progressive disease that affects respiratory function. It affects 1 in 15 New Zealanders and is the 4th largest cause of death, with significant costs to the health system. While, cigarette smoking is the leading cause of COPD, long-term exposure to other lung irritants, such as air pollution, chemical fumes, or dust can also cause and exacerbate it. Currently, we do know little what happens to the patients with COPD after they leave a doctor’s care. By learning more about patients’ movements in space and time, we can better understand the impacts of both the environment and personal mobility on the disease. This research is studying patients with COPD by using GPS-enabled smartphones, combined with the data about their spatiotemporal movements and information about their actual usage of medication in near real-time. We measure environmental data in the city, including air pollution, humidity and temperature and how this may subsequently be associated with COPD symptoms. In addition to the existing air quality monitoring network, to improve the spatial scale of our analysis, we deployed a series of low-cost Internet of Things (IoT) air quality sensors as well. The study demonstrates how health devices, smartphones and IoT sensors are becoming a part of a new health data ecosystem and how their usage could provide information about high-risk health hotspots, which, in the longer term, could lead to improvement in the quality of life for patients with COPD.

The Design of Elevator Monitoring Terminal Based on the GPRS

2013 ◽  
Vol 313-314 ◽  
pp. 1180-1183
Author(s):  
Qi Zhi Fang ◽  
Yong Zhe Ge ◽  
Hong Yu Xu
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
High Reliability ◽  
Low Cost ◽  
Monitoring Network ◽  
Wireless Monitoring ◽  
Management Platform ◽  
Management Quality ◽  
Ip Transport ◽  
Development Prospects

The elevator monitoring system of elevator is an integrated elevator management platform that can realize fault for alarm, rescuing trapped persons, daily management, quality evaluation and preventing hidden trouble by using C8051f060 MCU as the control core to sensor and collect the elevator operation data, with built-in TCP/IP transport protocol and with HuaWei GTM900C GPRS module to realize all kinds of data monitoring of the elevator, and the transmitting of the data to processing server through the network . This paper mainly introduces the formation of wireless monitoring network system and communication protocol construction, and especially analyzes the function and the system architecture of the wireless communication terminal in real-time monitoring. GPRS can not only satisfy the requirement of real-time elevator monitoring system, with low cost and high reliability but can also effectively avoid a variety of problems that are caused by transmitting the alarm data through cables . This system provides many valuable experiences for the development of unattended system, and it has a broad development prospects.

scholarly journals IOTFlood: hardware and software platform using internet of things to monitor floods in real time

2021 ◽  
Vol 16 (4) ◽  
pp. 1
Author(s):  
Francisco Vital Da Silva Júnior ◽  
Mônica Ximenes Carneiro Da Cunha ◽  
Marcílio Ferreira De Souza Júnior
Keyword(s):  
Internet Of Things ◽  
Real Time ◽  
Monitoring System ◽  
Research Design ◽  
Open Source Software ◽  
Low Cost ◽  
Sensor Data ◽  
Software Platform ◽  
Web Interface ◽  
Iot Platform

Floods are responsible for a high number of human and material losses every year. Monitoring of river levels is usually performed with radar and pre-configured sensors. However, a major flood can occur quickly. This justifies the implementation of a real-time monitoring system. This work presents a hardware and software platform that uses Internet of Things (IoTFlood) to generate flood alerts to agencies responsible for monitoring by sending automatic messages about the situation of rivers. Research design involved laboratory and field scenarios, simulating floods using mockups, and later tested on the Mundaú River, state of Alagoas, Brazil, where flooding episodes have already occurred. As a result, a low-cost, modular and scalable IoT platform was achieved, where sensor data can be accessed through a web interface or smartphone, without the need for existing infrastructure at the site where the IOTFlood solution was installed using affordable hardware, open source software and free online services for the viewing of collected data.

scholarly journals Impacts of Modifiable Factors on Ambient Air Pollution: A Case Study of COVID-19 Shutdowns

2020 ◽  
Author(s):  
Rebecca Tanzer-Gruener ◽  
Jiayu Li ◽  
s. rose eilenberg ◽  
Allen Robinson ◽  
Albert Presto
Keyword(s):  
Air Pollution ◽  
Real Time ◽  
Low Cost ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Activity Levels ◽  
Industrial Emissions ◽  
Modifiable Factors ◽  
Business As Usual ◽  
The Impact

Modifiable sources of air pollution such as traffic, cooking, and electricity generation emissions can be modulated either by changing activity levels or source intensity. Although air pollution regulations typically target reducing emission factors rather than altering activity, the COVID-19 related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real-time. We use data from a network of twenty-seven low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout urban and suburban Pittsburgh along with data from EPA regulatory monitors. The RAMP locations were divided into four site groups based on land use (High Traffic, Urban Residential, Suburban Residential, and Industrial). Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from “business as usual” periods in March 2019 and 2020. Overall, PM2.5 concentrations decreased across the domain by 3 μg/m3. Intra-day variabilities of the pollutants were computed to attribute pollutant enhancements to specific emission sources (i.e. traffic and industrial emissions). There was no significant change in the industrial related intra-day variability of PM2.5 at the Industrial sites following the COVID-related closures. The morning rush hour induced CO and NO2 concentrations at the High Traffic sites were reduced by 57% and 43%, respectively, which is consistent with the observed reduction in commuter traffic (~50%). The morning rush hour PM2.5 enhancement from traffic emissions fell from ~1.5 μg/m3 to ~0 μg/m3 across all site groups. This translates to a reduction of 0.125 μg/m3 in the daily average PM2.5 concentration. If PM2.5 National Ambient Air Quality Standards (NAAQS) are tightened these calculations shed light on to what extent reductions in traffic related emissions are able to aid in meeting more stringent regulations.

scholarly journals Impacts of Modifiable Factors on Ambient Air Pollution: A Case Study of COVID-19 Shutdowns

2020 ◽  
Author(s):  
Rebecca Tanzer-Gruener ◽  
Jiayu Li ◽  
s. rose eilenberg ◽  
Allen Robinson ◽  
Albert Presto
Keyword(s):  
Air Pollution ◽  
Real Time ◽  
Low Cost ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Activity Levels ◽  
Industrial Emissions ◽  
Modifiable Factors ◽  
Business As Usual ◽  
The Impact

Modifiable sources of air pollution such as traffic, cooking, and electricity generation emissions can be modulated either by changing activity levels or source intensity. Although air pollution regulations typically target reducing emission factors rather than altering activity, the COVID-19 related closures offered a novel opportunity to observe and quantify the impact of activity levels of modifiable factors on ambient air pollution in real-time. We use data from a network of twenty-seven low-cost Real-time Affordable Multi-Pollutant (RAMP) sensor packages deployed throughout urban and suburban Pittsburgh along with data from EPA regulatory monitors. The RAMP locations were divided into four site groups based on land use (High Traffic, Urban Residential, Suburban Residential, and Industrial). Concentrations of PM2.5, CO, and NO2 following the COVID-related closures at each site group were compared to measurements from “business as usual” periods in March 2019 and 2020. Overall, PM2.5 concentrations decreased across the domain by 3 μg/m3. Intra-day variabilities of the pollutants were computed to attribute pollutant enhancements to specific emission sources (i.e. traffic and industrial emissions). There was no significant change in the industrial related intra-day variability of PM2.5 at the Industrial sites following the COVID-related closures. The morning rush hour induced CO and NO2 concentrations at the High Traffic sites were reduced by 57% and 43%, respectively, which is consistent with the observed reduction in commuter traffic (~50%). The morning rush hour PM2.5 enhancement from traffic emissions fell from ~1.5 μg/m3 to ~0 μg/m3 across all site groups. This translates to a reduction of 0.125 μg/m3 in the daily average PM2.5 concentration. If PM2.5 National Ambient Air Quality Standards (NAAQS) are tightened these calculations shed light on to what extent reductions in traffic related emissions are able to aid in meeting more stringent regulations.

scholarly journals The Use of the Internet of Things for Estimating Personal Pollution Exposure

2019 ◽  
Vol 16 (17) ◽  
pp. 3130 ◽  
Author(s):  
Keith April G. Arano ◽  
Shengjing Sun ◽  
Joaquin Ordieres-Mere ◽  
and Bing Gong
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Internet Of Things ◽  
Policy Development ◽  
Prediction Models ◽  
Low Cost ◽  
Activity Patterns ◽  
Dynamic Feedback ◽  
Pollution Exposure

This paper proposes a framework for an Air Quality Decision Support System (AQDSS), and as a proof of concept, develops an Internet of Things (IoT) application based on this framework. This application was assessed by means of a case study in the City of Madrid. We employed different sensors and combined outdoor and indoor data with spatiotemporal activity patterns to estimate the Personal Air Pollution Exposure (PAPE) of an individual. This pilot case study presents evidence that PAPE can be estimated by employing indoor air quality monitors and e-beacon technology that have not previously been used in similar studies and have the advantages of being low-cost and unobtrusive to the individual. In future work, our IoT application can be extended to include prediction models, enabling dynamic feedback about PAPE risks. Furthermore, PAPE data from this type of application could be useful for air quality policy development as well as in epidemiological studies that explore the effects of air pollution on certain diseases.

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