scholarly journals Air Pollution Monitoring for Bogor Smart City Based Internet of Things and Social Media (Twitter)

2019 ◽  
Vol 621 ◽  
pp. 012006
Author(s):  
Mohamad Iqbal Suriansyah ◽  
Prihastuti Harsani
Keyword(s):  
Social Media ◽  
Air Pollution ◽  
Internet Of Things ◽  
Smart City ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring

Internet of Things Mobile–Air Pollution Monitoring System (IoT-Mobair)

2019 ◽  
Vol 6 (3) ◽  
pp. 5577-5584 ◽  
Author(s):  
Swati Dhingra ◽  
Rajasekhara Babu Madda ◽  
Amir H. Gandomi ◽  
Rizwan Patan ◽  
Mahmoud Daneshmand
Keyword(s):  
Air Pollution ◽  
Internet Of Things ◽  
Monitoring System ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring

scholarly journals Application of Internet of Things (IoT) on air pollution monitoring database system

2019 ◽  
Vol 125 ◽  
pp. 25005
Author(s):  
Sudarsono ◽  
Muhammad Andang Novianta ◽  
Cyrilla Indri Parwati
Keyword(s):  
Air Pollution ◽  
Internet Of Things ◽  
Structural Information ◽  
Line Graph ◽  
Pollution Index ◽  
Database System ◽  
Pollution Monitoring ◽  
Monitoring Station ◽  
Pollution Level ◽  
Air Pollution Monitoring

In the present work, a database system of air pollution monitoring is developed using Internet of Things (IoT) technology. The system aims to give structural information and trace of air pollution level at particular monitoring station. The particular monitoring location (node) is connected to IoT/M2M server via GSM network using GPRS feature and display on IoT/M2M application in web form. The database on IoT/M2M contains name, description, and location of the monitoring station, Pollution index and the time when the data are taken. On IoT/M2M, the data are displayed either in a color bar graph or a line graph. The color indicated the index value of the pollution. The data can be accessed via internet on isfuonline.info. The system is tested at laboratory environment to detect CO, SO2, NO2, O3, and PM. The test result shows that the system is worked well. Time required to transfer the monitoring data to the IoT server is about 15 minutes. Meanwhile, response time of the system is 30 minutes.

scholarly journals Air Pollution Monitoring System using IoT

2019 ◽  
Vol 9 (2) ◽  
pp. 1727-1731
Keyword(s):  
Lung Cancer ◽  
Air Pollution ◽  
Mental Illness ◽  
Internet Of Things ◽  
Automobile Industry ◽  
Exponential Growth ◽  
Pollution Monitoring ◽  
Adverse Impact ◽  
Human Beings ◽  
Air Pollution Monitoring

Air pollution has a very adverse impact on human beings and our ecosystem. With the rampant industrialization and exponential growth in automobile industry, the air gets highly contaminated by harmful toxins & gases released from their emissions which results into many hazardous diseases like asthma, bronchitis, mental illness, lung cancer etc. Hence the air pollution should be carefully monitored and efficiently controlled. Using internet of things (IoT) we can simultaneously gather pollutants level in highly explicit areas and transmit the data to centralized controlling and monitoring unit where suitable steps can be taken to warn people so as to reduce the level of pollutants in the air significantly.

scholarly journals SmartBike: an IoT Crowd Sensing Platform for Monitoring City Air Pollution

2017 ◽  
Vol 7 (6) ◽  
pp. 3602 ◽  
Author(s):  
Fulvio Corno ◽  
Teodoro Montanaro ◽  
Carmelo Migliore ◽  
Pino Castrogiovanni
Keyword(s):  
Air Pollution ◽  
Smart City ◽  
Pollution Monitoring ◽  
Air Pollution Monitoring ◽  
Crowd Sensing ◽  
Air Quality Measurements ◽  
Service Information ◽  
Sensing Platform ◽  
Environmental Monitoring System ◽  
The City

<p>In recent years, the Smart City concept is emerging as a way to increase efficiency, reduce costs, and improve the overall quality of citizen life. The rise of Smart City solutions is encouraged by the increasing availability of Internet of Things (IoT) devices and crowd sensing technologies. This paper presents an IoT Crowd Sensing platform that offers a set of services to citizens by exploiting a network of bicycles as IoT probes. Based on a survey conducted to identify the most interesting bike-enabled services, the SmartBike platform provides: real time remote geo-location of users’ bikes, anti-theft service, information about traveled route, and air pollution monitoring. The proposed SmartBike platform is composed of three main components: the SmartBike mobile sensors for data collection installed on the bicycle; the end-user devices implementing the user interface for geo-location and anti-theft; and the SmartBike central servers for storing and processing detected data and providing a web interface for data visualization. The suitability of the platform was evaluated through the implementation of an initial prototype. Results demonstrate that the proposed SmartBike platform is able to provide the stated services, and, in addition, that the accuracy of the acquired air quality measurements is compatible with the one provided by the official environmental monitoring system of the city of Turin. The described platform will be adopted within a project promoted by the city of Turin, that aims at helping people making their mobility behavior more sustainable.</p>

Application of Internet of Things in Air Pollution Monitoring

2014 ◽  
Vol 1073-1076 ◽  
pp. 554-557
Author(s):  
Jing Li
Keyword(s):  
Air Pollution ◽  
Internet Of Things ◽  
Pollution Monitoring ◽  
The Internet ◽  
Environment Monitoring ◽  
Environment Protection ◽  
Air Pollution Monitoring ◽  
Networking Technology ◽  
Internet Of Things Technology ◽  
The Internet Of Things

This article analyses how to combine the internet of things (IOT) with air pollution monitoring. It believes that application of internet of things can resolve air pollution monitoring problems. What the paper analyzes is how the Internet of Things technology effectively applied to the field of environment protection, to improve management of environment monitoring and protection. This paper mainly introduces concepts and architecture system of IOT used in environment monitoring and protection, through analyzing the problems in environment monitoring and protection in China, on the basis of summarizing the experience of IOT used in the field of environment protection in China, further proposes how to promote the development and application of networking technology in monitoring and protection of the environment in China, and focuses on the difficulties, obstacles and solutions which exist in.

scholarly journals Design of Quadrotor UAV and Internet-of-Things Based Air Pollution Monitoring Systems

2020 ◽  
Vol 3 (4) ◽  
pp. 120
Author(s):  
Adnan Rafi Al Tahtawi ◽  
Erick Andika ◽  
Maulana Yusuf ◽  
Wildan Nurfauzan Harjanto
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Internet Of Things ◽  
Measurement Data ◽  
Data Retrieval ◽  
Pollution Monitoring ◽  
Quality Monitoring ◽  
Sensor System ◽  
Air Quality Monitoring ◽  
Air Pollution Monitoring

Air pollution is one of problems causing global warming that is currently taking a place. Several air quality monitoring devices usually located at the city center are only limited to display data at one point. Therefore, a mobile device to monitor air quality is needed so as to enable the monitoring in several points. This paper aims to design an air quality monitoring system based on quadrotor Unmanned Aerial Vehicle (UAV) and Internet-of-Things (IoT) technology. The sensor system is designed to detect CO, CO2, air quality, and temperature variables. This sensor systems was then integrated with quadrotor in order to make the monitoring process can be carried out at various points. Quadrotor was designed using Ardupilot Mega (APM) 2.6 as the flight controler. Measurement data from system sensor was transmitted wirelessly using internet network via Wi-Fi module. Based on the test results, the sensor system was able to detect concentration of several test gas and was linear to the output voltage. Quadrotor orientation parameters at takeoff produced transient responses in less than 1 second. The air pollution sensor parameter data could also be displayed every 10 seconds on the ThingSpeak and ThingView interfaces, and could be mapped based on the data retrieval coordinates.

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