scholarly journals Smart Pollution Monitoring, Alert and Control System using IoT

2019 ◽  
Vol 9 (2) ◽  
pp. 1929-1935
Keyword(s):  
Air Pollution ◽  
Traffic Control ◽  
Urban Areas ◽  
Threshold Value ◽  
Threshold Level ◽  
Pollution Monitoring ◽  
Pollution Level ◽  
Health Related ◽  
Arduino Uno ◽  
And Control

One of the most important issues relating to the environment is Air Pollution. This is because it does not solely harm the environment in various ways such as ozone layer depletion, global warming but additionally affects the living beings adversely inflicting various health-related problems. The major contributors to Air Pollution apart from industries are vehicles. So, to observe and scale back air pollutants emitted from vehicles this paper proposes a design to develop a smart pollution monitoring system using IoT for detecting the over polluting vehicles. A semi-conductor sensor known as mq2 sensor is integrated with Arduino Uno and it is placed at the emission outlet of vehicle from where the smoke is emitted. The mq2 senor senses the different pollutants emitted from the vehicle and takes the reading of it. It is then compared with the pre-specified threshold value which is already programmed in Arduino Uno. Once the pollution level shoots on the far side beyond the set threshold level, various sorts of warnings such as textual warnings such as messages and, visual warning using LED are fabricated to point that the limit has been breached. Apart from it, if the owner of the vehicle is not taking necessary precaution then a message will be delivered to the traffic control office using GSM along with the GPS location including latitude and longitude values of the vehicle and will impose a fine on the owner of the vehicle as per traffic norms and may also cease the vehicle. This paper, when implemented in real time will be beneficial for the society as it is very economical and yields good result for measuring the air pollution mostly in urban areas.

An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache
Keyword(s):  
Air Pollution ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Urban Air Pollution ◽  
Warning System ◽  
Air Pollutant ◽  
Pollution Level ◽  
Urban Air ◽  
Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

Smart Environmental Monitoring System

2019 ◽  
Vol 10 (1) ◽  
pp. 43-54
Author(s):  
Karthik Sudhakaran Menon ◽  
Brinzel Rodrigues ◽  
Akash Prakash Barot ◽  
Prasad Avinash Gharat
Keyword(s):  
Air Pollution ◽  
Real Time ◽  
Urban Areas ◽  
Real Life ◽  
Cloud Service ◽  
Threshold Value ◽  
Time Data ◽  
Multiple Sensors ◽  
Alert Message ◽  
Environmental Monitoring System

In today's world, air pollution has become a common phenomenon everywhere, especially in the urban areas, air pollution is a real-life problem. In urban areas, the increased number of hydrocarbons and diesel vehicles and the presence of industrial areas at the outskirts of the major cities are the main causes of air pollution. The problem is seriously intense within the metropolitan cities. The governments around the world are taking measure in their capability. The main aim of this project is to develop a system which may monitor and measure pollutants in the air in real time, tell the quality of air and log real-time data onto a remote server (Cloud Service). If the value of the parameters exceeds the given threshold value, then an alert message is sent with the GPS coordinates to the registered number of the authority or person so necessary actions can be taken. The Arduino board connects with Thingspeak cloud service platform using ESP8266 Wi-Fi module. The device uses multiple sensors for monitoring the parameters of the air pollution like MQ-135, MQ-7, DHT-22, sound sensor, LCD.

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 Research on an Iot Based Air Pollution Monitoring System

2019 ◽  
Vol 8 (9S2) ◽  
pp. 553-558
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Life Forms ◽  
Pollution Monitoring ◽  
Wireless Sensor ◽  
Pollution Level ◽  
Air Pollution Monitoring ◽  
Pollution Levels ◽  
Different Sources

Humankind, moving to a period centered upon improvement has overlooked the significance of supportability and has been the real guilty party behind the rising Pollution levels in the world's air among all other living life forms. The Pollution levels at certain spots have come to such high degrees that they have begun hurting our very own It will being. An IoT based Air Pollution observing framework incorporates a MQ Series sensor interfaced to a Node MCU outfitted with an ESP8266 WLAN connector to send the sensor perusing to a Thing Speak cloud. Further extent of this work incorporates an appropriate AI model to foresee the air Pollution level and an anticipating model, which is fundamentally a subset of prescient displaying. As age of poisonous gases from ventures, vehicles and different sources is immensely expanding step by step, it winds up hard to control the dangerous gases from dirtying the unadulterated air. In this paper a practical air Pollution observing framework is proposed. This framework can be utilized for observing Pollutions in demeanor of specific territory and to discover the air peculiarity or property examination. The obligated framework will concentrate on the checking of air poisons concentrate with the assistance of mix of Internet of things with wireless sensor systems. The investigation of air quality should be possible by figuring air quality index (AQI)

scholarly journals Using UAV-Based Systems to Monitor Air Pollution in Areas with Poor Accessibility

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Oscar Alvear ◽  
Nicola Roberto Zema ◽  
Enrico Natalizio ◽  
Carlos T. Calafate
Keyword(s):  
Air Pollution ◽  
Urban Areas ◽  
Pollution Monitoring ◽  
Mobility Models ◽  
Optimization Strategy ◽  
Swarm Optimization ◽  
Air Pollution Monitoring ◽  
Acceptable Alternative ◽  
Rural Environments ◽  
Time Bounds

Air pollution monitoring has recently become an issue of utmost importance in our society. Despite the fact that crowdsensing approaches could be an adequate solution for urban areas, they cannot be implemented in rural environments. Instead, deploying a fleet of UAVs could be considered an acceptable alternative. Embracing this approach, this paper proposes the use of UAVs equipped with off-the-shelf sensors to perform air pollution monitoring tasks. These UAVs are guided by our proposed Pollution-driven UAV Control (PdUC) algorithm, which is based on a chemotaxis metaheuristic and a local particle swarm optimization strategy. Together, they allow automatically performing the monitoring of a specified area using UAVs. Experimental results show that, when using PdUC, an implicit priority guides the construction of pollution maps by focusing on areas where the pollutants’ concentration is higher. This way, accurate maps can be constructed in a faster manner when compared to other strategies. The PdUC scheme is compared against various standard mobility models through simulation, showing that it achieves better performance. In particular, it is able to find the most polluted areas with more accuracy and provides a higher coverage within the time bounds defined by the UAV flight time.

scholarly journals Hardware Efficient Solutions for Wireless Air Pollution Sensors Dedicated to Dense Urban Areas

2020 ◽  
Vol 12 (5) ◽  
pp. 776
Author(s):  
Marzena Banach ◽  
Rafał Długosz ◽  
Jolanta Pauk ◽  
Tomasz Talaśka
Keyword(s):  
Air Pollution ◽  
Urban Areas ◽  
Smart Cities ◽  
Real Data ◽  
High Amplitude ◽  
Base Station ◽  
Pollution Monitoring ◽  
Process Data ◽  
Signal Processing Algorithm ◽  
Air Pollution Monitoring

This paper proposes novel solutions for the application of air pollution monitoring systems in so called ‘smart cities’. A possibility of the implementation of a relatively dense network of wireless air pollution sensors that can collect and process data in real time was the motive behind our research and investigations. We discuss the concept of the wireless sensor network, taking into account the structure of the urban development in cities and we present a novel signal processing algorithm that may be used to control the communication scheme between particular sensors and an external network. We placed a special emphasis on the computational complexity to facilitate the implementation directly at the transistor level of particular sensors. The algorithm was verified using real data obtained from air pollution sensors installed in Krakow, Poland. To ensure sufficient robustness of the variability of input data, we artificially added high amplitude noise to the real data we obtained. This paper demonstrates the performance of the algorithm. This algorithm allows for the reduction of the noise amplitude by 23 dB and enables a reduction of the number of wireless communication sessions with a base station (BS) by 70%–80%. We also present selected measurement results of a prototype current-mode digital-to-analogue converter to be used in the sensors, for signal resolutions up to 7 bits.

scholarly journals PRIORITY BASED TRAFFIC LIGHTS CONTROLLER USING WIRELESS SENSOR NETWORKS

2013 ◽  
pp. 178-181
Author(s):  
K. R. SHRUTHI ◽  
K. VINODHA
Keyword(s):  
Traffic Control ◽  
Urban Areas ◽  
Traffic Management ◽  
International Standards ◽  
Wireless Sensor ◽  
Traffic Light ◽  
Traffic Lights ◽  
Adaptive Traffic Control ◽  
And Control ◽  
Multiple Intersections

Vehicular traffic is continuously increasing around the world, especially in large urban areas. The resulting congestion has become a major concern to transportation specialists and decision makers. The existing methods for traffic management, surveillance and control are not adequately efficient in terms of performance, cost, maintenance, and support. In this paper, the design of a system that utilizes and efficiently manages traffic light controllers is presented. In particular, we present an adaptive traffic control system based on a new traffic infrastructure using Wireless Sensor Network (WSN). These techniques are dynamically adaptive to traffic conditions on both single and multiple intersections. An intelligent traffic light controller system with a new method of vehicle detection and dynamic traffic signal time manipulation is used in the project. The project is also designed to control traffic over multiple intersections and follows international standards for traffic light operations. A central monitoring station is designed to monitor all access nodes..

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