This paper presents a portable device for outdoor air quality measurement that provides concentration values for the main pollutants: NO2, NO, CO, O3, PM2.5 and PM10, and other values such as temperature, humidity, location, and date. The device is based on the use of commercial electrochemical gas and optical particle matter sensors with a careful design of the electronics for reducing the electrical noise and increasing the accuracy of the measurements. The result is a low-cost system with IoT technology that connects to the Internet through a GSM module and sends all real-time data to a cloud platform with storage and computational potential. Two identical devices were fabricated and installed on a mobile reference measurement unit and deployed in Badajoz, Spain. The results of a two-month field campaign are presented and published. Data obtained from these measurements were calibrated using linear regression and neural network techniques. Good performance has been achieved for both gaseous pollutants (with a Pearson correlation coefficient of up to 0.97) and PM sensors.

Low-Cost Air Quality Measurement System Based on Electrochemical and PM Sensors with Cloud Connection.

Over the last few decades, the quality of air has been deteriorating at an alarming rate leading to demise of nearly seven million people annually worldwide. In the midst of the above worrisome facts citizens across the globe deserve transparency about the quality of the environment they live in, so that appropriate decisions could be taken before it is too late. Keeping this in mind a prototype for an air quality monitoring system has been developed in this work. The proposed air quality monitoring device comprises of a NodeMCU ESP32, a MQ-135 gas sensor and a DHT-11 temperature and humidity sensor module. As compared to other counterparts available, our proposed system gives an upper hand in terms of small size, efficient power usage and cost. The sensors record the data and send it to the NodeMCU acting as the base station of the overall setup. Having an inbuilt microcontroller and an onchip Wi-Fi transceiver, the NodeMCU not only serves the purpose of monitoring the data but also sending it to a remote server empowering tremendous scope for physical world to be communicated at a very fine and detailed level. The gas sensor records the concentration of toxic gases like NOx, CO2, benzene, smoke and gives an overall air quality parameter. If the concentration of the toxic gases exceeds a standard value an alert message is also displayed on the server. The integrated system could possibly be a big yes for the smart cities to justify steps to control pollution level in the years to follow.

Development of an IoT-based Real-Time Air Quality Monitoring Device

Air pollution is a contributor to approximately one in every nine deaths annually. To counteract health issues resulting from air pollution, air quality monitoring is being carried out extensively in urban environments. Currently, however, city air quality monitoring stations are expensive to maintain, resulting in sparse coverage. In this paper, we introduce the design and development of the MegaSense Cyber-Physical System (CPS) for spatially distributed IoT-based monitoring of urban air quality. MegaSense is able to produce aggregated, privacy-aware maps and history graphs of collected pollution data. It provides a feedback loop in the form of personal outdoor and indoor air pollution exposure information, allowing citizens to take measures to avoid future exposure. We present a battery-powered, portable low-cost air quality sensor design for sampling PM 2.5 and air pollutant gases in different micro-environments. We validate the approach with a use case in Helsinki, deploying MegaSense with citizens carrying low-maintenance portable sensors, and using smart phone exposure apps. We demonstrate daily air pollution exposure profiles and the air pollution hot-spot profile of a district. Our contributions have applications in policy intervention management mechanisms and design of clean air routing and healthier navigation applications to reduce pollution exposure.

/pdf/megasense-cyber-physical-system-for-real-time-urban-air-2dwac1q632.pdf

MegaSense: Cyber-Physical System for Real-time Urban Air Quality Monitoring

We present a device based on low-cost electrochemical and optical sensors, designed to be attached to bicycle handlebars, with the aim of monitoring the air quality in urban environments. The system has three electrochemical sensors for measuring NO2 and O3 and an optical particle-matter (PM) sensor for PM2.5 and PM10 concentrations. The electronic instrumentation was home-developed for this application. To ensure a constant air flow, the input fan of the particle sensor is used as an air supply pump to the rest of the sensors. Eight identical devices were built; two were collocated in parallel with a reference urban-air-quality-monitoring station and calibrated using a neural network (R2 > 0.83). Several bicycle routes were carried out throughout the city of Badajoz (Spain) to allow the device to be tested in real field conditions. An air-quality index was calculated to facilitate the user’s understanding. The results show that this index provides data on the spatiotemporal variability of pollutants between the central and peripheral areas, including changes between weekdays and weekends and between different times of the day, thus providing valuable information for citizens through a dedicated cloud-based data platform.

/pdf/a-novel-bike-mounted-sensing-device-with-cloud-connectivity-1d3qdiun.pdf

A Novel Bike-Mounted Sensing Device with Cloud Connectivity for Dynamic Air-Quality Monitoring by Urban Cyclists

Software engineering provides the competences and skills to design and develop robust, secure and efficient applications that solve real problems Students have to develop their abstract thinking to find solutions taking into account not only technical development, but economic and social impact In previous years, different changes have been introduced in the teaching methods with significant outcomes However, students are still facing difficulties with one of the core contents of the subject, UML For this reason, the present work aims to introduce C4 model as a complement of the existing UML diagrams This proposal uses the two first levels of the C4 model to complement the requirements elicitation process, traditionally based only on use cases, to let students start the design of their systems without going into greater technical details

C4 model in a Software Engineering subject to ease the comprehension of UML and the software

The interest in the quality of air is likely to increase, as the public concern for health and environmental issues is on the rise. So far, most data available comes from a small numbers of government-owned sensors, lacking a wide coverage of the entire reality. Improving the amount of data available thus involves reducing the cost of sensors and make their readings accessible to the public. The NanoSen-AQM project aims to do precisely that. Create and use vast numbers of low-cost nano-sensors, to make their data accessible for the public. To achieve such an ambitious goal, the project will use state-of-the-art techniques from Machine Learning and mobile and web development frameworks. As a result, the NanoSen-AQM platform should provide free access to the public and low-cost of entry for sensor owners willing to share their data.

An Online Platform For Real-Time Air Quality Monitoring

With the raising of environmental concerns regarding pollution, interest in monitoring air quality is increasing. However, air pollution data is mostly originated from a limited number of government-owned sensors, which can only capture a small fraction of reality. Improving air quality coverage in-volves reducing the cost of sensors and making data widely available to the public. To this end, the NanoSen-AQM project proposes the usage of low-cost nano-sensors as the basis for an air quality monitoring platform, capa-ble of collecting, aggregating, processing, storing, and displaying air quality data. Being an end-to-end system, the platform allows sensor owners to manage their sensors, as well as define calibration functions, that can im-prove data reliability. The public can visualize sensor data in a map, define specific clusters (groups of sensors) as favorites and set alerts in the event of bad air quality in certain sensors. The NanoSen-AQM platform provides easy access to air quality data, with the aim of improving public health.

https://onlinejour.journals.publicknowledgeproject.org/index.php/i-joe/article/download/11871/6801

NanoSen-AQM: From Sensors to Users

With the raising concerns for the environment, interest in monitoring air quality is likely to increase in the near future. However, most data comes from a limited number of government-owned sensors, which can only capture a small fraction of reality. Improving data coverage thus involves reducing the cost of sensors and make data widely available. For this, we will use a very high number of low-cost sensors as the basis for an air quality monitoring platform, capable of collecting, aggregating, storing and displaying data. This platform will use stream-based technologies capable of scaling for large numbers of sensors and users. The resulting NanoSen-AQM platform will provide vast amounts of air quality data to the public, with the aim of improving public health.

Pedro Lucas

Papers

An Online Platform For Real-Time Air Quality Monitoring

NanoSen-AQM: From Sensors to Users

A Hybrid Application for Real-Time Air Quality Monitoring