Traffic exhaust to wildfires: PM2.5 measurements with fixed and portable, low-cost LoRaWAN-connected sensors

© 2020 Forehead et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Air pollution with PM2.5 (particulate matter smaller than 2.5 micro-metres in diameter) is a major health hazard in many cities worldwide, but since measuring instruments have traditionally been expensive, monitoring sites are rare and generally show only background concentrations. With the advent of low-cost, wirelessly connected sensors, air quality measurements are increasingly being made in places where many people spend time and pollution is much worse: on streets near traffic. In the interests of enabling members of the public to measure the air that they breathe, we took an open-source approach to designing a device for measuring PM2.5. Parts are relatively cheap, but of good quality and can be easily found in electronics or hardware stores, or on-line. Software is open source and the free LoRaWAN-based “The Things Network” the platform. A number of low-cost sensors we tested had problems, but those selected performed well when co-located with reference-quality instruments. A network of the devices was deployed in an urban centre, yielding valuable data for an extended time. Concentrations of PM2.5 at street level were often ten times worse than at air quality stations. The devices and network offer the opportunity for measurements in locations that concern the public

Technical Solution for a Real-Time Air Quality Monitoring System

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

IoT-based air quality monitoring systems for smart cities: A systematic mapping study

The increased level of air pollution in big cities has become a major concern for several organizations and authorities because of the risk it represents to human health. In this context, the technology has become a very useful tool in the contamination monitoring and the possible mitigation of its impact. Particularly, there are different proposals using the internet of things (IoT) paradigm that use interconnected sensors in order to measure different pollutants. In this paper, we develop a systematic mapping study defined by a five-step methodology to identify and analyze the research status in terms of IoT-based air pollution monitoring systems for smart cities. The study includes 55 proposals, some of which have been implemented in a real environment. We analyze and compare these proposals in terms of different parameters defined in the mapping and highlight some challenges for air quality monitoring systems implementation into the smart city context

Testing Smart City environmental monitoring technology using small scale temporary cities

Exposure to Particulate Matter (PM) has been identified as a major health problem worldwide. Established measurement techniques require equipment costing many thousands of dollars and specialist expertise to maintain. Ongoing research is investigating the use of low cost <;$300 sensors to enable greater temporal-spatial density of readings to be taken. There are questions about the suitability and reliability of these low-cost sensors, which can be addressed by deploying and evaluating the sensors in real world applications. Rather than deploying standalone data loggers for each sensor, each air quality monitor is connected to an IoT device to enable real time transmission of data. We propose festival sites as small scale cities to enable a short term deployments and evaluation of sensors. This work illustrates that, if coupled with higher resolution of wind data, low-cost sensors may enable to follow the evolution of pollution hotspots and help the identification of pollution sources. This study, building upon the body of work focused on the evaluation and best practice of using low-cost sensors for PM monitoring. We present data from these IoT devices and experiences gained from using a festival site as a substitute for a city

Collision-Free Transmissions in an IoT Monitoring Application Based on LoRaWAN

International audienceWith the Internet of Things (IoT), the number of monitoring applications deployed is considerably increasing, whatever the field considered: smart city, smart agriculture, environment monitoring, air pollution monitoring, to name a few. The LoRaWAN (Long Range Wide Area Network)architecture with its long range communication, its robustness to interference and its reduced energy consumption is an excellent candidate to support such applications. However, if the number of end devices is high, the reliability of LoRaWAN, measured by the Packet Delivery Ratio (PDR), becomes unacceptable due to an excessive number of collisions. In this paper, we propose two different families of solutions ensuring collision-free transmissions. The first family is TDMA (Time-Division Multiple Access)-based. All clusters transmit in sequence and up to six end devices with different spreading factors belonging to the same cluster are allowed to transmit in parallel. The second family is FDMA (Frequency Divsion Multiple Access)-based. All clusters transmit in parallel, each cluster on its own frequency. Within each cluster, all end devices transmit in sequence. Their performance are compared in terms of PDR, energy consumption by end device and maximum number of end devices supported. Simulation results corroborate the theoretical results and show the high efficiency of the solutions proposed

Real-time application programming interfaces for depicting aquatic internet of things

Although recent years portray an increase demand for Internet of Things (IoT) applications in aquatic setting, there is a lack of standardization in collecting and displaying these data to a wider set of audiences ranging from marine biologists, whale-watching companies and environmentalists. More flexible APIs and long-range data access are necessary, providing the facilitated remote ac cess to the data, while reducing significantly the cost of fuel and time when obtaining the data from oceanic settings. The main goal of this thesis is to produce the robust back-end and an API for: (i) managing the IoT devices to be applied in aquatic setting; (ii) obtaining the status and the telemetry in real-time; and (iii) visualizing the collected data from IoT devices such as temperature, pressure, humidity, luminosity, GPS position, etc. The final product advances the state of the art in back-end development for collecting, storing and displaying larger datasets (e.g. collected telemetries, radio transmission data) in Single-page applications (SPAs). It will, moreover, use the latest back-end and front-end development tech niques (e.g. React.JS, Laravel) while optimizing database querying, and providing the real-time access to the data on any device, and without the need of refreshing the page.Embora nos últimos anos tenha existido um aumento no desenvolvimento de projetos na área da Internet das coisas (IoT) em ambientes aquáticos, não existe uma padronização na recolha e exibição dos dados obtidos com esses mesmos projetos de modo a possibilitar o seu aproveita mento por um conjunto diverso de utilizadores, que variam desde os biólogos marinhos, passando pelas empresas de observação de baleias até aos ambientalistas. Para que tal seja possível são necessárias APIs mais flexíveis e acesso a dados de longo alcance, fornecendo acesso remoto facil itado aos dados, reduzindo significativamente o custo de combustível e tempo ao obter os dados de configurações oceânicas. O principal objetivo desta tese é desenvolver um back office robusto e uma API para: (i) gerir os dispositivos de IoT a serem utilizados em ambientes aquáticos; (ii) obter o estado e a telemetria em tempo real; e (iii) visualizar os dados recolhidos pelos dispositivos de IoT como por exemplo, temperatura, pressão, humidade, luminosidade, posição do GPS, etc... O produto final contribui para o avanço da tecnologia, pois providencia um back office para recolher, guardar e exibir um grande conjunto de dados (por exemplo, multimédia recolhida, telemetrias, dados de transmissão de rádio) em aplicações de uma única página (SPAs). Além disso, utilizará as mais recentes técnicas de desenvolvimento de back-end e front-end (por exemplo, React.JS, Laravel), otimizando a consulta à base de dados e fornecendo o acesso em tempo real aos dados em qualquer dispositivo, e sem a necessidade de atualizar a página

IoT Data Processing for Smart City and Semantic Web Applications

The world has been experiencing rapid urbanization over the last few decades, putting a strain on existing city infrastructure such as waste management, water supply management, public transport and electricity consumption. We are also seeing increasing pollution levels in cities threatening the environment, natural resources and health conditions. However, we must realize that the real growth lies in urbanization as it provides many opportunities to individuals for better employment, healthcare and better education. However, it is imperative to limit the ill effects of rapid urbanization through integrated action plans to enable the development of growing cities. This gave rise to the concept of a smart city in which all available information associated with a city will be utilized systematically for better city management. The proposed system architecture is divided in subsystems and is discussed in individual chapters. The first chapter introduces and gives overview to the reader of the complete system architecture. The second chapter discusses the data monitoring system and data lake system based on the oneM2M standards. DMS employs oneM2M as a middleware layer to achieve interoperability, and DLS uses a multi-tenant architecture with multiple logical databases, enabling efficient and reliable data management. The third chapter discusses energy monitoring and electric vehicle charging systems developed to illustrate the applicability of the oneM2M standards. The fourth chapter discusses the Data Exchange System based on the Indian Urban Data Exchange framework. DES uses IUDX standard data schema and open APIs to avoid data silos and enable secure data sharing. The fifth chapter discusses the 5D-IoT framework that provides uniform data quality assessment of sensor data with meaningful data descriptions

LivingFog: Leveraging fog computing and LoRaWAN technologies for smart marina management (experience paper)

International audienceIn recent years, fog computing has emerged as a paradigm that brings computing, storage and networking resources closer to end users and devices at the edge of the network. One of the use cases for fog computing is IoT, where a large amount of data is generated by sensors that need to be pre-processed in place before the results are sent to the cloud for further processing and long-term storage. However, actual fog deployments are at their infancy. In this paper, we present the smart-marina project at La Marina de Valencia in which the LivingFog fog computing platform integrating opensource software and LoRaWAN technologies were used to process data collected from several sensors. We show the benefits of the platform in terms of latency reduction and bandwidth saving. Moreover, the platform has been used by particpants of the "Hack the fog" hackathon to deploy applications to test different innovative ideas on using the sensor data

An Orthogonal Air Pollution Monitoring Method (OAPM) Based on LoRaWAN

International audienceHigh accuracy air pollution monitoring in a smart city requires the deployment of a huge number of sensors in this city. One of the most appropriate wireless technologies expected to support high density deployment is LoRaWAN which belongs to the Low Power Wide Area Network (LPWAN) family and offers long communication range, multi-year battery lifetime and low cost end devices. It has been designed for End Devices (EDs) and applications that need to send small amounts of data a few times per hour. However, a high number of end devices breaks the orthogonality of LoRaWAN transmissions, which was one of the main advantages of LoRaWAN. Hence, network performances are strongly impacted. To solve this problem, we propose a solution called OAPM (Orthogonal Air Pollution Monitoring) which ensures the orthogonality of LoRaWAN transmissions and provides accurate air pollution monitoring. In this paper, we show how to organize EDs into clusters and sub-clusters, assign transmission times to EDs, configurate and synchronize them, taking into account the specificities of LoRaWAN and the features of the air pollution monitoring application. Simulation results corroborate the very good behavior of OAPM