Fig 2 - uploaded by Soledad Represa
Content may be subject to copyright.
LoRaWAN network coverage. The map shows the gateways together with the area of coverage. The circle represents the location of the air quality sensor.
Contexts in source publication
Context 1
... evaluate the scope and capacity of the network to transmit data, a portable node was used. At the same time, a software was developed that allows to visualize in a map the power received in the tests carried out and to estimate the range of the signal (Fig. ...
Context 2
... this pilot experience, a LoRaWAN network was deployed using the infrastructure of the UNLP towers and the fiber optic backbone that connects them. We used 5 devices brand Kerlink model iBTS [28] with omnidirectional antennas, in different points of the study region, as can be seen in Figure 2. These points were selected looking for the best range for a densely built urban area and areas with less obstruction of the signal, such as Berisso and Ensenada. ...
Context 3
... of the study region, as can be seen in Figure 2. These points were selected looking for the best range for a densely built urban area and areas with less obstruction of the signal, such as Berisso and Ensenada. As a result, it was possible to obtain a wide coverage of the urban area of La Plata and a large part of the city of Berisso and Ensenada (Fig. 2). The LoRaWAN network proved to be sufficient in terms of scope and coverage area, observing a better reception of signal in residential areas (gateways located in Gonnet and Berisso), in comparison to urbanized areas (gateway in the center of the city). ...
Similar publications
The IoT-Based Parking Monitoring System using Magnetometer as the Sensor is developed to detect the presence of cars in parking slots and to collect all the data from the sensor to be displayed in a mobile application so that user can easily find the empty parking slot. The system consists of four types of hardware and two types of software. This f...
![Figure 5. Mechanical External Casing Packer [8].](publication/334037304/figure/fig5/AS:774038725079046@1561556621732/Mechanical-External-Casing-Packer-8_Q320.jpg)
Citations
... Since PM is typically a greater concern than gases in the global south (Carvalho, 2016), we encountered more sensor networks measuring PM in these areas (Tagle et. al., 2020;Jang and Jung, 2023;Lopez-Restrepo et. al., 2021;Gramsch et. al., 2020;Gramsch et. al., 2021;Candia et. al., 2018;Connerton et. al., 2023;Dirienzo et. al., 2023;Quintero et. al., 2023) than those 595 measuring gas-phase compounds, although overall coverage is still sparse. A few mobile sensor studies are available for further reading on gas-phase coverage in Central and South America (Guevara et. al., 2010;Alvear-Puertas et. al., 2022). ...
We reviewed 60 sensor networks and 15 related efforts (sensor review papers and data accessibility projects) to better understand the landscape of stationary low-cost gas-phase sensor networks deployed in outdoor environments worldwide. This study is not exhaustive of every gas-phase sensor network on the globe, but rather exists to categorize types of sensor networks by their key characteristics and explore general trends. This also exposes gaps in monitoring efforts to date, especially regarding the availability of gas-phase measurements compared to particulate matter (PM), and geographic coverage gaps (the global south, rural areas). We categorize ground-based networks that measure gas-phase air pollutants into two main subsets based on their deployment type: quasi-permanent (long-term) and campaign (short to medium-term) and explore commonplace practices, strengths, and weaknesses of stationary monitoring networks. We conclude with a summary of cross-network unification and quality control efforts. This work aims to help scientists looking to build a sensor network explore best practices and common pathways, and aid end users in finding low-cost sensor datasets that meet their needs.
... The solution presented in [35], on the other hand, describes the prototype of an IoT system, based on sensors connected via Wi-Fi to an MCU node that forwards the data to the PC. Again, in [36], a system based on LoRaWAN technology is shown, where data are sent to the cloud for further processing. Finally, in [37] a sensor-based system is presented that uses a Raspberry as a server, which then also sends the data to the web for consultation. ...
... However, in the works cited, the various systems are designed and optimized for purposes other than that of this paper. In fact, in the conclusions of [35,36], an emphasis is placed on the fact that the developed system is aimed at the creation of smart cities, aiming at the integration with other monitoring systems. Similar conclusions are reached for [37]. ...
... This imposed us to use low-cost sensors. Among the available ones, we chose the SDS011 sensor, widely disseminated and documented in the literature [35][36][37][39][40][41][42], even with extremely recent articles which have dealt well with the issue of its performance. In particular, in [41], which constitutes a review of low-cost sensors, the SDS011 sensor is judged to be one of the best performing. ...
The problem of the containment of fine dust (especially PM 2.5 and PM 10) emitted into the atmosphere is particularly acute, especially in industrialized countries. However, there are particular areas where it is still not adequately considered. One of these is the construction site sector. The aim of this work is to design a flexible, economical, and easy-to-use system, which allows for the detection of the emissions produced in critical circumstances such as the demolition of a building. To this end, a data logger and five customized nodes were designed through a five-step method. The data logger is able to transmit data to a PC, making them available in real time. The study was conducted on a reconstruction site in L’Aquila, Italy, a city severely affected by the earthquake in 2009, for two working days and a public holiday. Even if not presenting substantial critical issues in relation to the latter, the experimental results show that the emissions of PM 2.5 and PM 10 detected during the demolition activity far exceed, in some moments, the threshold values. In fact, peaks as high as about 123 μg/m3 for PM 2.5 and over 1000 μg/m3 for PM 10 have been detected.
... Many of them feature environmental monitoring applications. Monitoring air pollution in smart city landscapes [1] is a prime example. Another application is the monitoring of tree growth and soil moisture levels in remote rural areas [2]. ...
Multiple LPWANs have been rolled out to support the variety of IoT applications that are crucial to the ongoing digital transformation. These networks vary largely in terms of quality-of-service, throughput and energy-efficiency. To cover all LPWAN use-cases most optimally, multiple networks can be combined into a multiple radio access technology (multi-RAT) solution. In particular environmental monitoring in both smart city and remote landscapes. We present and share such a multi-RAT platform. To derive an accurate profile of the multi-RAT opportunities in various scenarios, in the-field network parameter are monitored. The platform collects per-packet energy-consumption, packet delivery ratio (PDR) and other parameters of LoRaWAN, NB-IoT and Sigfox. Our preliminary measurements demonstrate the validity of using a multi-RAT solution. For example, we illustrate the potential energy savings when adopting multi-RAT in various scenarios.
... Second, the accuracy and reliability of the PM sensors built into the WPM are insufficient, and a standardization and certification scheme for low-cost PM sensors has not been established. The measured values output by the WPM are for reference, and they cannot be used as an alternative method of measurement, which requires strict accuracy as work environment measurements or personal sampling, required by laws and regulations [30]. It is also not appropriate to treat the results measured by the WPM as the results of work environment measurement or personal sampling. ...
We manufactured a wearable particle monitor (WPM), which is a simple and low-cost dust monitor. We aimed to evaluate the usefulness of the device by using it and location information of a Global Navigation Satellite System (GNSS) to measure dust generation in outdoor workplaces. We used nine WPMs and a particle counter KC-52 to measure in parallel the dust concentration diffusing standard particles in a dust exposure apparatus to evaluate the measurability of the WPM, and visualized dust generation in outdoor workplaces to evaluate its usability. We obtained location information using a GNSS in parallel with measuring with the WPM. The measured values of the WPM followed the measured values of the KC-52, with a strong correlation of the values between the KC-52 and each WPM. The discrepancy among devices tended to increase, however, because the measured values of the WPMs increased. For outdoor measurements, we could create a heat map of the relative values of dust generation by combining two data of the WPM and the GNSS. The methods of using the WPM could overview the conditions needed to produce dust emissions in dust-generating workplaces.
... Such a device is expected to be employed within a Smart City context. While several city-scale air quality wireless monitoring infrastructures can be found in literature [8], [9], [10], this paper focuses on the realisation of a different typology of data acquisition architecture. Indeed, in the proposed solution, the sensor nodes are expected to be provided with localisation features [11] and then to be deployed on means of public transport. ...
p>The aim of this paper is to discuss the characterisation of a solar energy harvesting system to be integrated in a wireless sensor node, to be deployed on means of transport to pervasively collect measurements of Particulate Matter (PM) concentration in urban areas. The sensor node is based on the use of low-cost PM sensors and exploits LoRaWAN connectivity to remotely transfer the collected data. The node also integrates GPS localisation features, that allow to associate the measured values with the geographical coordinates of the sampling site. In particular, the system is provided with an innovative, small-scale, solar-based powering solution that allows its energy self-sufficiency and then its functioning without the need for a connection to the power grid. Tests concerning the energy production of the solar cell were performed in order to optimise the functioning of the sensor node: satisfactory results were achieved in terms of number of samplings per hour. Finally, field tests were carried out with the integrated environmental monitoring device proving its effectiveness.</p
... The data was stored in internal memory and manually transferred to a computer. Candia et al. [15] propose a system and framework for using low cost sensor networks for air quality monitoring. The study used Nova SDS011, SDS021, and SHINYEI PPD42 sensors connected to an Arduino Mega, with an ESP8266 wifi module and a LoRaWAN module in the absence of a wifi network. ...
... In [3], the authors focused on WiFi-based systems for indoor air quality monitoring and prediction. Many recent works have exploited wireless sensors to monitor air quality [4], [5], [6], [7]. Typically, WSN-based air quality monitoring systems are comprised of multiple sensor nodes and one or several base stations. ...
... Also, the nodes appear to be powered by mains supply and therefore are not suitable for remote, autonomous operation in current form. LoRaWAN-based systems for air pollution monitoring have also been reported in [30]- [32]. However, these are designed to monitor only one pollutant, the PM. ...
Air pollution poses significant risk to environment and health. Air quality monitoring stations are often confined to a small number of locations due to the high cost of the monitoring equipment. They provide a low fidelity picture of the air quality in the city; local variations are overlooked. However, recent developments in low cost sensor technology and wireless communication systems like Internet of Things (IoT) provide an opportunity to use arrayed sensor networks to measure air pollution, in real time, at a large number of locations. This paper reports the development of a novel low cost sensor node that utilizes cost-effective electrochemical sensors to measure Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) concentrations and an infrared sensor to measure Particulate Matter (PM) levels. The node can be powered by either solar-recharged battery or mains supply. It is capable of long-range, low power communication over public or private LoRaWAN IoT network and short-range high data rate communication over Wi-Fi. The developed sensor nodes were co-located with an accurate reference CO sensor for field calibration. The low cost sensors’ data, with offset and gain calibration, shows good correlation with the data collected from the reference sensor. Multiple linear regression (MLR) based temperature and humidity correction results in Mean Absolute Percentage Error (MAPE) of 48.71% and R2 of 0.607 relative to the reference sensor’s data. Artificial Neural Network (ANN) based calibration shows the potential for significant further improvement with MAPE of 38.89% and R2 of 0.78 for leave one out cross validation.
... Also, the nodes appear to be powered by mains supply and therefore are not suitable for remote, autonomous operation in current form. LoRaWAN-based systems for air pollution monitoring have also been reported in [30]- [32]. However, these are designed to monitor only one pollutant, the PM. ...
Air pollution poses significant risks to environment and health. Air quality monitoring stations are often confined to a small number of locations due to the high cost of the monitoring equipment. They provide a low fidelity picture of the air quality in the city; local variations are overlooked. However, recent developments in low cost sensor technology and wireless communication systems like Internet of Things (IoT) provide an opportunity to use arrayed sensor networks to measure air quality, in real time, at a large number of locations. This paper reports the development of a novel low cost sensor node that utilizes cost-effective electrochemical sensors to measure Carbon Monoxide (CO) and Nitrogen Dioxide (NO2) concentrations and an infrared sensor to measure Particulate Matter (PM) levels. The node can be powered by either solar-recharged battery or mains supply. It is capable of long-range, low power communication over public or private LoRaWAN IoT network and short-range high data rate communication over Wi-Fi. The developed sensor nodes were co-located with an accurate reference CO sensor for field calibration. The low cost sensors’ data shows strong correlation with the data collected from the reference sensor. Offset and gain calibration further improves the quality of the sensor data.
... The MCU has an ATmega32u4 processor and a radio communication Lora HopeRF RFM95/96W, programmable in arduino environment. For the management of communication routines, the LMIC library, originally developed by IBM, was implemented [18]. ...
Wireless communications and the Internet of
Things (IoT) paradigm are keys to transforming traditional
cities into smart cities, as they provide the necessary
infrastructure to improve the services that reach citizens. This
article presents a pilot project for smart cities developed in the
city of La Plata, proposing an intelligent infrastructure for
public lighting based on LoRaWAN technology that can serve
as a basis to deploy other solutions for Smart Cities. An end-toend solution is presented, from the intervention of a street
luminaire with air quality sensors, its transmission through the
network and consolidation in an IoT platform developed for this
purpose. Results of the deployment in a real urban scenario, are
described in this paper.
