Implementation of a Low-Cost Energy and Environment Monitoring System Based on a Hybrid Wireless Sensor Network

Kim, Joo Young; Chung, Beom Jin; Son, Sung-Yong

doi:10.1155/2017/5957082

Cited by 17 publications

(14 citation statements)

References 14 publications

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“…A total of 80 (3.26 %) of the data points were outside of the limit of agreement (51 above the upper limit and 29 below the lower limit). This range is significantly lower than 300 ppb (the World Health Organization, WHO, threshold for tVOC; Koistinen et al, 2008). The plot shows that Foobot FBT0002100 underestimated the concentrations at high concentrations (> 300 ppb).…”

Section: Total Volatile Organic Compounds (Tvoc)mentioning

confidence: 88%

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Field evaluation of a low-cost indoor air quality monitor to quantify exposure to pollutants in residential environments

Moreno-Rangel

Sharpe

Musau

et al. 2018

J. Sens. Sens. Syst.

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Abstract. Measurements of temporal and spatial changes to indoor contaminant concentrations are vital to understanding pollution characteristics. Whilst scientific instruments provide high temporal resolution of indoor pollutants, their cost and complexity make them unfeasible for large-scale projects. Low-cost monitors offer an opportunity to collect high-density temporal and spatial data in a broader range of households. This paper presents a user study to assess the precision, accuracy, and usability of a low-cost indoor air quality monitor in a residential environment to collect data about the indoor pollution. Temperature, relative humidity, total volatile organic compounds (tVOC), carbon dioxide (CO2) equivalents, and fine particulate matter (PM2.5) data were measured with five low-cost (“Foobot”) monitors and were compared with data from other monitors reported to be scientifically validated. The study found a significant agreement between the instruments with regard to temperature, relative humidity, total volatile organic compounds, and fine particulate matter data. Foobot CO2 equivalent was found to provide misleading CO2 levels as indicators of ventilation. Calibration equations were derived for tVOC, CO2, and PM2.5 to improve sensors' accuracy. The data were analysed based on the percentage of time pollutant levels that exceeded WHO thresholds. The performance of low-cost monitors to measure total volatile organic compounds and particulate matter 2.5 µm has not been properly addressed. The findings suggest that Foobot is sufficiently accurate for identifying high pollutant exposures with potential health risks and for providing data at high granularity and good potential for user or scientific applications due to remote data retrieval. It may also be well suited to remote and larger-scale studies in quantifying exposure to pollutants.

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Section: Total Volatile Organic Compounds (Tvoc)mentioning

confidence: 88%

“…The AMS iAQ-CORE-C does not report absolute values for any particular gas, but instead indicates the relative change in levels of reducing gases such as CO and a wide range of VOCs (Brown, 2017). This sensor has been used to control environmental monitoring systems (Kim et al, 2017) and smart health applications (Chan et al, 2017).…”

mentioning

confidence: 99%

Field evaluation of a low-cost indoor air quality monitor to quantify exposure to pollutants in residential environments

Moreno-Rangel

Sharpe

Musau

et al. 2018

J. Sens. Sens. Syst.

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“…Thus, a high level of performance is achieved within a communication system in which the frequency band is limited. There are a number of papers in the literature [20][21][22][23][24][25][26][27] dealing with LoRa, but none investigates the issue of scalability.…”

Section: Large-scale Lora Sensors For Long-range Transmissionsmentioning

confidence: 99%

LoRa (Long-Range) High-Density Sensors for Internet of Things

Lavric

2019

Journal of Sensors

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Over the past few years, there has been a growing awareness regarding the concept of Internet of Things (IoT), which involves connecting to the Internet various objects surrounding us in everyday life. The main purpose of this concept closely connected to the smart city issue is increasing the quality of life by contributing to streamlining resource consumption and protecting the environment. The LoRa communication mechanism is a physical layer of the LoRaWAN protocol, defined by the LoRa Alliance. Compared to other existing technologies, LoRa is a modulation technique enabling the transfer of information over a range of tens of kilometers. The main contribution this paper brings to the field is analyzing the scalability of the LoRa technology and determining the maximum number of sensors which can be integrated into this type of monitoring and control architecture. The sensor architecture is specific to the smart city concept that involves the integration of a large number of high-density sensors distributed on a large-scale geographic area. The reason behind this study is the need to assess the scalability of the LoRa technology, taking into consideration other factors, such as the packet payload size, the duty circle parameter, the spreading factor, and the number of nodes. The experimental results reveal that the maximum number of LoRa sensors that can communicate on the same channel is 1,500; furthermore, in order to obtain a high performance level, it is necessary to schedule and plan the network as carefully as possible. The spreading factor must be allocated according to the distance at which the sensor is placed from the gateway.

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“…While MQTT utilizes TCP, CoAP works on top of UDP. CoAP has been utilized in some implementations of smart environmental monitoring systems [5]. It is a simplified version of HTTP and thus it is possible to bridge both protocols.…”

Section: Introductionmentioning

confidence: 99%

Practical Design of a WSN to Monitor the Crop and its Irrigation System

García¹,

Parra²,

Jiménez³

et al. 2019

NPA

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Due to environmental problems, such as the lack of water for irrigation, each day it becomes more necessary to control crops. Therefore, the use of precision agriculture becomes more evident. When it comes to making decisions on crops, it is evident the need to apply the concept of Smart Agriculture, that focuses on utilizing different sensors and actuators. As the number of IoT devices used in agriculture grows exponentially, it is necessary to design the implemented network so that the data is transmitted without problems. The present work shows a wireless network design, in which we use the information collected by the sensors of a Wireless Sensor Network (WSN), and a Wireless Mesh Network (WMN) formed by Access Points (AP) to transmit the data to a network that monitors agriculture for smart irrigation. In addition, through simulations we have presented a proposal of the maximum number of nodes that must be connected to an AP so that the network is efficient.

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Implementation of a Low-Cost Energy and Environment Monitoring System Based on a Hybrid Wireless Sensor Network

Cited by 17 publications

References 14 publications

Field evaluation of a low-cost indoor air quality monitor to quantify exposure to pollutants in residential environments

Field evaluation of a low-cost indoor air quality monitor to quantify exposure to pollutants in residential environments

LoRa (Long-Range) High-Density Sensors for Internet of Things

Practical Design of a WSN to Monitor the Crop and its Irrigation System

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