A NDIR-based CO2 monitor system for wireless sensor networks

García-Romeo, D.; Fuentes, Hesner Coto; Medrano, N.; Calvo, B.; Martínez, P.A.; Azcona, C.

doi:10.1109/lascas.2012.6180326

Cited by 12 publications

(6 citation statements)

References 2 publications

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“…The internal and external sensor nodes have approximately the same structure. They are based on a microcontroller that acquires environmental data through a specific ad hoc designed electronic front end for each type of sensor (electrochemical, NDIR [19], particulate digital sensor).…”

Section: Internal Sensor Nodementioning

confidence: 99%

A Distributed IoT Air Quality Measurement System for High-Risk Workplace Safety Enhancement

Parri

Tani

Baldo

et al. 2023

Sensors

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The safety of an operator working in a hazardous environment is a recurring topic in the technical literature of recent years, especially for high-risk environments such as oil and gas plants, refineries, gas depots, or chemical industries. One of the highest risk factors is constituted by the presence of gaseous substances such as toxic compounds such as carbon monoxide and nitric oxides, particulate matter or indoors, in closed spaces, low oxygen concentration atmospheres, and high concentrations of CO2 that can represent a risk for human health. In this context, there exist many monitoring systems for lots of specific applications where gas detection is required. In this paper, the authors present a distributed sensing system based on commercial sensors aimed at monitoring the presence of toxic compounds generated by a melting furnace with the aim of reliably detecting the insurgence of dangerous conditions for workers. The system is composed of two different sensor nodes and a gas analyzer, and it exploits commercial low-cost commercially available sensors.

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Section: Internal Sensor Nodementioning

confidence: 99%

A Distributed IoT Air Quality Measurement System for High-Risk Workplace Safety Enhancement

Parri

Tani

Baldo

et al. 2023

Sensors

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“…The first one is measurement using method of wavelength absorption that is one of the properties of chemical compound. This method is called NDIR (not dispersive infrared) [17]. The second method is based on changes of electrical charge of chemical reaction measuring.…”

Section: Wireless Sensor Network Technologymentioning

confidence: 99%

Large scale integration of wireless sensor network technologies for air quality monitoring at a logistics shipping base

Molka-Danielsen

Engelseth

Wang

2018

Journal of Industrial Information Integration

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The future of logistics shipping bases will be to seek efficient flows of materials to meet the needs of business partners. Supply chain and operations managers of supply bases will need to integrate technologies that allow for greater automation, digitalization, flexibility and improved communications among stakeholders. The technologies that are likely to boost integration will consist of a plethora of Industrial Internet-of-Things (IIoT) technologies that may include Wireless Sensor Network (WSN) technologies and could be applied for improved monitoring of healthy and safe industrial workplaces for workers. However, little is known regarding how WSN technologies can be implemented on a larger scale and its implications when integrated on standard logistics and operations of industrial workplaces such as a shipping base. The WSN sensor units represent an integrating resource that are capable of monitoring air temperature, humidity and levels of carbon dioxide (CO2) and other gasses and of disseminating this information to different actors in the production system. Air quality factors play a critical role in the perceived levels of workers' comfort and in reported medical health. The low cost of wireless sensor network (WSN) technologies offer potential for continuous, autonomous and importantly networked assessment of industrial workplace air quality that may have implications for operations management and quality of production. This paper initially presents a case study that monitors air quality that is collected with WSN technologies from two workshops carried out by a large on-shore logistics base that supports offshore petroleum logistics. The case study demonstrates a monitoring and visualization approach for facilitating BD in decision making for health and safety in the shipping industry. However, with the advancement in IIoT technologies and the emergence of smart sensing and actuating devices, it is possible to form a digital closed-loop system that we argue is essential for managers to link together information about air quality with supply chain and operations management decisions. We propose that central to effective decision making is the data analytics approach and visualization of what is potentially, big data (BD) in monitoring the air quality in industrial workplaces. We discuss how WSN technologies can be integrated into the logistics management and operations of the shipping base. Through an analytical discussion of BD we explore how to extend the potential application of IIoT and Visual Analytics to facilitate a smart workplace for the Industry 4.0 era.

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“…The first one is measurement using method of wavelength absorption, which is one of the properties of chemical compound. This method is called NDIR (not dispersive infrared) [3]. The second method is based on changes of electrical charge of chemical reaction measuring.…”

Section: Consequences Of Co 2 Accumulationmentioning

confidence: 99%

“…It is suitable for detection of NH 3 , NO x , alcohol, Benzene, smoke and CO 2 [5]. The sensitivity characteristic of the MQ-135 sensor can be seen at Fig.…”

Section: Sensor Descriptionmentioning

confidence: 99%