An IoT-Based Smart Solution for Preventing Domestic CO and LPG Gas Accidents

Gomes, João B. A.; Rodrigues, Joel J. P. C.; Al‐Muhtadi, Jalal; Arunkumar, N.; Rabelo, Ricardo A. L.; Furtado, Vasco

doi:10.1109/latincom.2018.8613241

Cited by 8 publications

(8 citation statements)

References 15 publications

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“…In the simulation, the software environment is Python 3.6 with Keras 2.4.3, which has been widely used to deploy machine learning algorithms and experiment environments. The experiments are carried out based on the data collected from the sensors integrated at the air quality monitoring station in Düebendorf in Switzerland 4 .The dataset contains record from April 2017 to December 2019, with the data collected from 18 Senseair LP8 sensors as well as a co-located Picarro G1301 reference sensor. In more details, the following quantities are utilized in our experiments: (i) True values of CO 2 concentration level and the temperature at each minute during the whole time span are provided by the reference sensor; (ii) Measurements of CO 2 concentration level and corresponding sensor current of the detector provided by LP8 sensors and the data before 2017.07.01 are single measurements, data after 2017.07.01 are 10 minute average values.…”

Section: Numerical Resultsmentioning

confidence: 99%

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On Data-Driven Self-Calibration for IoT-Based Gas Concentration Monitoring Systems

You

Chen

et al. 2022

IEEE Internet Things J.

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In this paper, data-driven self-calibration algorithms for the Internet-of-Things-based gas concentration monitoring systems embedded with low-cost gas sensors are designed. The measurement errors are assumed to be caused by imperfect compensation for the variation of sensor component behavior. Specifically, the calibration procedure for the non-dispersive infrared CO2 sensors is developed, for which the temperature dependency is the most dominant drift source. For a single sensor, the hidden Markov model is used to characterize the statistical relationship between different quantities introduced by the physical model that builds on the Beer-Lambert law. For the calibration in the Internet-of-Things-based system, sensors first transmit their belief functions of the true gas concentration level to the cloud. Then the cloud fusion center computes a fused belief function according to certain rules. This belief function is then used as reference for calibrating the sensors. To deal with the case where belief functions highly conflict with each other, a Wasserstein distance based weighted average belief function fusion approach is first proposed as networked calibration algorithm. To achieve more long-term stable calibration results, the networked calibration problem is further formulated as a partially observed Markov decision process problem, and the calibration strategies are derived in a sequential manner. Correspondingly, the deep Q-network approach is applied as a computationally efficient method to solve the proposed Markov decision process problem. The performance of practical designs of the proposed self-calibration algorithms is finally illustrated in numerical experiments utilizing real data.

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Section: Numerical Resultsmentioning

confidence: 99%

“…I N recent years, there has been a growing interest in deploying Internet of Things (IoT) systems for gas concentration monitoring [1]- [4]. For example, IoT-based gas concentration monitoring systems that are embedded with carbon dioxide (CO 2 ) sensors are essential for actions against global warming for monitoring the greenhouse effect.…”

Section: Introductionmentioning

confidence: 99%

On Data-Driven Self-Calibration for IoT-Based Gas Concentration Monitoring Systems

You

Chen

et al. 2022

IEEE Internet Things J.

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“…20,24 Over the last 10 years, authors have investigated and proposed new solutions to sense environmental gases using wireless sensors, mostly based on short-range communication protocols, with massive usage of the ZigBee wireless protocol. [25][26][27][28][29][30][31] The study proposed in Reference 25 consists on CO 2 photoacoustic sensor deployed with a Z-Wave module for monitoring air quality in schools, with periodic data collection and transmission. Authors have not reported the possibility of the integration of the proposed sensor with other smart devices.…”

Section: Background and Related Workmentioning

confidence: 99%

A novel Internet of things‐based plug‐and‐play multigas sensor for environmental monitoring

Gomes

Rodrigues

Rabêlo

et al. 2020

Trans Emerging Tel Tech

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Ambient gas measurement is essential in diverse fields and applications, from preventing accidents, to air pollution warnings, and granting the correct gas mixture to patients in hospitals. Gas leakage can reach large proportions, affecting neighborhoods or even cities, causing enormous environmental impacts.The integration of gas sensors through the Internet of things (IoT) paradigm should ease the information collecting and sharing processes, granting better experiences to users, and avoiding major losses and expenses. With this integration, final users must be capable of operating these gadgets without previous technological knowledge, thus, the proposal of plug-and-play (PnP) sensors and actuators should be considered. This article proposes an IoT-based solution for sensing environmental gases preceding a PnP approach, combining the hardware and software integrations for a better user experience. In this proposal, the PnP interface is defined, using the universal asynchronous receiver/transmitter protocol. The wireless communication is made through the IEEE 802.15.4 and IEEE 802.11 (Wi-Fi) standards. The proposed sensor is capable of detecting smoke, oxygen, hydrogen, carbon monoxide, alcohol vapor, liquefied petroleum gas, benzene, ammonia, methane, and propane. The solution is integrated with a middleware for IoT, called In.IoT, a software that receives the sensed data, stores, and forward them to other smart devices on the same context, allowing an Android-based mobile application to warn users regarding the environmental gases concentrations. The proposed solution is experimented, demonstrated, validated, and it is ready for use. INTRODUCTIONData collection on ambient gases is essential in different fields as environmental monitoring, enclosed spaces supervision, chemical processes, and medicine, where hospitalized patients must receive the correct concentration of oxygen (O 2 ) for a best recovery process. The supervision of mines is essential to avoid explosions due to methane (CH 4 ) escapeTrans Emerging Tel Tech.

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“…Suh et al [107] presented a portable dual gas detector for H 2 S and CO based on Wi-Fi and Bluetooth, operating with MOS transducers and communicating with smartphones; the sensed data being transferred to an online spreadsheet. To avoid accidents related to gas leakages, a CO and LPG gas sensor was proposed based on the MOS technology connected through the 6LoWPAN over the IEEE 802.15.4 [146]. Sensed data is transferred to a local MQTT broker and stored on a local database to validate the proposed wireless communication.…”

Section: Gas-sensing Solutions For Iot and Wireless Sensors And Actuamentioning

confidence: 99%

IoT-Enabled Gas Sensors: Technologies, Applications, and Opportunities

Gomes

Rodrigues

Rabêlo

et al. 2019

JSAN

Self Cite

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Ambient gas detection and measurement had become essential in diverse fields and applications, from preventing accidents, avoiding equipment malfunction, to air pollution warnings and granting the correct gas mixture to patients in hospitals. Gas leakage can reach large proportions, affecting entire neighborhoods or even cities, causing enormous environmental impacts. This paper elaborates on a deep review of the state of the art on gas-sensing technologies, analyzing the opportunities and main characteristics of the transducers, as well as towards their integration through the Internet of Things (IoT) paradigm. This should ease the information collecting and sharing processes, granting better experiences to users, and avoiding major losses and expenses. The most promising wireless-based solutions for ambient gas monitoring are analyzed and discussed, open research topics are identified, and lessons learned are shared to conclude the study.Technologies to sense gases and wireless communications support are elaborated in Sections 5 and 6, respectively. The most promising solutions in terms of sensing methods and IoT-enabled solutions are discussed in Section 7 and open research topics are identified. Lessons learned are shared at Section 8 and, finally, Section 9 concludes the study. Background on Environmental GasesSome gases are the key to ensure the functionality of systems and entire industries, as well as the presence of other gases being a problem in other fields, causing the loss of entire production lines, as in the food industry, or even cause the loss of lives and explosions. In this section, the most important gases in terms of pollution monitoring and control, health issues, and accident prevention are listed with their main characteristics.Oxygen (O 2 ) is the most important gas for life, and is crucial in numerous fields. Patients under anesthesia, or recovering from surgery and from certain diseases need controlled O 2 doses to keep them alive and fully recovered. The decrease of oxygen levels in enclosed spaces can be related with other gases leakage, which would lead people inside these spaces to asphyxiate, leading to an unconscious state, or even to death [29]. Numerous industrial processes rely on the correct concentration of this gas to achieve the best results, mainly chemical and combustion, which without the correct percentages will not grant the best performance of systems. Engine control systems depend on the correct mixture to achieve the expected performances, whether it is lower fuel consumption or power and speed [29][30][31][32].Carbon dioxide (CO 2 ) is a colorless, odorless gas, generated by the oxidation and combustion of hydrocarbon, as well as by living beings in the respiration process. It is a key gas for the greenhouse effect, and the increase of its levels, in the presence of other gases, is related with atmospheric pollution. It is also the key gas on the oxygen production by the photosynthesis process. The accumulation of this gas in enclosed spaces can be responsible to s...

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An IoT-Based Smart Solution for Preventing Domestic CO and LPG Gas Accidents

Cited by 8 publications

References 15 publications

On Data-Driven Self-Calibration for IoT-Based Gas Concentration Monitoring Systems

On Data-Driven Self-Calibration for IoT-Based Gas Concentration Monitoring Systems

A novel Internet of things‐based plug‐and‐play multigas sensor for environmental monitoring

IoT-Enabled Gas Sensors: Technologies, Applications, and Opportunities

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