2022
DOI: 10.3390/info13040164
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A Smart Building Fire and Gas Leakage Alert System with Edge Computing and NG112 Emergency Call Capabilities

Abstract: Nowadays, the transformations of cities into smart cities is a crucial factor in improving the living conditions of the inhabitants as well as addressing emergency situations under the concept of public safety and property loss. In this context, many sensing systems have been designed and developed that provide fire detection and gas leakage alerts. On the other hand, new technologies such edge computing have gained significant attention in recent years. Moreover, the development of recent intelligent applicat… Show more

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Cited by 12 publications
(6 citation statements)
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“…Also, in some cases, Blynk App's notifications are delayed in sending to the user. In [20] a smart building fire and gas leakage alert system namely SB112, which combines a small-size multisensor-based scheme with an open-source edge computing framework and an automated next-generation (NG) 112 emergency call functionality was proposed using ESP32 as microcontrollers units and Raspberry Pi as Edge gateway. As part of an end-to-end scenario, crucial actors such as IoT devices, public safety answering points (PSAP), middleware for a smart city platform, and relevant operators are involved.…”
Section: B Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…Also, in some cases, Blynk App's notifications are delayed in sending to the user. In [20] a smart building fire and gas leakage alert system namely SB112, which combines a small-size multisensor-based scheme with an open-source edge computing framework and an automated next-generation (NG) 112 emergency call functionality was proposed using ESP32 as microcontrollers units and Raspberry Pi as Edge gateway. As part of an end-to-end scenario, crucial actors such as IoT devices, public safety answering points (PSAP), middleware for a smart city platform, and relevant operators are involved.…”
Section: B Related Workmentioning
confidence: 99%
“…Among these applications, smart buildings are emerging, which support the flow of information throughout the building, providing advanced functionalities and services, allowing the automatic control, monitoring, management, and maintenance of the various subsystems or applications of the building in an optimal and integrated way, locally and/or remotely [11]. There are many research papers dealing with wireless networkbased IoT/M2M smart building systems, whether MCN or WSN [12]- [20], which will be discussed in detail in the related work part. Comparing the proposed system with all these research works, the drawbacks of existing building management systems include the lack of using IoT and M2M technologies together, reliance on one or two wireless communication technologies at most, a limited wireless transmission range, mostly inconveniently designed user interface, and excessive costs.…”
mentioning
confidence: 99%
“…The vertical axis of ROC curve is true positive rate (TPR). TPR represents the proportion of the predicted positive and actually positive samples to all positive samples, as shown in Equation (15). The horizontal axis of ROC curve is false positive rate (FPR).…”
Section: Evaluation Indexmentioning
confidence: 99%
“…Then the method of multivariate weighted fusion was used to assess the probability of fire occurrence. Avgeris et al [15,16] used edge computing technology to overcome the shortcomings of the fire perception system based on the Internet of Things, such as limited energy resources and lack of real-time processing computing ability. Therefore, the fire perception system with edge computing technology can quickly detect the fire situation and take appropriate measures.…”
Section: Introductionmentioning
confidence: 99%
“…Wang et al [ 12 ] designed and performed modified hierarchical analysis to determine the weight of each sensor, subsequently utilizing the multivariate weighted fusion method to assess the probability of fire occurrence. Maltezos et al [ 13 ] used edge computing technology to overcome the shortcomings of the fire perception system based on the Internet of Things, such as limited energy resources and a lack of real-time computer processing ability. These methods improve the real-time accuracy of the fire detection system to a certain extent, but the accuracy is not satisfactory.…”
Section: Introductionmentioning
confidence: 99%