Next generation automated emergency calls - Specifying next generation ecall &amp; sensor-enabled emergency services

Sdongos, Evangelos; Bolovinou, Anastasia; Tsogas, Manolis; Amditis, Angelos; Guerra, Bárbara; Manso, Marco

doi:10.1109/ccnc.2017.8015368

Cited by 10 publications

(4 citation statements)

References 2 publications

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“…in the form of an alert). Several state of the art frameworks can be found in literature that enable automatic initiation of NG112 call [29][30]. Such frameworks can fully contribute to critical infrastructure monitoring and buildings in complex urban scenes [31][32].…”

Section: B Sb112mentioning

confidence: 99%

Public safety in smart cities under the edge computing concept

Maltezos

Karagiannidis

Dadoukis

et al. 2021

2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)

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The transformation of cities into smart cities is a crucial issue in improving the living conditions of the inhabitants. One of the major goals of the smart city concept is to modernize the urban management utilizing technical tools that offer stateof-the-art technologies. Recent years have disclosed a remarkable proliferation of compute-intensive safety and security applications in smart cities. Such applications continuously generate enormous amounts of data which demand strict latencyaware computational processing capabilities. To address the limitations of cloud computing for enabling real-time smart city environments, edge computing is a viable solution. Initially, this paper, discusses the trends, the requirements and the technologies for public safety in smart cities under an edge computing concept. Then, proposes the concept and the development of an edge computing platform, namely Distributed Edge Computing IoT Platform (DECIoT), integrating to a smart building sensing system with an NG112 call functionality and a chemical precursor spectroscopic system.

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Section: B Sb112mentioning

confidence: 99%

Public safety in smart cities under the edge computing concept

Maltezos

Karagiannidis

Dadoukis

et al. 2021

2021 IEEE International Mediterranean Conference on Communications and Networking (MeditCom)

Self Cite

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“…The incident detection/reporting time is an important phase in traffic incident duration and can affect the duration time of the following phases. Obtaining the incident exact occurrence time based on an intelligent vehicle system, such as the eCall system [59,60] in Europe and the OnStar system of General Motors, is possible in the future.…”

Section: How To Combine Multiple Data Resourcesmentioning

confidence: 99%

“…Combining multiple data resources Intelligent vehicle system (for example, eCall) Sdongos et al [59]; Oorni, Goulart [60] Traffic condition detection information Wei, Lee [16]; Lee, Wei [17]; He et al [40] Crowdsourcing technology Gu et al [61]; Kurkcu et al [62] Time sequential prediction model Based on response term's report Khattak et al [5]; Pereira et al [45]; Li et al [46] Based information from social media Gu et al [61] Outlier prediction Different models for different duration ranges Lin et al [10]; Valenti et al [19] A time sequential prediction model Qi, Teng [55]; Pereira et al [45]; Li et al [46] Improvement of prediction methods Machine Learning Zhan et al [15]; Lin et al [54]; Park et al [57]; Ma et al [82] et al…”

Section: Challengesmentioning

confidence: 99%

Overview of traffic incident duration analysis and prediction

Pereira

Ben‐Akiva³

2018

Eur. Transp. Res. Rev.

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Introduction: Non-recurrent congestion caused by traffic incident is difficult to predict but should be dealt with in a timely and effective manner to reduce its influence on road capacity reduction and enormous travel time loss. Influence factor analysis and reasonable prediction of traffic incident duration are important in traffic incident management to predict incident impacts and aid in the implementation of appropriate traffic operation strategies. The objective of this study is to conduct a thorough review and discusses the research evolution, mainly including the different phases of incident duration, data resources, and the various methods that are applied in the traffic incident duration influence factor analysis and duration time prediction. Methods: In order to achieve the goal of this study, we presented a systematic review of traffic incident duration time estimation and prediction methods developed based on various data resource, methodologies etc. Results: based on the previous studies, we analyse (i) Data resources and characteristics: different traffic incident time phases, data set size, incident types, duration time distribution, available data resources, significant influence factors and unobserved heterogeneity and randomness, (ii) traffic incident duration analysis methods, mainly including hazard-based duration model and regression and statistical tests, (iii) traffic incident duration prediction methods and evaluation of prediction accuracy. Conclusions: After a comprehensive review of literature, this study identifies and analyses future challenges and what can be achieved in the future to estimate and predict the traffic incident duration time.

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“…The utilisation of VoIP and SIP for emergency communication has been a topic for intensive research during the past decades with [6], [7], [8], [9] and [10] being some of the research works in very recent years. Besides a European mandate for emergency communication M.493 [11] has been established by ETSI and the European Commission, to regulate the setup of VoIP emergency services' architectures according to European law and jurisdiction.…”

Section: Related Workmentioning

confidence: 99%

Untitled

2019

JUSPN

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VoIP-based emergency communication is a promising approach to improving the safety of citizens worldwide. The transition required in this scope includes substituting the legacy PSTN/SS7 based emergency call system by Next Generation IP based components for call establishment and control. Thereby, SIP is used as a session control protocol and RTP as the means to transfer emergency data between the caller and the corresponding Public Safety Access Point (PSAP). The emergency data is not only restricted to voice communication but can cover a rich variety of data, which can be acquired by different means (including the end-user devices) and transmitted over IP. This includes video, geopositioning data, voice, Real-Time Text, and sensor data in line with emerging IoT architectures and approaches. A vital aspect in this scope is given by the performance of the underlying network, including its capability to establish calls in emergencies and to transfer the data required for serving the situation. Therefore, in this paper, we evaluate the computational performance of the most recent VoIP emergency system implementation, which was developed by the H2020-EMYNOS project as a realisation of the EENA NG112 Long Term Definition (LTD) vision. We perform a series of trials and evaluate the performance of the EMYNOS system in a multi-party lab environment established during the project. We evaluate the time needed to perform basic emergency call operations over IP, whilst in parallel generating Internet type of background traffic. Correspondingly, we worked out a methodology and implemented it in our testbed, both of which are presented in the current paper. The obtained numerical results lead to the conclusion that SIP-based emergency services stand a good chance to replace legacy systems when it comes to their performance. Additionally, we also provide a perspective on how the blockchain technology could potentially be put to use to enhance the quality of the next-generation emergency services. We propose the utilisation of blockchain technology for tracking emergency calls and enabling efficient recognition of fraud calls, which is a critical aspect for PSAP providers concerning the potential denial of service attacks. In this context, we provide evaluations and numerical results based on a private Ethereum based blockchain playground running at the premises of Fraunhofer FOKUS.

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Next generation automated emergency calls - Specifying next generation ecall & sensor-enabled emergency services

Cited by 10 publications

References 2 publications

Public safety in smart cities under the edge computing concept

Public safety in smart cities under the edge computing concept

Overview of traffic incident duration analysis and prediction

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