University of Hertfordshire

By the same authors

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An integrated internet of everything — Genetic algorithms controller : Artificial neural networks framework for security/safety systems management and support. / Ramalingam, Soodamani; Garzia, Fabio; Lombardi, Mara.

IEEE Explore: Security Technology (ICCST), 2017 International Carnahan Conference on, Madrid, Spain . IEEE, 2017. p. 1-6.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Harvard

Ramalingam, S, Garzia, F & Lombardi, M 2017, An integrated internet of everything — Genetic algorithms controller: Artificial neural networks framework for security/safety systems management and support. in IEEE Explore: Security Technology (ICCST), 2017 International Carnahan Conference on, Madrid, Spain . IEEE, pp. 1-6. https://doi.org/10.1109/CCST.2017.8167863

APA

Ramalingam, S., Garzia, F., & Lombardi, M. (2017). An integrated internet of everything — Genetic algorithms controller: Artificial neural networks framework for security/safety systems management and support. In IEEE Explore: Security Technology (ICCST), 2017 International Carnahan Conference on, Madrid, Spain (pp. 1-6). IEEE. https://doi.org/10.1109/CCST.2017.8167863

Vancouver

Ramalingam S, Garzia F, Lombardi M. An integrated internet of everything — Genetic algorithms controller: Artificial neural networks framework for security/safety systems management and support. In IEEE Explore: Security Technology (ICCST), 2017 International Carnahan Conference on, Madrid, Spain . IEEE. 2017. p. 1-6 https://doi.org/10.1109/CCST.2017.8167863

Author

Ramalingam, Soodamani ; Garzia, Fabio ; Lombardi, Mara. / An integrated internet of everything — Genetic algorithms controller : Artificial neural networks framework for security/safety systems management and support. IEEE Explore: Security Technology (ICCST), 2017 International Carnahan Conference on, Madrid, Spain . IEEE, 2017. pp. 1-6

Bibtex

@inproceedings{61ef38bedbf04a6f95d6a27b6a0afd43,
title = "An integrated internet of everything — Genetic algorithms controller: Artificial neural networks framework for security/safety systems management and support",
abstract = "Security/Safety is managed, mostly, by means of integrated systems which have to consider, more and more, sensors, devices, cameras, mobile terminals, wearable devices, etc. that use wireless networks, to ensure protection of people and/or tangible/intangible assets from voluntary attacks, allowing also the safe management of the related consequent emergency situations that can derive from the above mentioned voluntary attacks. These aims can be achieved using integrated systems and innovative technologies, such as Internet of Everything (IoE) which can connect people, things (mobile terminals, smart sensors, devices, actuators; wearable devices; etc.), data/information/knowledge and particular processes. An integrated security system can therefore be considered as an IoE system where several devices, sensors, cameras, people, etc. interact, generating a huge volume of data and information that is necessary to transmit, analyze and eventually store for security purposes and, ultimately, for emergency management derived from voluntary attacks. This means that it is necessary to use suitable tools capable of analyzing, in a smart way, the huge volume of information to achieve the desired security/safety objectives and eventual emergency management of critical situations. The purpose of the paper is to illustrate an integrated IoE-GACs-ANNs based framework which can support and manage security/safety systems that operate in complex environments, characterized by a multitude of sensors, devices, etc. and the related results obtained from theoretical, computational and practical point of view, where it has been applied.",
keywords = " Security, Personnel, Artificial neural networks, Genetic algorithms, Risk management, Safety, Tools ",
author = "Soodamani Ramalingam and Fabio Garzia and Mara Lombardi",
year = "2017",
month = dec,
day = "7",
doi = "10.1109/CCST.2017.8167863",
language = "English",
pages = "1--6",
booktitle = "IEEE Explore",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - An integrated internet of everything — Genetic algorithms controller

T2 - Artificial neural networks framework for security/safety systems management and support

AU - Ramalingam, Soodamani

AU - Garzia, Fabio

AU - Lombardi, Mara

PY - 2017/12/7

Y1 - 2017/12/7

N2 - Security/Safety is managed, mostly, by means of integrated systems which have to consider, more and more, sensors, devices, cameras, mobile terminals, wearable devices, etc. that use wireless networks, to ensure protection of people and/or tangible/intangible assets from voluntary attacks, allowing also the safe management of the related consequent emergency situations that can derive from the above mentioned voluntary attacks. These aims can be achieved using integrated systems and innovative technologies, such as Internet of Everything (IoE) which can connect people, things (mobile terminals, smart sensors, devices, actuators; wearable devices; etc.), data/information/knowledge and particular processes. An integrated security system can therefore be considered as an IoE system where several devices, sensors, cameras, people, etc. interact, generating a huge volume of data and information that is necessary to transmit, analyze and eventually store for security purposes and, ultimately, for emergency management derived from voluntary attacks. This means that it is necessary to use suitable tools capable of analyzing, in a smart way, the huge volume of information to achieve the desired security/safety objectives and eventual emergency management of critical situations. The purpose of the paper is to illustrate an integrated IoE-GACs-ANNs based framework which can support and manage security/safety systems that operate in complex environments, characterized by a multitude of sensors, devices, etc. and the related results obtained from theoretical, computational and practical point of view, where it has been applied.

AB - Security/Safety is managed, mostly, by means of integrated systems which have to consider, more and more, sensors, devices, cameras, mobile terminals, wearable devices, etc. that use wireless networks, to ensure protection of people and/or tangible/intangible assets from voluntary attacks, allowing also the safe management of the related consequent emergency situations that can derive from the above mentioned voluntary attacks. These aims can be achieved using integrated systems and innovative technologies, such as Internet of Everything (IoE) which can connect people, things (mobile terminals, smart sensors, devices, actuators; wearable devices; etc.), data/information/knowledge and particular processes. An integrated security system can therefore be considered as an IoE system where several devices, sensors, cameras, people, etc. interact, generating a huge volume of data and information that is necessary to transmit, analyze and eventually store for security purposes and, ultimately, for emergency management derived from voluntary attacks. This means that it is necessary to use suitable tools capable of analyzing, in a smart way, the huge volume of information to achieve the desired security/safety objectives and eventual emergency management of critical situations. The purpose of the paper is to illustrate an integrated IoE-GACs-ANNs based framework which can support and manage security/safety systems that operate in complex environments, characterized by a multitude of sensors, devices, etc. and the related results obtained from theoretical, computational and practical point of view, where it has been applied.

KW - Security, Personnel, Artificial neural networks, Genetic algorithms, Risk management, Safety, Tools

U2 - 10.1109/CCST.2017.8167863

DO - 10.1109/CCST.2017.8167863

M3 - Conference contribution

SP - 1

EP - 6

BT - IEEE Explore

PB - IEEE

ER -