Smart Optical Sensors for Internet of Things: Integration of Temperature Monitoring and Customized Security Physical Unclonable Functions

Dias, Lília M. S.; Ramalho, João F. C. B.; Silvério, Tiago; Fu, Lianshe; Ferreira, Rute A. S.; Andre, P.

doi:10.1109/access.2022.3153051

Cited by 19 publications

(8 citation statements)

References 47 publications

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“…Dias et al have indicated that creating a tailored security system for IoT devices is complex due to the IoT environment's diverse, divided, and non-interoperable nature [7]. Various security measures have been suggested to enhance information safety, authorization, access management, confidence, and privacy in connected devices.…”

Section: Background and Analysismentioning

confidence: 99%

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Rani,

Parasa,

Hemanand

et al. 2024

MATEC Web Conf.

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The Internet of Things (IoT) expansion has introduced a new era of interconnectedness and creativity inside households. Various independent gadgets are now controlled from a distance, enhancing efficiency and organization. This results in increased security risks. Competing vendors rapidly develop and release novel connected devices, often paying attention to security concerns. As a result, there is a growing number of assaults against smart gadgets, posing risks to users' privacy and physical safety. The many technologies used in IoT complicate efforts to provide security measures for smart devices. Most intrusion detection methods created for such platforms rely on monitoring network activities. On multiple platforms, intrusions are challenging to detect accurately and consistently via network traces. This research provides a Multi-Stage Intrusion Detection System (MS-IDS) for intrusion detection that operates on the host level. The study employs personal space and kernel space data and Machine Learning (ML) methods to identify different types of intrusions in electronic devices. The proposed MS-IDS utilizes tracing methods that automatically record device activity, convert this data into numerical arrays to train multiple ML methods, and trigger warnings upon detecting an incursion. The research used several ML methods to enhance the ability to see with little impact on the monitoring devices. The study evaluated the MS-IDS approach in a practical home automation system under genuine security risks.

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Section: Background and Analysismentioning

confidence: 99%

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Rani,

Parasa,

Hemanand

et al. 2024

MATEC Web Conf.

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show abstract

“…Salah satunya dengan memanfaatkan kontak langsung dengan benda atau objek yang ingin diukur suhunya, tanpa kontak langsung dengan objek, dengan memanfaatkan perwakilan suhu dengan benda yang lain di lingkungan yang sama, dan lain lain [3]. Salah satu metode pengukuran yang umum dilakukan terutama pasca pandemi COVID -19 adalah pengukuran tanpa kontak langsung [4] [5]. Berbagai macam alat pengukuran suhu telah banyak pula digunakan untuk pengukuran tanpa kontak langsung [6][7] [8].…”

Section: Pendahuluanunclassified

Estimasi Galat Sebagai Kompensasi Hasil Pembacaan Sensor Suhu Non-Sentuh Menggunakan Regresi Linier

Purnama¹,

Afandi²,

Selamet³

et al. 2023

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Abstrak Penelitian ini bertujuan untuk membuktikan penerapan metode regresi linear untuk mengestimasi galat sebagai kompensasi untuk menurunkan galat pembacaan sensor suhu non-sentuh. Hal ini terlihat pada masa pandemi COVID – 19 melalui penggunaan thermo gun untuk mengukur suhu seseorang membutuhkan jarak yang sangat dekat. Penelitian dilakukan dengan mengukur objek air yang merupakan unsur terbanyak pada tubuh manusia. Suhu pengukuran telah dikondisikan pada 36°C, 37°C, dan 38°C dengan masing-masing variasi jarak 2cm, 4cm, dan 6cm. Hasil dari validasi menunjukkan model dapat menurunkan galat pada suhu 36°C pada masing-masing jarak sebesar 4,43%, 8,00%, dan 8,70% pada jarak 2cm, 4cm, dan 6cm. Validasi berdasarkan MAE sebelum dimodelkan adalah 2,91 dan nilai MAE setelah dimodelkan adalah 0,37. Penurunan nilai galat pada suhu 37°C untuk masing-masing jarak 2cm, 4cm, dan 6cm adalah 5,94%, 8,72%, dan 7,34%. Nilai validasi berdasarkan MAE sebelum dimodelkan adalah 3,02 dan nilai MAE setelah dimodelkan adalah 0,27. Penurunan nilai galat pada suhu 38°C untuk masing-masing jarak 2cm, 4cm, dan 6cm adalah 6,27%, 8,67%, dan 11,03%. Nilai validasi berdasarkan MAE sebelum dilakukan permodelan adalah 3,87 dan nilai MAE setelah dimodelkan adalah 0,57. Berdasarkan data tersebut dapat disimpulkan bahwa estimasi galat sebagai kompensasi hasil pembacaan sensor suhu non-sentuh mampu menurunkan galat hasil pembacaan sensor.

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“…At the same time, a structure with intrinsic sensing ability also has potential development prospects in the medical scenes . This methodology provides feasible and convenient solutions for the univocal identification and optical temperature monitoring using mobile phones and thus can be connected to the IoT directly …”

Section: Body Temperature and Thermal Comfortmentioning

confidence: 99%

“…199 This methodology provides feasible and convenient solutions for the univocal identification and optical temperature monitoring using mobile phones and thus can be connected to the IoT directly. 200…”

Section: Optical Systems For Personal Thermal Comfort Assessmentmentioning

confidence: 99%

Wearable Optical Sensing in the Medical Internet of Things (MIoT) for Pervasive Medicine: Opportunities and Challenges

et al. 2022

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Recent advances in the Medical Internet of Things (MIoT) and big data enable a prospering platform for pervasive healthcare and facilitate the transformation from hospital-centered to human-centered healthcare. Wearable devices as human interfaces provide first-hand data and real-time monitoring, which are key technologies in the MIoT. Several remarkable surveys have been conducted to summarize the recent progress in wearable sensors and systems for the MIoT and pervasive medicine. However, few have focused on wearable optical sensing (WOS) technologies, which is an emerging sensing modality in wearable devices. WOS can achieve high precision, high compatibility, high anti-interference, and low motion artifacts for human vital signal acquisition, which are particularly useful in special scenarios such as intensive care units (ICUs). These technologies can also be integrated with smart fabrics or mobile computing for out-of-hospital healthcare. This work provides the first literature review of WOS for pervasive medicine. We aim to systematically summarize the emerging WOS technologies in the MIoT for disease diagnosis and health monitoring. Specifically, this review covers the technical bases and design principles of major WOS technologies and their application domains for monitoring and treatment. We also discuss the opportunities and challenges, especially in the COVID-19 outbreak.

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Smart Optical Sensors for Internet of Things: Integration of Temperature Monitoring and Customized Security Physical Unclonable Functions

Abstract: Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 19 publications

References 47 publications

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Implementation of a multi-stage intrusion detection systems framework for strengthening security on the internet of things

Estimasi Galat Sebagai Kompensasi Hasil Pembacaan Sensor Suhu Non-Sentuh Menggunakan Regresi Linier

Wearable Optical Sensing in the Medical Internet of Things (MIoT) for Pervasive Medicine: Opportunities and Challenges

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