Customized blockchain-based architecture for secure smart home for lightweight IoT

Ammi, Meryem; Alarabi, Shatha; Benkhelifa, Elhadj

doi:10.1016/j.ipm.2020.102482

Cited by 79 publications

(32 citation statements)

References 11 publications

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“…According to the introduction of Kalman filter for the optimal estimation of carrier attitude, it can be seen that motion acceleration is one of the main sources of dynamic error, especially when the limbs are in motion [17]. Assume that the motion acceleration at a certain joint is a, and the output of the accelerometer is b, which is used as a criterion for measuring and judging.…”

Section: Human Motion Modelmentioning

confidence: 99%

RETRACTED ARTICLE: Human motion capture system in sports performance based on Internet of Things technology and wireless inertial sensor

2021

EURASIP J. Adv. Signal Process.

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Taking human movements has very good prospects of application in sports, animated projects, medicine and health and other areas. This article aims to study the human motion capture system in sports performances based on the Internet of Things technology and wireless inertial sensors. This article first introduces the theory and characteristics of the Internet of Things and motion capture; next, according to the different characteristics of the sensors in the inertial motion capture system, a two-step Kalman filter is proposed to process the accelerometer and the magnetometer separately and, finally, the structure of this article. The human body motion model is used to analyze the acceleration dynamic error that occurs during the motion. In addition, an inertial motion capture system is constructed to obtain and visualize the structure of each motion node. The experimental results in this paper show that the Kalman filtering algorithm can ensure the accuracy of angle estimation under different motion states and has good fault tolerance to external interference. Among them, the error of the static state is reduced by 23.1%.

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Section: Human Motion Modelmentioning

confidence: 99%

RETRACTED ARTICLE: Human motion capture system in sports performance based on Internet of Things technology and wireless inertial sensor

2021

EURASIP J. Adv. Signal Process.

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“…For the RL algorithm, the loss is defined by the user input matrix, depending on the action chosen. Therefore, let a be a parameter to weight the decreases, the total QoE after the n iterations (transitions) of the system is determined by (18).…”

Section: Qoe In Smart Home Resultsmentioning

confidence: 99%

“…Other authors [14][15][16][17][18] present studies from the point of view of access security to IoT devices in smart homes. Apthorpe et al [14] present the study of four Smart home IoT devices.…”

Section: Related Workmentioning

confidence: 99%

“…They also comment on the main security and privacy challenges of the platforms and review the state of the art of the proposed countermeasures. Ammi et al [18] propose a novel Blockchain-based solution for secure smart home systems, using a combined hyperledger fabric and hyperledger composer. Another important aspect of the proposed solution is the mapping of the attributes of a smart home to those from the hyperledger composer.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Artificial intelligent system for multimedia services in smart home environments

et al. 2021

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Internet of Things (IoT) has introduced new applications and environments. Smart Home provides new ways of communication and service consumption. In addition, Artificial Intelligence (AI) and deep learning have improved different services and tasks by automatizing them. In this field, reinforcement learning (RL) provides an unsupervised way to learn from the environment. In this paper, a new intelligent system based on RL and deep learning is proposed for Smart Home environments to guarantee good levels of QoE, focused on multimedia services. This system is aimed to reduce the impact on user experience when the classifying system achieves a low accuracy. The experiments performed show that the deep learning model proposed achieves better accuracy than the KNN algorithm and that the RL system increases the QoE of the user up to 3.8 on a scale of 10.

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“…Currently, the IoT platform is using the security layer provided by Firebase, which Google Cloud backs. However, to provide a more solid security layer is interesting to consider the work done in [ 39 ]. Eventually, this can trigger different applications with a high level of security and reliability for Smart Homes.…”

Section: Design and Implementation Of The E-switchmentioning

confidence: 99%

Design and Implementation of the E-Switch for a Smart Home

García-Vázquez

Guerrero-Osuna

Ornelas-Vargas

et al. 2021

Sensors

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As the development of systems in smart homes is increasing, it is of ever-increasing importance to have data, which artificial intelligence methods and techniques can apply to recognize activities and patterns or to detect anomalies, with the aim of reducing energy consumption in the main home domestic services, and to offer users an alternative in the management of these resources. This paper describes the design and implementation of a platform based on the internet of things and a cloud environment that allows the user to remotely control and monitor Wi-Fi wireless e-switch in a home through a mobile application. This platform is intended to represent the first step in transforming a home into a smart home, and it allows the collection and storage of the e-switch information, which can be used for further processing and analysis.

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Customized blockchain-based architecture for secure smart home for lightweight IoT

Cited by 79 publications

References 11 publications

RETRACTED ARTICLE: Human motion capture system in sports performance based on Internet of Things technology and wireless inertial sensor

RETRACTED ARTICLE: Human motion capture system in sports performance based on Internet of Things technology and wireless inertial sensor

Artificial intelligent system for multimedia services in smart home environments

Design and Implementation of the E-Switch for a Smart Home

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