Comparison of fiducial marker detection and object interaction in activities of daily living utilising a wearable vision sensor

Shewell, Colin; Medina-Quero, Javier; Espinilla, Macarena; Nugent, Chris; Donnelly, Mark; Wang, Haiying

doi:10.1002/dac.3223

Cited by 13 publications

(8 citation statements)

References 33 publications

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“…Third, the application layer. The application layer is responsible for the connection between the network and users, combining perception information with the characteristics of needs and applications, analyzing and processing sensor information and providing services according to user needs [32]- [34].…”

Section: ) the Network Structure Of The Internet Of Thingsmentioning

confidence: 99%

Intelligent Monitoring System of Residential Environment Based on Cloud Computing and Internet of Things

Liu

Xiao

2021

IEEE Access

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With the development of society and the improvement of living standards, people pay more and more attention to their own living environment and life safety, and more people are gradually paying attention to the impact of the quality of the living environment on their health and work efficiency, and to meet this demand of people, it is necessary to effectively monitor and control the living environment. Based on this, this article applies cloud computing and Internet of things technologies that have developed rapidly in recent years, and proposes to design a residential environment intelligent monitoring system based on cloud computing and Internet of things, and use Internet of things and sensor technologies to achieve target connection and communication. It then uses distributed computing, a cloud computing technology, to implement integrated, standardized management of this system for truly intelligent monitoring. In this article, we first gathered a large amount of information through literature search methods, systematically introduced cloud computing and Internet of Things technologies, and introduced two applications in environmental intelligent monitoring. Next, we propose a design experiment of a residential environment intelligent monitoring system based on cloud computing and the Internet of Things, and propose an overall concept of system design, system hardware and software design requirements, and device selection and comfort evaluation. And living environment data integration is introduced in detail. We then tested the performance of the system in a specific application of the system in a real residential environment, using data parameters collected at different points in time as experimental data. Finally, it is concluded that the fuzzy close fusion algorithm used in the experiment can obtain data parameter values that are in good agreement with the real values, and the error range is controlled within 0-0.01; the indoor environment comfort is judged by 1 as the standard. PMV > 1 indicates that the comfort level is excellent, and in the test experiment, each parameter value at 5 time points is all >1, indicating that the indoor environment comfort level detected by the system is excellent.INDEX TERMS Cloud computing, Internet of Things technology, living environment, intelligent monitoring system. I. INTRODUCTION A. BACKGROUND AND SIGNIFICANCE

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Section: ) the Network Structure Of The Internet Of Thingsmentioning

confidence: 99%

Intelligent Monitoring System of Residential Environment Based on Cloud Computing and Internet of Things

Liu

Xiao

2021

IEEE Access

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“…Within the homebased literature description of activities through the detection of human joints with a vision sensor has been considered (Rege, Mehra, Vann & Luo, 2017). In addition, the wearable vision sensors (Shewell, Medina-Quero, Espinilla, Nugent, Donnelly & Wang, 2017) in daily object interaction has been reported. The main disadvantages of vision sensor approaches include the high computational costs, in addition to privacy concerns (Sixsmith & Johnson, 2004).…”

Section: Representation Of Temporal Data For Real-time Activity Recognitionmentioning

confidence: 99%

Ensemble classifier of long short-term memory with fuzzy temporal windows on binary sensors for activity recognition

Medina-Quero

Zhang

Nugent

et al. 2018

Expert Systems with Applications

Self Cite

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There are approaches that successfully recognize activities of daily living by using a trained classifier on feature vectors created from binary sensor data. Although these approaches have been successful, there are still open issues such as the evaluation of multiple temporal windows, ensembles of classifiers or unbalanced classes which need to be addressed in order to improve the performance of the real-time activity recognition process. In this paper, we present a methodology for Real-Time Activity Recognition based on the diverse fields of Machine Learning, including Fuzzy Logic and Recurrent Neural Networks. The methodology uses a long-term and short-term representation of binary-sensor activations based on Fuzzy Temporal Windows.The paper proposes an ensemble of activity-based classifiers for the purposes of balanced training, where each classifier in the ensemble is a Long Short-Term Memory. The approach was evaluated using two binary-sensor datasets of daily living activities and benchmarked against previous approaches based on the combination of sensor activation features.

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“…Each of these markers are associated with an individual ID. This method of identifying pieces has been employed previously, with prosperous results (La Delfa, 2015), (Chewell, 2016). For this project, 100 markers, with a size of 1cm, were generated using the DICT_6X6_100 dictionary.…”

Section: Designmentioning

confidence: 99%

Designing a Musical Game Of Shogi

Davenport¹,

Dejaegere²,

Lochrie³

et al. 2018

EasyChair Preprints

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This paper will discuss the design and implementation of the Shogi board, an interface built to allow members of the general public to interact with various Japanese instruments in a novel way. The Shogi board brings elements of Japanese culture to the attention of the general public in England ahead of the season of culture commencing in 2019. This interface utilizes maker technology to create an accessible method for members of the general public to compose music with traditional instruments in public settings.

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Comparison of fiducial marker detection and object interaction in activities of daily living utilising a wearable vision sensor

Cited by 13 publications

References 33 publications

Intelligent Monitoring System of Residential Environment Based on Cloud Computing and Internet of Things

Intelligent Monitoring System of Residential Environment Based on Cloud Computing and Internet of Things

Ensemble classifier of long short-term memory with fuzzy temporal windows on binary sensors for activity recognition

Designing a Musical Game Of Shogi

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