Human interaction with IoT-based smart environments

Shirehjini, Ali Asghar Nazari; Semsar, Azin

doi:10.1007/s11042-016-3697-3

Cited by 40 publications

(8 citation statements)

References 35 publications

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“…Para gerar esse ambiente dinâmico é necessário que as características smart sejam incorporadas em todas as fases do ciclo de vida de um edifício (ARDITI; MANGANO; DE MARCO, 2015). Esse aspecto da construção leva a um aumento do uso das tecnologias IoT e da quantidade de objetos conectados à IoT aumentando, assim, a complexidade dos sistemas inteligentes (LIN et al, 2016;ORSINO et al, 2016;DUMANLI et al, 2017;SHIREHJINI;SEMSAR, 2017;SONG et al, 2017;ZHANG, 2018). Esse fato é caracterizado por vários estudos, como o de Fahad, Khan e Rajarajan (2015) que apresenta o uso da telemedicina em smart home, permitindo o monitoramento contínuo de pessoas que moram sozinhas.…”

Section: Ambiente Dinâmico (2015 a 2019)unclassified

“…O mesmo ocorre com a manutenção da preocupação com as características do segundo momento, como percebe-se no conceito de edifício inteligente utilizado por Arditi, Mangano e De Marco (2015) que contém aspectos de custos energéticos. Ou seja, apesar dos esforços voltados para a tecnologia, o usuário permanece nos estudos de smart home, fato também apresentando no trabalho de desenvolvimento de uma interface adequada para aumentar a confiança do usuário de smart home(SHIREHJINI; SEMSAR, 2017). Diante do cenário de evolução e difusão rápida de tecnologias voltadas para o ambiente de smart home (GHAYVAT; MUKHOPADHYAY; GUI, 2016), alguns autores afirmam que ocorre, nesse momento,…”

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Avaliação de desempenho de smart home: um mapa da literatura

Nascimento

Esslin

2021

P&P

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O uso de smart home é um tema emergente que demanda criação de estratégias para atender às necessidades dos usuários. As ferramentas da avaliação de desempenho podem ser um auxílio nesse processo. Assim, o objetivo deste artigo é identificar as características dos estudos na área de avaliação de desempenho de smart home. Foi utilizado o ProKnow-C como instrumento de intervenção metodológica que orientou a seleção de 30 artigos selecionados nas bases de dados Scopus e Web of Science. Com base no portfólio bibliográfico selecionado: (i) a análise bibliométrica permitiu a constatação da existência de discussões de características emergentes em três períodos temporais e (ii) os mapas da literatura construídos sintetizam a abordagem de smart home em termos da tecnologia, serviços e usuários. A análise sistemática possibilitou a direção de novos estudos para investigar a lacuna existente na literatura relacionada à gestão da avaliação de desempenho de smart home.

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Section: Ambiente Dinâmico (2015 a 2019)unclassified

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Avaliação de desempenho de smart home: um mapa da literatura

Nascimento

Esslin

2021

P&P

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“…There have been numerous studies highlighting the need and recognition of the human importance within the IoT [11][12][13]. Atzori et al [7] noted the importance saying "Particular attention has to be paid to the design of effective (better if "intelligent") interfaces both between humans and things and between things" (p. 135).…”

Section: Background and Related Workmentioning

confidence: 99%

Activity recognition evaluation via machine learning

Rameka¹,

Connor²,

Kruse³

2019

ICST Transactions on Ambient Systems

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With the proliferation of relatively cheap Internet of Things (IoT) devices, smart environments have been highlighted as an example of how the IoT can make our lives easier. Each of these 'things' produces data which can work in unison to react to its users. Machine learning makes use of this data to make inferences about our habits and activities, such as our buying preferences or likely commute destinations. However, this level of human inclusion within the IoT relies on indirect inferences from the usage of these devices or services. Activity recognition is already a widely researched area and could provide a more direct way of including humans within this system. This research explores the feasibility of using a cost effective, unobtrusive, single modality ground-based sensor matrix to track subtle pressure changes to predict user activity, in an effort to assess its ability to act as an intermediary interface between humans and digital systems such as the IoT.

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“…Another widespread concerning issue of multi-agent collaborative control is the triggering and identifying problem of the scene modes, which refers to the human-computer interaction technology of smart home platforms [ 33 ]. At present, most of the smart home control systems have brought in the graphical interface for user interaction controls [ 34 , 35 , 36 ], for example, Shastri et al designed a kind of Android mobile client and its human-machine interface for smart home systems [ 36 ].…”

Section: Key Technologies and Platform Implementmentioning

confidence: 99%

Combining a Multi-Agent System and Communication Middleware for Smart Home Control: A Universal Control Platform Architecture

Zheng

Zhang

Zheng

et al. 2017

Sensors

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In recent years, the smart home field has gained wide attention for its broad application prospects. However, families using smart home systems must usually adopt various heterogeneous smart devices, including sensors and devices, which makes it more difficult to manage and control their home system. How to design a unified control platform to deal with the collaborative control problem of heterogeneous smart devices is one of the greatest challenges in the current smart home field. The main contribution of this paper is to propose a universal smart home control platform architecture (IAPhome) based on a multi-agent system and communication middleware, which shows significant adaptability and advantages in many aspects, including heterogeneous devices connectivity, collaborative control, human-computer interaction and user self-management. The communication middleware is an important foundation to design and implement this architecture which makes it possible to integrate heterogeneous smart devices in a flexible way. A concrete method of applying the multi-agent software technique to solve the integrated control problem of the smart home system is also presented. The proposed platform architecture has been tested in a real smart home environment, and the results indicate that the effectiveness of our approach for solving the collaborative control problem of different smart devices.

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Human interaction with IoT-based smart environments

Cited by 40 publications

References 35 publications

Avaliação de desempenho de smart home: um mapa da literatura

Avaliação de desempenho de smart home: um mapa da literatura

Activity recognition evaluation via machine learning

Combining a Multi-Agent System and Communication Middleware for Smart Home Control: A Universal Control Platform Architecture

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