Towards adaptive control in smart homes: Overall system design and initial evaluation of activity recognition

Wang, Zelin; Dogan, S.; Stolikj, Milosh; Kondoz, A.M.

doi:10.1109/intellisys.2017.8324274

Cited by 1 publication

(1 citation statement)

References 26 publications

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“…For device management, in [12] introduce the common machine learning algorithm -Support Vector Machine -to classify and handle the the status of devices. Zelin et al [46] introduce the first component of activity recognition for a user's state to support future decisions towards adaptive control over devices.…”

Section: Anomaly Detection / Device Managementmentioning

confidence: 99%

Review on the Application Areas of Decision-Making Algorithms in Smart Homes

Boden

2023

Frontiers in Artificial Intelligence and Applications

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Automated decision-making is one of the fundamental functions of smart home technologies. With the increasing availability of Artificial Intelligence (AI) and Internet of Things (IoT) technologies, those functions are becoming increasingly sophisticated. While many studies have been conducted on optimizing algorithms to improve the accuracy of predictions, less attention has been paid to how humans interact with algorithmic systems. This involves questions such as to what degree humans are involved in the algorithmic decision-making process and how we can design meaningful interactions between humans and systems relying on decision-making algorithms. With these questions in mind, our paper presents a literature review on the current state of decision-making algorithms in smart homes. Based on an analysis of 49 selected papers, we present a systematic investigation towards the application areas and the deployment functions that decision-making algorithms currently take in smart homes. Focusing on two main application areas – energy management and healthcare, our paper sheds light on the current deployment of decision-making algorithms in smart homes and identifies the current intentions of involving humans in-the-loop. Within the background of facilitating human-in-the-loop as an interaction paradigm, we aim to expose the design challenges for human-in-the-loop decision-making algorithms in smart homes which can pave the way for developing more effective human-machine hybrid intelligent systems in smart homes in the future.

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Section: Anomaly Detection / Device Managementmentioning

confidence: 99%

Review on the Application Areas of Decision-Making Algorithms in Smart Homes

Boden

2023

Frontiers in Artificial Intelligence and Applications

View full text Add to dashboard Cite

show abstract

Towards adaptive control in smart homes: Overall system design and initial evaluation of activity recognition

Cited by 1 publication

References 26 publications

Review on the Application Areas of Decision-Making Algorithms in Smart Homes

Review on the Application Areas of Decision-Making Algorithms in Smart Homes

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