A novel method for detecting and predicting resident's behavior in smart home

Raeiszadeh, Mahsa; Tahayori, Hooman

doi:10.1109/cfis.2018.8336634

Cited by 10 publications

(5 citation statements)

References 11 publications

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“…By continuously analyzing user interactions, behavior patterns, and feedback, the AI can learn and customize the automation and recommendations to align with individual preferences. This personalized experience enhances user satisfaction and convenience [28]. 5.…”

Section: Contextual Awarenessmentioning

confidence: 94%

Untitled

2023

JRAR

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This chapter provided an overview of Smart Home AI, exploring its features, components, functionalities, and integration challenges. The chapter highlighted the importance of sensors, actuators, and a central AI hub in creating an intelligent living space that adapts to user needs and preferences. It discussed the various functionalities and features offered by Smart Home AI systems, such as voice-controlled assistants, automated lighting and energy management, intelligent climate control, enhanced security systems, personalized automation, predictive maintenance, and remote monitoring and control. The chapter also delved into the integration process of devices and appliances within a Smart Home AI system, discussing protocols like Zigbee, Z-Wave, Wi-Fi, Bluetooth, Thread and LoRaWAN. It addressed the challenges of interoperability, vendor-specific implementations, fragmented ecosystems, and security considerations in device integration. The interpretation and analyses of the A,I. systems shows the effectiveness of the AI algorithms and machine learning techniques in achieving the desired outcomes.In experiments of energy efficiency, user experience and security between smart home system and normal home system, smart home system showed significant superiority. Furthermore, the chapter explored the role of AI algorithms and machine learning techniques in Smart Home AI systems, enabling personalized automation, intelligent scheduling, predictive analysis, adaptive behavior, and contextual awareness. It emphasized how these AI components enhance convenience, efficiency, and the overall user experience. Privacy and security considerations were discussed, emphasizing the risks of data collection, data breaches, unauthorized access, malware, and ransomware. The chapter highlighted measures such as data encryption, user authentication, data anonymization, secure communication protocols, regular updates and patches, network segmentation, intrusion detection and prevention systems, security audits, and user education to mitigate these risks and protect user privacy.The chapter concluded by addressing the challenges and future directions of Smart Home AI. It discussed interoperability issues, ethical considerations related to privacy, security, bias, and discrimination, and potential future developments in the field. These developments included enhanced AI capabilities, edge computing, integration with smart grids and renewable energy, natural language processing and human-like interactions, predictive analytics, and proactive recommendations. Overall, Smart Home AI systems offer immense potential to transform homes into intelligent living spaces. By addressing challenges, prioritizing privacy and security, and embracing future advancements, Smart Home AI can provide seamless, personalized, and intelligent experiences that enhance our daily lives.

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Section: Contextual Awarenessmentioning

confidence: 94%

Untitled

2023

JRAR

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“…"the user normally goes to the bathroom before bed." [9] On a lower level, wearable sensors have been used to predict upper-limb reaching actions through the use of electroencephalography (EEG), but only over time periods of up to a second. [10] Locomotion events can also be predicted through wearable sensors, but again, the timeframe for this prediction is rather short.…”

Section: A Predicting Future Actionsmentioning

confidence: 99%

A Systematic Literature Review of Intent Sensing for Control of Medical Devices

Russell

Bergmann

2022

IEEE Trans. Med. Robot. Bionics

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The usefulness of medical devices, which require user input, is often limited by the control schemes that operate them. The recognition of user intent could enable far more intuitive control schemes that respond automatically to what the user wants the device to do. This paper provides a definition for intent, and then aims to systematically review current methods for sensing intent. It compares the accuracy of different methods and discusses how they might be combined. A systematic literature search was performed using IEEE Xplore, PubMed and Web of Science databases. 2311 papers were considered, reduced to 155 after review. All selected papers were assessed for quality using a checklist. The results identified and compared 15 sensing modalities used for intent sensing in a range of situations and applications that broadly fell into 12 distinct categories, with highly varying levels of accuracy. Several papers reached accuracy levels that could be suitable for everyday clinical application, but most work done on intent sensing to date has focused on activity transition classification, with fewer papers addressing task goal interference or predicting future actions. Further work can focus on the implementation of these kind of methods into a combined, context-aware intent-sensing control system.

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“…Thirdly, in terms of smart home healthcare, with the gradual increase in life expectancy, home healthcare is becoming more and more important. Using machine learning and artificial intelligence methods from sensor data can track and detect changes in individuals' behavioral pattern and lifestyle [20]. By adopting an unsupervised clustering algorithm, recurrent output neural network model, and genetic algorithm, AI systems can constantly monitor the elderly in smart homes and send an alert to the caregiver if any abnormal activities occur [21,22].…”

Section: Second-round Selection Of Literaturementioning

confidence: 99%

Review on the Application of Artificial Intelligence in Smart Homes

et al. 2019

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Smart home and artificial intelligence technologies are developing rapidly, and various smart home products associated with artificial intelligence (AI) improved the quality of living for occupants. Although some studies discussed the application of artificial intelligence in smart homes, few publications fully considered the integration of literature and products. In this paper, we aim to answer the research questions of “what is the trend of smart home technology and products” and “what is the relationship between literature and products in smart homes with AI”. Literature reviews and product reviews are given to define the functions and roles of artificial intelligence in smart homes. We determined the application status of artificial intelligence in smart home products and how it is utilized in our house so that we could understand how artificial intelligence is used to make smart homes. Furthermore, our results revealed that there is a delay between literature and products, and smart home intelligent interactions will become more and more popular.

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A novel method for detecting and predicting resident's behavior in smart home

Cited by 10 publications

References 11 publications

Untitled

Untitled

A Systematic Literature Review of Intent Sensing for Control of Medical Devices

Review on the Application of Artificial Intelligence in Smart Homes

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