8
B. Smart Homes diverse user commands and queries, catering to a global
user base in smart homes. Understanding various languages
Advancements in electronics, information communication
helps AGI systems recognize cultural nuances, which can
technologies,mobileapplications, autonomoussystems,virtu-
be crucial for personalized and context-aware interactions in
alization, and cloud computing have contributed to the evolu-
smart homes.
tionofthesmarthomeconcept.Asmarthomeischaracterized
The Whisper model [216] has revolutionized speech recog-
as a living space outfitted with devices that possess com-
nition, delivering exceptional accuracy across diverse speech
putational capabilities and communication technologies. This
tasks and challenging conditions. Through minimal data pre-
setupseamlesslyintegratesdiverseIoTdevicesandsensors,AI
processing and weak supervision, it achieves state-of-the-art
algorithms, and network connectivity. The purpose is to facil-
results, excelling in multilingual recognition, translation, and
itate smooth communication and control of various systems
language identification. Its accuracy in understanding spoken
and appliances within the household. Through collaborative
language can enable more intuitive and natural interactions
interaction, these IoT devices ensure convenience, comfort,
between users and their smart home systems. This includes
security, energy efficiency, and an improved quality of life for
controlling devices, requesting information, and even having
residents. Smart homes offer remote user control, enabling a
context-aware conversations. This level of communication
wide range of tasks, such as voice interaction, setting alarms,
bridges the gap between human language and technology,
managing to-do lists, and controlling other smart devices like
bringing smart home interactions closer to human-like inter-
locks, light bulbs, thermostats, and more [182], [183], [184].
actions, a significant step towards AGI.
A smart home is characterized by its automation capa-
Recent strides in text-to-speech synthesis have led to inno-
bilities [185], [186], [187], [188], allowing tasks such as
vative models like VALL-E [217]. This pioneering approach
adjusting lighting, temperature, and blinds to be executed
capitalizes on abundant semi-supervised data to train a versa-
based on occupants’ preferences or environmental conditions.
tile text-to-speech system, capable of producing personalized,
The interconnected IoT devices communicate through a cen-
high-qualityspeech.Itoffersdiverseoutputswhilemaintaining
tralized hub or cloud-based platform, while remote access
the acoustic setting and speaker’s emotions related to the
and control enable homeowners to manage devices from afar
prompt. Incorporating VALL-E into AGI systems for smart
using smartphone apps or web interfaces [189], [190], [191],
homeselevatesthequalityofcommunication,personalization,
[192].Energyefficiency[193],[194],[195],[196]ispromoted
and adaptability. These advancements bring us closer to the
through smart thermostats, lighting, and energy monitoring
vision of AGI-powered smart homes that seamlessly interact
systems to reduce consumption and utility bills. Enhanced
with users in ways that are natural, tailored, and responsive,
securityandsurveillancefeatures[10],[197],[198],[199],like
fostering an environment that aligns with users’ preferences
cameras, motion sensors, and smart locks, bolster safety and
and needs.
real-time monitoring. Voice-activated virtual assistants [200],
[201], [202], such as Amazon Alexa or Google Assistant,
facilitate device control via voice commands. Smart homes C. Smart Healthcare
also adapt to occupants’ preferences, delivering personalized Incorporating AGI into the healthcare sector presents a
experiences[203],[204],[205],[206]andautomatingroutines. vast potential for optimizing patient care [75], [78], refining
Moreover, certain smart homes incorporate health monitoring wearable device monitoring, and more. With the continued
devices for tracking vital signs, activity levels, and sleep development of AGI, various aspects of healthcare have wit-
patterns to promote wellness and safety for residents [207], nessed notable advancements. Research findings increasingly
[208], [209], [210]. underscore AGI’s capacity to usher in a transformative era for
Large language models built upon the Transformer archi- intelligent healthcare solutions.
tecture, such as BERT [33], GPT [211], XLNet [212], and AGI has demonstrated its potential in enhancing patient
T5 [213] have introduce both opportunities and challenges care through the prediction of disease progression, identifica-
towards AGI-integrated smart home. To address challenges tion of potential complications, and optimization of treatment
includingthemodels’dependenceondiscretetokensforinput, strategies [75]. Leveraging electronic health record (EHR)
or domain mismatch problems [214], dedicated frameworks data, machine learning models can forecast patient outcomes,
have been developed based on large language models. Ad- furnishinginsightscriticalforpersonalizedtreatmentplanning.
vances in technologies like XLS-R [215], Whisper [216], Through EHR analysis, AGI can construct comprehensive
and DALL-E [217] contribute to the advancement of AGI in patient profiles, amalgamating medical history and current
smart homes by enhancing the capabilities of AI systems in health conditions. Rajkomar et al. [220] demonstrated the
understanding, communicating, and adapting to the dynamic high accuracy of outcome prediction through machine learn-
and complex environments of modern living spaces. ing using EHR data, culminating in enhanced patient care
XLS-R is a large-scale model for cross-lingual speech rep- strategies. Furthermore, AGI’s pivotal role lies in furnish-
resentationlearningbasedonwav2vec2.0[218],[219],where ing tailored treatment recommendations that align with each
cross-lingual transfer is employed to enhance representations patient’s distinct characteristics and requirements. Zhang et
for low-resource languages using the knowledge from high- al. [221] highlighted the effectiveness of machine learning-
resource languages. XLS-R’s ability to understand and pro- driven recommendation systems in providing personalized
cess multiple languages enables AGI systems to comprehend treatment plans. More recently, Venkatasubramanian et al.