Optimization of Smart Home Based on Human Computer Interaction

Perspective

Wujiangshan Zhou

College of Art and Design, Beijing University of Technology, Beijing, China

Keywords: Smart Home Users, Emotionality Personalization, Human-Computer Interaction.

Abstract: Smart home products have become a "must-have" in home renovations, with particularly high penetration

rates among younger demographics and high-income households—exceeding 50% in some cities. However,

due to limitations in artificial intelligence technology, internet of things technologies human-computer

interaction technology and related technological advancements, current smart home systems still fall short of

fully meeting user demands. Today, smart homes face challenges such as complex operation and insufficient

personalization. This article focuses on optimizing smart homes in two key areas: personalization and

emotional engagement. Enhancing daily convenience and emotional value through intelligent color-based and

interface-size-adaptive layouts. Also by improving personalized connections between smart devices and users,

such as self-regulating living environment, automatic equipment operating, and voice service the system can

better adapt to individual needs, deliver tailored services, address emotional requirements, and ultimately

achieve the goal of convenient and comfortable living for users. Through the above optimization measures,

we aim to make smart homes more convenient for daily life and achieve higher levels of automation.

1 INTRODUCTION

Smart Home refers to a residential environment

where household devices are interconnected through

IoT (Internet of Things) technologies, artificial

intelligence (AI), and automated control systems,

enabling intelligent management and remote

operation. Its core objectives are to enhance living

convenience, comfort, and security. With

advancements in 5G, IoT, and AI technologies,

coupled with strong governmental policy support,

smart home adoption rates are steadily increasing.

China's smart home market size surpassed hundreds

of billions of Chinese yuan in 2019 and is projected

to exceed one trillion yuan by 2025, with a compound

annual growth rate (CAGR) exceeding 20%.

Meanwhile, smart home products have become a

standard configuration in home decoration,

particularly demonstrating higher penetration rates

among younger demographics and high-income

households, with adoption exceeding 50% in some

cities.

With the rapid advancement of artificial

intelligence (AI), IoT technologies, and big data

analytics, smart home systems have evolved from

standalone device control into holistic ecosystems.

The core objective of smart homes lies in delivering

user-centric automated services, where human-

computer interaction (HCI) technologies serve as the

critical bridge between users and devices. The

implementation depth of HCI directly determines

system efficiency and user satisfaction. However,

constrained by current technological limitations,

smart homes primarily fulfill basic functions such as

remote appliance control and intelligent security

systems, yet fall short of addressing comprehensive

user demands. Challenges persist, including

operational complexity, insufficient personalization,

and privacy vulnerabilities. Modern users

increasingly expect smart homes to proactively

perceive human states (e.g., activity patterns,

emotional cues) and autonomously adjust device

configurations, while demanding heightened

personalized adaptability. Consequently, the

continuous expansion of functional capabilities is

imperative to better align with consumer expectations

and enhance lifestyle convenience.

In recent years, there have been many

explorations in human-computer interaction for smart

homes. In smart home, because many devices need to

collect a large amount of personal life information

and share it with multiple devices through the Internet,

Zhou, W.

Optimization of Smart Home Based on Human Computer Interaction Perspective.

DOI: 10.5220/0014307200004718

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Engineering Management, Information Technology and Intelligence (EMITI 2025), pages 37-42

ISBN: 978-989-758-792-4

personal privacy has become a core area of smart

home. The optimization of smart homes requires

ensuring efficient living for users while not infringing

on their privacy. Hua Du with other authors aim to

reduce excessive privacy collection and maintain user

security by using discrete selection (Du et al., 2023).

Speech recognition is the foundation for smart homes

to communicate with users. In order to improve smart

homes’ ability to recognize and understand speeches，

Chandra Irugalbandaraand others suggest a

recognition system called “HomeIO”, which can be

able to achieve voice activity detection and automatic

speech recognition while reducing the demand for

cloud services (Irugalbandara et al., 2023). Sensors

provide useful information for the personality or

services of smart homes by collecting data on the

user’s life information. The data set designed by

Gibson Chimamiwa and other investors can better

collect the data recorded by different sensors, and

improve the accuracy of smart home services

(Chimamiwa et al., 2020). Xu Huan developed an

age-adaptive smart home human-computer

interaction system by constructing a multi-source

data fusion framework through advanced data fusion

technology, implementing control optimization

protocols for elderly-oriented interaction commands，

which achieves a rapid-response capabilities for

senior users' daily operational demands (Xu, 2022).

Nuno Costa and other researchers addressed the

challenges of elderly individuals living alone through

a large project called Aging Inside a Smart Home

(Costa et al., 2014).

Optimizing smart homes from the perspective of

human-computer interaction can promote the

development of multimodal interaction and related

technologies. Through natural interaction (voice,

gestures) and emotional computing technology, the

personalization of smart home services can be

enhanced and emotional value can be provided to

users, creating a more comfortable and convenient life.

The second part of this article will explain the core

technologies required for optimization, the third part

will explain the optimization plan, the fourth part will

discuss the optimization plan for smart homes, and

the fifth part will summarize the optimization plan.

2 RELATED TECHNOLOGIES

2.1 Concept and Application of Human

Computer Interaction

Human-Computer Interaction (HCI) is an

interdisciplinary field that studies information

exchange and collaboration between humans and

computer systems, integrating computer science,

psychology, design studies, and other disciplines. Its

primary objectives are to enhance technological

usability and user experience. The core of HCI lies in

achieving natural and efficient information

communication through interface design and

optimization of interaction modes. In smart home

applications, HCI enables natural interactions via

voice recognition, touch-sensitive interfaces, and AI

algorithms, facilitating automated control of

interconnected smart devices to improve daily

convenience.

Multimodal Human-Computer Interaction

(MHCI) is a technology that integrates multiple

sensory modalities such as speech, tactile input,

vision, and gestures to enable natural and efficient

information exchange between humans and

machines. Interaction using a single sensory modality

is called unimodal, while employing three or more

modalities is referred to as multimodal (Liu & Liang,

2024). Touchscreen control, video control, and voice

control stand as the three most prevalent human-

computer interaction methods in smart homes (Zhou

et al., 2022).

2.2 The Development of AI Technology

and Its Application in Smart

Homes

Artificial intelligence technology has achieved

leapfrog development in recent years through deep

learning, breakthroughs in computing power, and big

data. In the field of smart homes, AI enables voice

assistants to achieve human-machine voice

interaction through voice processing. Meanwhile,

computer vision technology supports facial

recognition, which can be applied in security

monitoring and other scenarios. Machine learning

algorithms enable devices to have autonomous

learning capabilities, analyze user habits, and change

the operating mode of household appliances by

combining with IoT technology. Intelligent cameras

enable high-definition filming and remote monitoring,

and integrate monitoring and alarm through AI to

ensure the safety of individuals living alone. In the

future, with the continuous development of AI, smart

homes will present more natural human-machine

collaboration and better service capabilities.

EMITI 2025 - International Conference on Engineering Management, Information Technology and Intelligence

3 OPTIMIZATION STRATEGIES

3.1 Optimizing Smart Homes with

Emotional Resonance and User

Centered Personalization Principles

3.1.1 Emotionality

Emotional Experience Design refers to design

methodologies and principles that prioritize and

cultivate users' positive emotional experiences during

interactions with products, services, or environments.

This approach specifically focuses on creating

meaningful affective responses through intentional

design interventions (Xu & Huang, 2024). Emotional

Design was first proposed by American cognitive

psychologist Donald Norman as a design philosophy.

He categorized emotional design into three levels:

Visceral Level Design, Behavioral Level Design, and

Reflective Level Design.

Visceral Level Design emphasizes the sensory

experience evoked by the design itself. In the current

development trend of smart homes, enhancing the

direct sensory impact of smart home systems allows

users to derive greater emotional value. This can be

achieved through personalized interface layouts and

unique voice interaction features in smart home

ecosystems, which elevate users' trust and affinity

toward these systems.

Behavioral Level Design focuses on the

functionality and efficiency of products. By

optimizing the operational efficiency of smart home

devices, users' daily life efficiency and comfort are

significantly improved.

Reflective Level Design involves post-usage

reflection, where users evaluate whether the product

aligns with their needs and fulfills their emotional

expectations, thereby influencing their purchase

decisions or continued usage.

3.1.2 Personalization

The personalized needs of smart home systems stem

from the diversity of user scenarios and requirements.

People's lifestyles, habits, and emotional appeals vary

significantly, demonstrating inherent heterogeneity.

Single-mode devices cannot satisfy the demands of

all user groups, necessitating customized services

tailored to different demographics to better

accommodate diverse user needs.

Figure 1 illustrates the structural framework for

smart home optimization strategies.

Figure 1: Structural framework for smart home

optimization strategies (Picture credit: Original).

3.2 Optimization

Based on the principles of emotional engagement and

personalization, researchers can optimize smart home

systems to better align with users' needs and

preferences.

Drawing on the visceral level of human

perception, smart home interfaces should adopt an

intuitive layout design, ensuring that application

information is presented in a clear and concise

hierarchy. This allows users to quickly and accurately

locate desired functions during interaction. By

analyzing usage frequency data for different features

over time, frequently accessed functions can be

emphasized through enlarged icons or highlighted

colors for enhanced visibility. As a critical element in

interface design, color significantly influences users'

emotional responses to smart home systems.

Implementing zonal color coding and incorporating

user-preferred color schemes can elevate both the

aesthetic appeal and emotional acceptance of smart

interfaces, thereby improving overall user

engagement and satisfaction. For elderly users, red

and orange should be predominantly used as layout

color schemes. This is because older adults

experience relatively less impairment in

distinguishing red and orange hues. Additionally, red

can evoke a sense of warmth for seniors living alone

long-term, while orange helps elders perceive vitality

(Zhao, 2024).

The goal of optimizing smart home systems is to

enhance their operational efficiency and improve

users' quality of life. According to IDC's smart home

research, 72% of users desire devices capable of

autonomously learning their habits rather than

requiring manual configuration. Optimization can be

achieved through environmental sensors that detect

Optimization of Smart Home Based on Human Computer Interaction Perspective

human behavior under varying weather conditions

and identify users' preferred temperature, humidity,

and other parameters in different settings. Once

environmental changes are detected, the system

automatically adjusts to provide the most comfortable

conditions. By employing LSTM (Long Short-Term

Memory Networks) to build a user behavior

prediction model, smart homes collect data on users'

daily activities over the past week, analyze unique

patterns and variations, and generate predictions for

the next day's behavior through big data analytics.

This enables smart homes to proactively adapt indoor

environments to users' optimal preferences during

different activities, thereby better safeguarding their

quality of life. Figure 2 illustrates the structural

framework of this process.

Figure 2: The system structure of intelligent control of the

indoor environment (Picture credit: Original).

Smart home systems enable devices to operate

proactively, reducing user waiting time and

enhancing daily efficiency. Taking coffee machines

as an example—an essential part of daily life—87%

of users believe that the automatic coffee preparation

feature significantly enhances daily convenience. By

integrating smart home technology with the Internet

of Things (IoT), devices are connected via Wi-Fi,

Bluetooth, and other protocols to enable data sharing.

A smart hub (e.g., Amazon Echo, HomePod)

consolidates data from multiple devices, and

computational analysis of this data identifies precise

usage patterns and frequencies in user behavior. This

allows the system to preemptively activate devices

like coffee machines, saving time. The diagram below

illustrates the automated process of a coffee machine

preparing beverages for users. First, IoT technology

is employed to collect data on the coffee machine's

operating hours and users' activity patterns. By

analyzing the peak frequency of coffee consumption

times, the system can prepare coffee in advance, as

shown in Fig. 3.

Figure 3: Coffee machine automatic operation flow chart

(Picture credit: Original).

Over half a century ago, Weizenbaum developed

a simple yet powerful chatbot called ELIZA

(Chkroun & Azaria, 2021). It delivers substantial

emotional resonance to users. Therefore, our smart

home optimization incorporates voice-controlled

interactive communication capabilities between

smart home systems and occupants. Voice control is

one of the most popular control methods for smart

homes, accounting for 56.55% of usage. Consumers

expect voice assistants to recognize the voices of

different family members and provide customized

services based on personal preferences. Through

voice recognition and sentiment analysis algorithms,

the system can capture users' tone, intonation, and

emotion-specific keywords to identify their

emotional state and adapt its responses accordingly.

Additionally, by monitoring users' body language via

cameras, it can achieve multimodal interaction, such

as integrating speech, facial expressions, and physical

movements—to more accurately assess whether the

current environment aligns with user comfort and

make real-time adjustments. For users living alone,

elderly individuals, and children, smart home systems

can infer their emotional states from their facial

expressions and provide emotional value through

conversational interactions, thereby reducing feelings

of loneliness. Figure 4 illustrates the communication

flow between smart home devices and users.

Figure 4: Smart home and user communication flow chart

(Picture credit: Original).

EMITI 2025 - International Conference on Engineering Management, Information Technology and Intelligence

4 DISCUSSION

4.1 Advantage

Smart homes, through voice control and remote

operation capabilities, liberate human labor and

optimize the efficiency of daily life management.

Moreover, smart home systems that regulate

temperature and humidity enable people to live in

their most comfortable environment, significantly

enhancing daily comfort and quality of life. Smart

home systems provide personalized services that

bring people a more convenient lifestyle. For example,

smart coffee machines can automatically prepare

beverages for users without requiring manual

operation, significantly enhancing daily convenience.

Furthermore, smart homes can provide emotional

value to people, enabling individuals of all ages to

feel a sense of companionship and enhancing their

overall happiness in daily life.

4.2 Limitation

Smart home devices offer many advantages, but they

also have significant limitations. These limitations

manifest at multiple levels. Firstly, smart homes are

heavily reliant on technology, with these systems

widely employing cloud-based services such as those

provided by Google and Amazon—a dependency that

exposes them to cyber attacks. Internet outages or

system failures can result in complete device

malfunctions. To ensure proper operation, these

systems require both stable internet connectivity and

a secure environment free from cyber threats

(Irugalbandara et al., 2023, Huang, 2023).

Additionally, as smart homes require the collection of

users' daily life data and even facial expressions,

privacy and data security emerge as critical concerns,

with potential leaks posing severe consequences for

users. Furthermore, incompatibility between different

brands of smart home products often forces users to

remain within a single ecosystem, highlighting the

urgent need to reduce technical barriers between

manufacturers and improve cross-brand

interoperability.

5 CONCLUSION

The paper proposes personalized layout design for

smart homes while optimizing their emotional

resonance and personalized features. Through

optimization, smart homes can better enhance

personalized services tailored to individual user needs.

Personalization is a critical pathway toward

optimizing user experience. By integrating voice

emotion recognition and facial expression analysis，

smart systems achieve affective computing

capabilities, supporting emotional well-being and

adaptive environmental adjustments. The evolving

computational capabilities of artificial intelligence,

coupled with progressive developments in Internet of

Things (IoT) architectures, empower smart home

systems to process user behavioral data through

sophisticated algorithms, thereby delivering context-

aware services tailored to individual preferences.

Optimizing smart homes from a human-computer

interaction perspective can not only enhance the

convenience of people's lives but also unlock broader

market opportunities for smart home technologies. In

the future, it will be essential to continuously break

down barriers between different smart home brands,

enabling seamless data sharing across platforms to

avoid redundant data collection.

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