PORTFOLIO. Run Cao B.Arch. South China University of Technology Selected Works 2019-2023 caorun847374504@gmail.com
CONTENT Main Projects
01
VENDOR INSIGHT | Mobile Vendor & Big Data
02
MIND FOCUS | ADHD & Open Space Office
03
COOPERATIVE BEAT | Nonverbal Communication
04
CITY ROAM | AR & Citywalk
[Urban Data Analysis] Personal Research | Guangzhou | 2023
[User Data Measurement] Personal Research | Guangzhou | 2023
[User Behavior] Academic Studio | Guangzhou | 2023
[User Experience] Academic Studio | Hong Kong | 2023
Other Works
05
Architecture Heritage Scanning & Mapping
06
Scale of Time — Poetry Space Art Installation
07
Gaze Upon Dacheng Hall
08
WATERFOWL
[3D Scanning & Field Measurement] Academic Research | Guangzhou | 2022
[Installation Construction] Internship Project | Guangzhou | 2020
[Historical Site Renovation] Graduation Project | Nanyang | 2023
[Bamboo Construction] Competition Project | Guangzhou | 2019
[Urban Data Analysis] VENDOR INSIGHT | Mobile Vendor & Big Data NLP Analysis & Object Detection & GIS Analysis
[TOOL] Weiciyun, Gephi, ArcGIS, Rhino, YOLOv4 [LOCATION] Guangzhou, Guangdong, China [DATE] Sep. - Nov. 2023 [INSTRUCTOR] Han Tu [INDIVIDUAL PROJECT]
Mobile Vendor Social Problem
Data Base
Analysis
Weibo Entries
NLP Analysis(Weiciyun)
Baidu Street View
Object Detection(YOLOv4)
Urban Data
ArcGIS Analysis
Design Guideline
Social issues arising from mobile vendors in Guangzhou have been escalating both in spatial and non-spatial dimensions. However, the majority of solutions to mobile vendor issues are formulated in a top-down manner, with very few bottom-up approaches. This research aimed to collect evaluations of the mobile vendor issue from numerous individuals through big data methods. I employ machine learning to study the spatial and non-spatial dimensions of the location of vendors. During the initial investigation into the social issues caused by mobile vendors, I scraped 41,849 Weibo entries from 2015 to 2023 related to Guangzhou and mobile vendors. I conducted Natural Language Processing (NLP) analysis, identifying the perspectives and needs of various social members on the issue. To explore the contradiction between the city's built environment and the distribution of mobile vendors, I trained a YOLOv4 model with 500 photos of mobile vendors, predicting their locations in a total of 493,220 street view images from 2014 to 2023. After combining the predicted results with Points of Interest (POI), house prices, population density, and other data for analysis, I visualized the spatial distribution contradiction of mobile vendors. Based on the results of NLP and visualization analysis, urban design guidelines were formulated to allow mobile vendors in the city to sell more effectively while reducing their negative impact on urban appearance.
Problems of Mobile Vendor Space Occupation and Urban Development
Survival Pressure and Social Injustice
An increasing number of urban spaces are becoming formalized, leading to a continuous exclusion of street vendors. The presence of mobile vendors also brings about disorder and noise, impacting the living environment of residents.
In Guangzhou, mobile vendors, as a low-income group, face significant challenges in supporting their entire families, leading to high survival pressure.
spatial conflict among the government, mobile vendors, and residents.
Government
Vendor Exclude Discipline
City Developemnt
Use Gray Space
non-spatial conflict among the government, mobile vendors, and merchants.
Resident
Government
Purchant Complaint
Sales Space
Mess Noise
Vendor Normalization
Comfortable Environment
Social Governance
Security Problem
Merchant Compete Complaint
Survival Pressure
Take Away Business
Make Profit
Accessible Data
Research Methodology
Based on the issues related to mobile vendors, both spatial and non-spatial aspects were considered, and four districts in the central areas of Tianhe, Yuexiu, Haizhu, and Liwan in Guangzhou were selected. Within this scope, relevant data about mobile vendors were collected.
01 PROBLEMS
Weibo Entries
POI Data
Population Density
Housing Price
360° Street View
Spacial problems
Non-spacial problems
city appearance
city construction
economic problem
social problem
informal space
living density
regulation
security problem
02 DATABASE Social Media Posts
Urban Data Point of Interest(POI)
OpenStreetMap
metro station market bus station city management
guangzhou.osm
Weibo Scraper
Route of vendor Route of city inspector Scope of influence
Street View Images (SVI)
road network.shp
From Baidu POI API key
GIS: Points along Gemoetory Housing Price(HP)
Keyword Mobile Vendor & Guangzhou
Guangzhou_SVI.csv
house price and rent price plot ratio
TXT 41849 texts in total
From Anjuke APP
4 direction
0° 270°
Publish time From 2014-2023
Population Density(PD)
90°
API key
180°
Guangzhou_SVI.csv
100m accuracy 1000m mesh
Publisher certification personal and official
historical streetview
123305x4=493220 From 2014 to 2023
From WorldPop.org
03 ANALYSIS Natural Language Processing Data Cleaning removing irrelevant and duplicate texts
Pedestrian
Data Intergration POI
HP
PDM GIS
Classification Sort data by time and publisher Keyword Arrangement people, place,abstract word,criteria, object
Object Detection(ML) L
Training Dataset Divide vendors into four classes Table
Car
TricycleG
round
500 streetview images in total YOLOv4 Training 1306 times iteration Average IoU = 64.67% mAP@0.50 = 95.27 %
Collocation Analysis
YOLOv4-vendor.weight Historical streetview prediction Data Intergration and Visualization
Data_Intergration.csv
predicted Pt.csv
04 DESIGN SUGGESTION DATA Analysis
Emotion Analysis Positive
SPSS
optimisml
ove serenity
interest
contempt
correlationr
egression
admiration terror
rage
Street management
Vendor
Road occupation
fear
apprehension
Individual
Square openness
amazement surprise
disgust
Government
submission
ecstasy
loathing
Negative
exploratoty
trust
vigilance annoyance anger
descriptive statistics acceptance
joy
anticipation aggressiveness
Spatial Solution
awe
Neutral
sadness
Non-spatial Solution
POI
pensiveness remorse
disapproval
ROAD
Government
Regulation
Vendor
Normalization
Individual
Cooperation
Emotional Model
Evaluation of Texts proportion of emotions
City Inspector Mobile Vendor
Evaluation of Keywords Count the number of times keywords appear in different emotions
HP PD ML POI
ROAD HP PDM L
NLP analysis Spatial Problem
Association Analysis
High-frequency nouns related to spatial location are associated with "inspector," "vendor," and "regulation." This indicates that these locations are frequent sites for regulation and inspection.
Non-spatial Problem
The scraped Weibo entries were categorized into two groups: official and individual accounts. The majority of the entries were identified as official accounts. Frequency analysis reveals that the most common nouns are "vendor," "city inspector," "street," "market," "regulation," and "city appearance." In terms of adjectives, there is a scarcityv of positive and neutral adjectives, with a predominance of negative adjectives. The most frequently occurring adjective is "messy."
Account
Noun
"Vendor" and "inspector" often co-occur and are frequently associated with "regulation." regulation" has a close relationship with "city appearance," suggesting that the purpose of regulation is for beautifying the cityscape.
Adjective
fine healthy vendor
convenient
city inspector
steady simple cheap
Positivie
unobstructed official 2020-2023
board street
citizen
fresh flexible
vendor
clinical case
extensive
arbitrary official 2017-2019
street
important fixed
market market
city
formal complex busy
school
normal
Neutual
Official
community
city inspector
free stall road square crossing
regulation
individual 2020-2023
messy epidemic
individual 2017-2019
Negative
school
Individual
official 2014-2016
food individual 2014-2016
traffic economy price
People Place
regulation
city appearance serious
Abstract noun
order
uncivil
Weight
civilization
congested
0
smell of cooking noise disturbance
disordered
Criteria
square
2000 4000 6000 8000 10000
violent narrow
city appearance
Emotion Analysis
citizen Negative posts proportion was increasing for both sides. This was attributed to the increasing restrictions on mobile vendors operating on the streets due to urban development and issues related to the pandemic.
community clinical case
Tianhe Park
Huacheng Avenue
city inspector
Ersha Island
Shamian
vendor
Yide Road
Urban Data Collection
Official
Individual
Point of Interest According to literature, mobile vendors typically choose locations near markets and transportation hubs because of the high foot traffic, and they tend to avoid areas near urban management bureau offices to prevent potential penalties from the city inspectors.
traveller customer Market_POI Density
street low
market
High
city school stall
City Manager_POI Density There was often a large gathering of mobile vendors near schools. However, due to concerns about food safety and management issues, most parents and authorities did not want vendors to appear around schools.
road square crossing
low
High
walking street bridge
Transportation_POI Density
urban village low
subway station
High
park train station regulation epidemic food Population Density
traffic
To maximize profits, mobile vendors typically choose to set up stalls in places with high foot traffic and dense population, aiming to attract a larger customer base.
economic When mobile vendors operated on the road, it affects traffic and lead to congestion. As the incidence of occupying roads increased, negative evaluations also rose.
price
Greasy dirt can affect the cleanliness of city streets and the living environment of residents.
city appearance
Therefore, both individuals and officials did not want vendors to generate greasy dirt.
order
low
High
civilization greasy dirt noise disturbance car tricycle
Housing Price
fruit barbeque vegitable waste 5.0
4.5
4.0
3.5
43.02%
47.67%
56.41%
3.0
2.5
2.0
1.5
19.27%
1.0
0.5
0.0
37.71%
20.25%
17.21%
32.08%
26.38%
Individuals generally hold a negative attitude towards street vendors than the government, and from 2014 to 2023, negative opinions have increased.
negative
positive
0.0
0.5
1.0
1.5
2.5
2.0
2014-2016
28.39%
23.34%
2017-2019
28.65%
21.61%
2020-2023 people place abstract word criteria object
38.09%
17.76%
3.0
3.5
4.0
4.5
5.0
48.27%
49.74%
44.15%
Government reports on street vendors are mostly positive; however, the proportion of negative evaluations has been consistently increasing from 2014 to 2023.
Due to their lower income and the inability to move long distances, mobile vendors often reside in close proximity to their homes. They complete the entire process, from preparing materials to selling, near their residences. Consequently, they tend to choose areas with lower housing prices. low
High
Object Detection and Data Analysis Machine Learning
2014 - 2016
2017 - 2019
2020 - 2023
Correlaiton Analysis
Conclusion
Number of table vendor
Class 0 Table Mobile Vendors
Distribution of table vendor 2014-2016
Distribution of table vendor 2017-2019
Distribution of table vendor 2020-2023
The number of table vendors has continuously decreased from 2014 to 2023, but their distribution locations have not changed significantly.
Number of ground vendor
Class 1 Ground Mobile Vendors
Distribution of ground vendor 2014-2016
Distribution of ground vendor 2017-2019
Distribution of ground vendor 2020-2023
The number of ground vendors has decreased dramatically after 2020, and their distribution locations have changed over 10 year period.
Number of car vendor The number of car vendors has continuously decreased from 2014 to 2023, and their distribution locations are quite uniform. Class 2 Car Mobile Vendors
Distribution of car vendor 2014-2016
Distribution of car vendor 2017-2019
Distribution of car vendor 2020-2023
Number of tricycle vendor
Class 3 Tricycle Mobile Vendors
Distribution of tricycle vendor 2014-2016
Distribution of tricycle vendor 2017-2019
Distribution of tricycle vendor 2020-2023
The number of tricycle vendors was several times higher in the period 2017-2019 compared to the other two years, and their distribution is relatively uniform.
Jianye Avenue
Huacheng Avenue
Dongfeng East Road
Baoye Road
Duobao Road
Zengnan Road
Design Guideline
High
Low
Heat map of combination of all the vendor from 2020 to 2023
Find out where the vendors are most densely populated and have the most serious problems based on the machine learning results, and use the NLP analysis results and correlation analysis results to implement urban design for the problem of mobile vendors.
Spatial Solution
Non-Spatial Solution
Government
Street management
School management
Time management
Set criteria
Street hygiene
Reduce noise
Get a license
Flea market for vendor
Cooperation
Complaint in time
Mobile Vendor
Low road occupation Individual
Open up the market
[User Data Measurement] MIND FOCUS | ADHD & Open Space Office VR Experiment Based on CPT and EEG Data [TOOL] Unity, Rhino, Muse2, Oculus Quest 2,Python [LOCATION] Guangzhou, Guangdong, China [DATE] Jul. - Aug. 2023 [INSTRUCTOR] Han Tu [MY ROLE] 90% UNITY Scene Design 45% User Test 70% Data Cleaning and Analysing 100% Application Design and Drawing this Pofolio [GROUP MEMBER] Yuhao Huang, Kaitong Guan, Hanyu Xue Improve Concentration Survey People with ADHD lack of concentration in open office
Questionnaires Interviews
VR Experiment
Factors Selection
Unity Modelling
Experiment Scenes
EEG test
Quantitative Analysis
APP Design
CPT test
Problems Qualitative Analysis
As open offices become increasingly common, more and more patients with Attention Deficit Hyperactivity Disorder (ADHD) find it challenging to concentrate in such environments. However, there hasn't been a systematic study on which factors of open offices affect the concentration of individuals with ADHD. This research aimed to investigate the factors influencing the concentration of individuals with ADHD in open office environments, with the goal of enhancing their focus. We conducted phone interviews with 25 ADHD patients, comprehending their assessments and various needs in an open office setting, categorizing the factors influencing ADHD concentration into three classes: spatial orientation, noise, and spatial segmentation. Subsequently, we utilized VR devices to simulate open office environments, measured users’ EEG data, and collected behavioral data through the Continuous Performance Test (CPT) to quantify the influence of these factors. We analysed the data and calculated the weight of the distraction of each factors. Based on our calculations, we designed a seat selection application to effectively address the distraction issues faced by individuals with ADHD in open office environments. Our study systematically measured the factors affecting ADHD concentration and determined their respective weights. This seat selection application proves to be a solution for improving the concentration of individuals with ADHD in open office settings.
Preliminary Research
JourneyMap & Main Factors
Background
DURING WORK
Concentration
RUN-UP TIME
I don't want to eat medicines everyday to let me concentrate.
fetch water
clear the desk
chatting
other passing by
being watched
foof smell
outside view
noise
Elements
make plans
By breaking the traditional cubicle structure and promoting communication and cooperation among employees, open office is considered to improve work efficiency. However, more and more cases showed that the open office environment may face many challenges for some employees' adult ADHD patients in their daily lives, especially in the workplace. Besides drug control, is there any other possibility to help ADHD stay focused at work?
Factors Evaluation
Main Factors
Too much distraction, I cannot stay focus! Orientation The seats in different positions affevct the concealment of the space, that is,
Sound Different sound types can affect ADHD’s concentration, such as white noise (the
Spatial type Different space types will affect ADHD’s concentration, such as whether the view
the degree of surveillance,which will affect the concentration of ADHD.
sound of keyboard, paper and pen) and seductive sounds (people talking).
outside the window can be seen, indoor work areas and rest areas
ADHD Uers Persona Needs
Behavior High Distraction
Spatial chaos
Outside scenery Being watched
People walking
Schedule planning
Dam-board
Noise
Stare at screen for a long time
Work in a relaxed sitting position
Independent work station
Get rid of ADHD medicine
Listen to people talk instead of working
Chat with multiple people
High interactive work
Relaxed working atmosphere
Talking with others Water dispenser
People talking Rest place High Universality
Low Universality
Traits
Pain points
Number of people Suffer from ADHD
Work in open space office
Take medicine regularly
Light Music Easily influenced by surrounding
Severe procrastination
Make plans without finish
Long run-up time
Desk size Exercise habit Virtual office Scent
Temperature
Space atmosphere
Low Distraction We conducted telephone interviews with 25 ADHD patients to learn about the factors that affect ADHD patients' concentration in an open office environment.We divided the factors into four categories according to the degree of distraction and university. High distraction and high university influencing factors were used as research variables in this study.
Experiment Methods
Experiment Procedure Selected Factors from Interviews
Pritential Challange and Strategies ？
Orientation of open space will affect ADHD's concentration
√
Noise in the open office will affect ADHD' s concentration
Spatial type will affect ADHD' s concentration
Causes Line of Sight (Be Watched)
Testing in real venues Use VR to simulate the is too expensive real environment
unable to measure concentration level
Use EEG equipment to measure brain wave
unable to measure work performance
Vision or Perception
Sound
Auditory Sense
Field of View
Vision or Perception
Use CPT to analyasis ADHD's performance
Variables Technologies Tech 1 — VR Simulation
Space Orientation Tech 2 — EEG Test
Tech 3 — CPT Test
Supervisor A position that can be easily seen by the supervisor
Other colleagues A positon easily seen by walking colleagues
Sound Seductive sound(S) Sound of talking and Eating
The level of being watched
Space Segmentation
White sound(W) The sound of things being carried, keyboards, drafts
The ratio of two types of sounds
Indoors(I) Outdoors(O) See space Have views out outside the office the window area The visibility of tow types of space
1 Low monitoring level
2 Middle 3 High
THETA
Procedure The level of being watched
Seductive sound(S)
White sound(W)
Indoors(I)
Outdoors(O)
High S High W Low Monitoring
Low S High W 1
High I High O
2
Low I High O
3
High I Low O
4
Low I Low O
Middle Monitoring High S Low W
Use Unity to model the VR scene, and record different office environment audios to simulate a real open office environment, and display the VR scene in Oculus Quest 2.
Scenarios
Use the Muse2 device to measure the brain wave data of experimenters. Beta waves and Theta waves can reflect the concentration level of the experimenters.
In the CPT test, the experimenters will see random letters appearing one after another and have to respond to the correct letter within a short time by clicking a button.
Scene Design
High Monitoring
Low S Low W
6 min Test and 1min Rest Each Experiment
6 min Test and 1min Rest Each Experiment
The sequence of experiments was arranged randomly
Perform scene design in unity according to experimental variables and process
6 min Test and 1min Rest Each Experiment
Experiment Scenes Based on the experimental variables and with reference to the typical open office floor plan, the scene was modeled in Unity, and people walking and talking were added to the scene to simulate the open office environment as realistically as possible. Different seat positions and different audios correspond to different variables.Different experimental scenarios are changed by the different combinations of seats and audio.Different scenes have changed the level of
Scene 4
Scene 4
Scene 2
Scene 1
Scene 4
Scene 3
Scene 4
Scene 4
Scene 7 Scene 2
Scene 5
concentration for ADHD patients.
Scene 1
Scene 4
Scene 6
Scene 3 Scene1
Scene2
Scene6
Scene3
Scene 4
Scene4
Scene7
Scene5
Scene 5
Scene 6
Scene 7
Low monitoring
Middle monitoring
High monitoring
Human voice
Environmental voice
None sound
City view
Entertainment area view
Office staff flow line
EEG Data Processing
CPT Data Processing
We tested 10 people with ADHD who took medication, and who didn't take medication, and 10 people without ADHD. Obtained their EEG data through experiments, and perform data cleaning and analysis. And the characteristics of the EEG data of the three groups were compared.
While conducting VR & EEG testing, the experimenter was asked to perform CPT testing to simulate working in an open office environment. They were faced with repetitive boring tasks and had to maintain concentration for a period of time. We recorded the timing of their behavior of clicking the botton to analysis their work performance.
β and θ brainwaves are associated with the concentration level
Collected the data of 10 testers with ADHD and 10 without ADHD
Count the average value of each group and get average brainwave
Perform moving average and linear trend analysis
ADHD without Medicine
Record the timings of tester clicking the button during the CPT test.
Compare the recorded timing to key timing of each scenarios
Correct Detection
The concentration levels of people with ADHD who don't take medication decreased over time and remained at a low level.
ADHD with Medicine
This indicates the number of times the subject responded to the target stimulus. Higher rates of correct detections indicate better attentional capacity.
Collected and analysed the data to get different test scorings
Omission Error
This indicates the number of times the target was presented, but the subject did not click the button. High rates indicate that the subject is either not paying attention to stimuli or has a sluggish response.
Correct Detection of Space Orientation
Omission Error of Space Orientation
Correct Detection of Noise
Omission Error of Noise
The concentration levels of people with ADHD who take medication increased over time but remained at a low level.
People without ADHD
The concentration levels of people without ADHD increased over time and remained at a consistently high level.
Count the Average value of the test scorings in each scenarios
Data Analysis
EEG
people walk by
people disappear
CPT Correct Detection
CPT Omission Error
Location
Sound_Mute
Testers with ADHD had low correction rate and low omission rate. Sound_Mute
Sound_human voice decreased
Tester with ADHD had Moderate correction rate and low omisison rate. Sound_human voice decreased
Low correction and high omission
Sound_environment voice decreased
Tester with ADHD had low correction rate and high omisison rate. Sound_environment voice decreased
highest
Sound_both voice decreased
Sound_both voice decreased
Tester with ADHD had high correction rate and high omisison rate. people talk loud
Slience
lowest
Orientation_low monitor
Tester with ADHD had low correction rate and high omisison rate. Orientation_low monitor
Loud white sound
lowest omission
Orientation_medium monitor
Tester with ADHD had high correction rate and lowest omisison rate.
Orientation_medium monitor
Orientation_High monitor
Tester with ADHD had high correction rate and high omisison rate.
Orientation_High monitor
Subjects with ADHD BETA_Average
THETA_Average
BETA_Trend
THETA_Trend
The correction rate of experimenters with ADHD is significantly lower than that of experimenters without ADHD, and the corrction rate of people with ADHD is more affected by changes in environmental factors.
The omission rate of experimenters with ADHD is significantly higher than that of experimenters without ADHD, and the omission rate of people with ADHD is more affected by changes in environmental factors.
Ave rate with ADHD Subjects without ADHD Ave rate without ADHD
Design Solution Concentration Factors Analysis Method Based on the analysis of the aforementioned EEG and CPT data, the arithmetic mean of all data points for Beta waves, Theta waves, as well as the average values of Correct Detection, show a negative correlation with the degree of attention dispersion in ADHD. Omission Error exhibits a positive correlation. Using these relationships, calculate the weight of attention dispersion for each factor.
Seat Evaluation
Seat Selection Application
distraction level low
high
ADHD patients can use this APP to analyze existing open office environments. Based on the analysis results, the app can suggest improvements to enhance focus and recommend products that can help improve concentration.
Home Page
AR Scanning
Seat Selection Result
Set the basic information and needs that meet their situation about the open office
If users haven't chosen the seat. Scan the office overall plan to get the spatial information of the office
Evaluate the whole office and choose the most suitable seat for ADHD patients to focus.
360° Scanning
Seat Evaluation Result
Shopping Page
If users already had a seat, used the panorama to scan the view upon the seat
If users have a seat, they can get the evaluation of their seat and the advice
Users can buy more equipment and items to improve their concentration based on advice.
The higher the weight, the greater the impact of the factor on ADHD concentration.
Conclusion on Each Factor
Weight_Space Orientation
Whether high or low monitor will lead to distraction, it is easier to concentrate when at an intermediate value.
Weight_Noise
Both human voices and white noise will have an impact on concentration, with human voices having a greater impact.
Weight_Space Segmentation
Both indoor and outdoor views have an impact on concentration, and indoor views have a greater impact.
[User Behavior] COOPERATIVE BEAT | Nonverbal Communication Cooperative Installation Test & Education [TOOL] Arduino IDE, Arduino Mega, Rhino, 3D Printer [LOCATION] Guangzhou, Guangdong, China [DATE] Jun. - Aug. 2023 [INSTRUCTOR] Yiqing Wang [MY ROLE] 70% Conceptual Design 100% Fabrication, User Test, Drawing this Pofolio [GROUP MEMBER] Ruirui Ren
Theory Nonverbal Communication Efficiency Test
Conduit Metaphor
Inspiration Heart Beat Process
Expression Body Language
Installation Fabrication Communication Education Tutorial Cooperation Training
Michael Ready proposed the Conduit Metaphor Theory in 1979, suggesting that language is like a conduit, transferring one's thoughts from one end to another. However, non-verbal communication often constitutes a significant portion of face-to-face interaction, and there has been a lack of quantifiable means to study non-verbal communication. We aim to explore the relationship between body language, expressions, and the efficiency of information transmission in non-verbal communication through the design of a collaborative installation. Simultaneously, this collaborative installation can serve as an educational tool to help children develop cooperative awareness and understand non-verbal communication. We utilized Arduino distance sensors and air pumps to detect people's positions and simulate the process of heartbeats. In user testing, participants collaborated to simulate the heartbeat process non-verbally, and their motion data were recorded to evaluate the effectiveness of their collaborative efforts. We successfully completed the simulation of the heartbeat process in user testing, analyzing the efficiency of information transmission through expressions and body movements in non-verbal communication. Additionally, we involved children in our installaition game, allowing them to experience the process of nonverbal cooperation.
Importance of Nonverbal Communication
Spoken words Eye contact Loudness Facial expressions Voice Tone Gesture Appearance Touch Body movement
People get the basic meaning of what others say from what words they say. Space/distance
Nonverbal behaviors may constitute a universal language system. Smiling, crying, pointing, caressing, and glaring are examples understood across nationalities, offering a fundamental means of communication when verbal interaction is hindered by language barriers.
People judge other people's attitudes and emotions from the tone, intonation, and loudness of their voices. Verbal 7%
Percentatge of Communication Albert Mehrabian's research has suggested that when people talking to other, 7% of meaning is communicated through spoken word, 38% through tone of voice, and 55% through body language.
Spoken words
Voice 38% Voice
Loudness
Body Language 55% Tone
Body movement
Conduit Metaphor
The Toolmakers Paradigm
Thought is a container
Mutual understanding needs iterations
Facial expressions
Space distance
Touch
Gestures
Eye contact
Apperaance
Noise
Eject
Thoughts
Extract
Idea Space
Speakers eject thoughts into idea space
Idea space contains thoughts
Listeners extract thoughts from idea space
Rather than words, an "idea space" between individuals' minds can serve as the container for mental content. The conduit is not a sealed pipeline but an open channel, enabling mental content to flow into or out of this shared space.
Meaning is created by individuals as messages are exchanged. Receivers independently interpret messages, using their personal context and past experiences to assimilate new information. Achieving shared understanding requires ongoing, dialogical communication, as listeners make sense of the presenter's perceptions without knowing their exact thoughts.
Different people in different environments and backgrounds, when faced with the same information, will interpret it based on their own knowledge and may end up with completely different interpretations.
water direction gas direction
Interaction Process
Inspiration
We found inspiration in the beating and circulation of the heart
state 1
state 2
state 3
Venous flow returns to the right atrium and arrives in the right ventricle
Venous blood is then sent in the lung via the pilmonary artery
state 4
After oxygenation in the lung, the blood returns to the left atrium
Red blood arrives in the left ventricle and then is sent in the arteries to the tissues
Metaphor installation
state 1 In the initial state, the blue side is full of water and the red side is half filled.
state 2
state 3
state 4
The balloon in the blue side starts to inflate and water flows to the red side.
The balloon on the blue side begins to deflate and the water is sucked back.
red side ballon begins to At the end of the interaction, inflate, the water flows to the the volume of outflowing bottom container. water is recorded.
Process Explanation Non-verbal communication medium 1 Not familiar with device operation mode 2 Low level of education 3 Certain communication barriers
1 Understand the operating mode of the device 2 High level of education 3 No language communication barriers
state 5
position information
position information
Sensor 2
Distance △ 2
△2=△3
Balloon 1 Inflation
△2≠△3
Static
△1=△3 △2=△4
Both ballons Deflation
Air Pump 1 Blue Side Sensor 3
Distance △ 3
Both Pumps installation reaction
installation reaction
Sensor 1
People only communicate with each other through the metaphor installation, without using language.
Installation Detail
Installation This installation will provide interactive feedback on the location information of both communicators.
Both users move within a range of 2 meters from the installation and engage in nonverbal communication.
Static
△1=△4
Static
△1≠△4
Balloon 2 Inflation
Final Mixed Liquid
Air Pump 2
User 2 people can explore the effectiveness of conveying information in different forms of nonverbal communication through the installation.
△1≠△3 △2≠△4 Distance △ 1
Red Side User 1
Liquid 1 Out flow
Sensor 4
Distance △ 4
Liquid 2 Out flow
Situation
Δ2 ≠ Δ3 static
Δ2 = Δ3 A balloon inflation
Δ1 ≠ Δ3 static
Δ1 = Δ3 both balloons inflation
Δ1 ≠ Δ4 static
Δ1 = Δ4 B balloon inflation
Δ2 ≠ Δ4 static
Δ2 = Δ4 both balloons inflation
The installation consists of three layers: interaction layer, circuit layer, and output layer. Components 1-9 are for the interaction layer, 10-14 are for the circuit layer, and 15-18 are for the output layer.
Installation Components
5
6
7
8
Installation Test
1 State 1: at the beginning of the interaction, both ballons are static 2 State 2: blue ballon inflates, water flows from blue bottle to red bottle 3 State 4: red ballon inflates,water flows form red bottle to the bottom 4 State 5: In the end, water was pumped into the bottom container
1
2
3
4
3
1
2
4
10
17
15
16
18
9
11
13
12
14
1 5000mL container 2 2000mL container 3 glass tube
10 Arduino Mega 11 HC-SR04 12 air pump
4 steel hoop 5 union elbow 6 glass stopper 7 ballon 8 plastic joint
13 12V battery 14 breadboard 15 three-neck flask 16 angle iron 17 connect plate
9 rubber band
18 screw and nut
Installation Structure
Circuit Design 5 6
3
3
5
3
8
4 9
8 4 9
-S R C H
04
1
R -S
7
The installation consists of three layer
C
04
H
7
2 Pump
11
Pump
11
14
13
10
12
12
11
10
11 Arduino Mega
13
12
14 11
11
H
H
04
C
R
-S
-S
C
12V Battery
Plan of the Circuit Layer 15
1 5000mL container 2 2000mL container 3 glass tube 4 steel hoop 5 union elbow 6 glass stopper 7 balloon 8 three-neck bottle cap 9 rubber band
10 Arduino Mega 11 HC-SR04 12 air pump 13 12V battery 14 breadboard 15 three-neck flask 16 angle iron 17 connect plate 18 screw and nut
Record Data in Excel
16 17 18
04
11
R
12 11
The user's position was detected by an ultrasonic sensor and the air pump was driven to inflate the ballon to let the liquid flow out. At the same time, the installation transmitted the location data to the computer excel document through Arduino Mega.
User Test Scenes
Experimental Procedure Each test was conducted for 3 minutes, recording position data during the process and the final volume of water flowing out. Testers
Both testers know the rule of installation
Only one tester know the rule of installation
Both testers don't know the rule of installaion
Variations
expression
expression
body movement
Nonverbal Cooperation
no expression
no body movement
Expression Cooperation
Both testers can see each other's expressions and body movements.
body movement
Body Movement Cooperation
Both testers can only see each other's expressions, but not their body movements.
Both testers can only see each other's body movements, but not their expressions.
Expression Cooperation
Body Movement Cooperation
Location Recording
Nonverbal Cooperation
tester who don't know the rule Location Analysis tester who don't know the rule
tester who know the rule
area 1
area 2
tester who know the rule area 3
area 4
Location data recorded by sensors (only one tester know the rule, Nonverbal Cooperation) Both balloons deflation
200 Blue balloon inflation 150
Blue balloon inflation
100 Red balloon inflation 50 Red balloon inflation 60
0
Static
Blue balloon inflation
Red balloon inflation
120
Both deflation
Static
Blue balloon inflation
180s
Red balloon inflation
Tutorial Scenes
Non-verbal Communication Education
Cooperation Training & Playing
This installation can train non-verbal communication and help children understand the importance of non-verbal communication. At the same time, explain the way the heart moves in a vivid way
This installation can cultivate children's sense of cooperation and allow children with language communication difficulties to participate and communicate with other children through body language.
[User Expericence] CITY ROAM | AR & Citywalk User Research and Application Development [TOOL] Figma, Rhino, Bezel, Unity [LOCATION] HongKong, China [DATE] Sep. - Nov. 2023 [INSTRUCTOR] Chengyu Chen, Han Tu [MY ROLE] Group Conceptual Design 45% User Interview 50% App Design and Drawing this Pofolio [GROUP MEMBER] Yiling Jiang, Jialu Li Iteration
User Research
Questionaires Bad Citywalk Experience
AR Prototype
User Test
Hifi Prototype
Interviews
Improve
Citywalk, as a new form of urban micro-tourism, is becoming increasingly popular among young people who enjoy exploring urban scenery and understanding city culture through this activity. However, although there are many travel apps on the market, there are few specifically designed for citywalks. We aimed to enhance the citywalk experience through augmented reality (AR) by customizing journeys for users and enriching their experience with AR landscapes. Through online surveys and phone interviews, we researched ten users who regularly participate in citywalks. We categorized them into two user personas: those primarily interested in understanding city culture and those focused on exploring and checking in at trendy spots. We identified user pain points related to their desire for more points of interest along the route and more interesting landscapes. Using Bezel, we created an AR prototype and developed low-fi wireframes. We tested our prototype with users, collected feedback, and iterated our product. Subsequently, we designed a hi-fi prototype. By combining citywalk route recommendations with navigation and AR landscapes, we created a unique citywalk experience. This not only facilitates route planning for citywalk users but also enhances the variety of landscapes they encounter during their citywalks.
ARCHITECTURE HERITAGE SCANNING & MAPPING Tomb's Details
Point Cloud in VR Scene
Location: Guangzhou, Guangdong, China Date: Sep. - Dec. 2022 Instructor: Jiang Feng Member: Shunjie Chan, Yixing Luo, Jianling Teng, Jiang Zhu, Yu Xin
Pavilion's Details
Stone pillar plinth 1
Wooden pillar plinth
Window pattern
Stone pillar plinth 2
Plaque 1
Eaves tiles
Plaque 2
Dougong
Surveying and mapping of ancient tombs of Muslim sages (Tang Dynasty, 629AC, 2370 sqm).
Installation Construction Project Name: The Scale of Time — Poetry Space Art Installation Project design & completion year: 2020 Chief Designer: Zhenjiang Guo Installation design team: Jiayu Zeng, Meijun Li, Run Cao, Minghao Zhu, Wenyu Wang Project address: Guangdong Times Museum, Guangzhou, China Building area: 15 square meters Poetry creation: Lihai Huang Interaction Design: Chuan Liu
Gaze Upon Dacheng Hall | Nanyang Wangfu Hotel Renovation Design Elevation construction
Pillar construction
Stone brick Waterproof layer Reinforced concrete
Wooden beams
Wooden pillars
Cross steel connecting
Connect steel plate
Weld steel plate
Bolted connection
Tiebeam reinforcement
Diagonal beam laying
Purlin laying
Grille laying
Glass laying Reinforced concrete pillars and beams
Graduation Project Location: Nanyang, Henan, China Area: 11000 ㎡ Instructor: Jiang Feng, Haohao Xu Date: Feb. - Jun. 2023 Individual work Wancheng Center in Nanyang: Confucian temple used to transform into Nanyang Wangfu Hotel. Plan preserves hotel functions, enhances cultural attributes, fortifies temple's essence, creates commemorative public space, exhibition, and Chinese studies areas for elevated cultural vibrancy.
Bamboo Construction PROJECT NAME: Waterfowl LOCATION: Guangzhou, Guangdong, China AREA: 18 sqm DATE : Oct. - Dec. 2019 INSTRUCTOR: Lu Xiong, Guanqiu Zhong MY ROLE: Group Design, Prototype Modelling 50%, Group Constuction GROUP MEMBER: Yi Gong, Chenlong Su, Mingqi Xiao, Xiang Xiong, Hao Huang, Xingyue Gu, Yongxi Du, Haoming Huang, Zhaoming Lv, Hankai Chen
Modelling
Selecting bamboo
Curving bamboo
Fixing bamboo frame
Making steel cable net
Tightening the cable surface
Weaving bamboo
Cutting the edge