Reusable, Sharable, and Transferable Smart Data Platform for Collaborative
Development of Data-Driven Smart Cities (year 2)
Background :- UN's Sustainable Development Goals (https://sdgs.un.org/goals)- Goal 11: Make cities and human settlements inclusive, safe, resilient and sustainable- Goal 13: Take urgent action to combat climate change and its impacts- Goal 17: Strengthen the means of implementation and revitalize the global partnershipfor sustainable development- Society 5.0 (https://www8.cao.go.jp/cstp/english/society5_0/index.html)- "A human-centered society that balances economic advancement with the resolutionof social problems by a system that highly integrates cyberspace and physical space.”
Targets:- Disaster risk reduction and sustainable transport- Smart environmental Tourism and Sustainable Mobility (Dalat city, Vietnam)- Smart Dengue Early Warning System (Cauayan City, Philippines)- Smart Outdoor Activities (Singapore)- Atmosphere and Climate Change- Transboundary Air-Pollution Forecasting (Brunei)- Multi-stakeholder partnerships and voluntary commitments- xData Platform and Event Data Sharing: A decentralized and collaborative approach tofast, economically, and sustainably develop user-centered applications.
Speaker: Minh-Son Dao
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Reusable, Sharable, and Transferable Smart Data Platform for Collaborative
Development of Data-Driven Smart Cities

Project Members :- Minh-Son Dao, National Institute of Information andCommunications Technology, Japan (NICT- Asem Kasem, Universiti Teknologi Brunei (UTB)- Dang Thanh Hai, Dalat University, Vietnam (DLU)- Filip Biljecki, National University of Singapore (NUS)- Betchie Aguinaldo, Isabele State University in Cauayan, thePhilippines (ISU)Project Duration :- 24 months (2019/04/01 – 2022/03/31)

Project Budget:- 40,000 USD/year
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Project Activities: Scientific and Technological Development
1. Scientific- Values and Complex Events Prediction- Insights from cross-data- Decentralized and collaborative development- Data Visualization and Geo-based Navigation
2. Technological development- Deep Multimodal Learning for Predicting Haze
Transboundary using peripheral and weather
from stations and open data.
- Discovering Periodic-Frequent Patterns in Very
Large Uncertain Temporal Databases.
- Cross-Data model, Fuzzy membership and Visual pollution Integrating for Air pollutionEstimation and Prediction using Images.
- Interactive Incident Retrieval System for First-view Travel-log Data with new incident classes
automatically generation engine.
- Graph-based CCTV network dataset and baseline methods for Traffic Flow.
- Data collection system (e.g., sensor networks, crowdsourcing).
- A risk-avoidable navigation system based on cross-data.
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Project Activities: Experiments including field testing- Sensor Networks designation and deployment- Environment-mobility sensor networks in Dalat city (Vietnam)- Dengue sensor networks in Cauayan city (Philippines)- Data structure and database designation based on 3D-GIS data format to harmonize dataexchanged among partners and to further adapt to smart cities (Singapore)- Data collection:- Collect haze trans-border-related datasets (air pollution, fire forest, weather) fromASEAN countries (UTB)- Collect Dengue-related dataset in Cauayan city, the Philippines (ISU)- Collect CCTV videos and environment-weather dataset in Dalat city, Vietnam (DLU)- Collect first-view travel-log data for 8 typical road incidents from open sources (NICT)- Transfer knowledge:- Transfer models and tools developed by NICT to partners for reusing on local data.
- Models Evaluation:- Evaluate the adaptability and accuracy of transferred models on local data (UTB, NICT,DLU, NUS)
- System Manual Instruction:- Construct the website to give manual instructions for reusing and sharing products
developed by partners (https://www.xdata.nict.jp/xDataPFDocs/WebAPI/1.0/en/)
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R&D results: Application (or system) development
Smart environmental-mobility (DLU)

Community Dengue Early Warning System (ISU)Publicdataset
Smartsustainable
city

10 Airpollution
stations
Air pollution & weather data

CCTV City
network
Map-based Data Visualization

Video data

Risk map (app)MM-trafficEvent (NICT): Incident detection and retrieval from dashcams DB

Haze transboundary Prediction (UTB)
stations
Airpollution?

PublicDBstations
stations

Framework

fireforest

Interactive GUI

MM-Mobility-AQI (NICT): Anticipate Future AQI based on visual pollution
Urbannature
Haze
Image at Tc

MovingObjects

From November 18 Online

Crossmodel

Current
AQI

Future
AQI

Tc

Tc+t

stations

Baseline
AlgosBenchmark: Insights for wellbeing
challenge in Haze Transboundarytime

ASEAN IVO Project Review 2021

R&D results: Experiments including field testing
Haze transboundary (UTB)

MM-trafficEvent (NICT)

Incident detection modelInteractive Search Engine

Incident detection Results

Fine-grained incident detection Result

Urban nature

MM-Mobility-AQI (NICT)

Road Image

Smart environmental-mobility (DLU)

Moving objects

Estimation and Prediction Accuracy

Congestion Prediction using CCTV data
From November 18 Online

Transaction'S_NED_HOUSE(0.8),
S_MED_ROAD(0.67),
S_LOW_TRE(0.24),
S_LOW_SKY(0.19),
R_LOW_TRUCK(1),R_MED_CAR(0.94),
R_MED_PED(0.94),
R_LOW_BICYLE(0.68)

PM2.5
estimation
modelFuzzy(PM2.5)

RULE
Uncertainty
data mining
Current
PM25

S_LOW_TREE,
R_HIGH_CAR-> PM25_lv2

FuturePM25

Pattern: S_low_tree S_low_sky S_high_road PM25_lv4
R_high_motobike :[4819, 1779]-> if there are lots of motobike running on a road with few
trees, PM25 can reach level 4. And if PM25 is level 4, after
1779 period, it happens again
5
ASEAN IVO Project Review 2021

Project Activities: Budget plan in detail
1. 22K USD is located to DLU to set up the network of ten
environment-weather stations across Dalat city, Vietnam.
2. 10K USD is provided to NUS to create the software of QGIS
3. 4K USD is located to UTB to buy equipment for collecting roadincident data.
4. 4k USD is provided to ISU to finish their IoT OL trap

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R&D results: Scientific and technological
1. Values and Complex Events Prediction- MM-trafficEvent: Automatically create a new incident class and Detect incident fromdashcam videos.
- MM-Mobility-AQI: Predict environmental quality using transfer learning and uncertain
temporal transaction data mining.
- MM-trafficNET: Predict congestions using GNN techniques on CCTV database (videos).
- MMM-hazePrediction: Predict air pollution using Multi-Attention Spatio-Temporal
Graph Networks on Tokyo peripheral dataset (air pollution, weather)
2. Insights from cross-data- Mining of Periodic-Frequent Patterns in Very Large Uncertain Temporal Databases,
applied for Tokyo and Vietnam environment-visual dataset. The patterns can reason
the association between urban nature, moving vehicles, and air pollution.
3. Decentralized and collaborative development- Transferred Learning: Utilize transfer learning models developed by NICT to partners
on local datasets.
- MM-sensing system: the integration system to connect personal multimedia devices,xData Edge (local servers) and xData PF for predicting events (e.g., AQI, congestion)
4. Data Visualization and Geo-based Navigation- A risk-avoidance navigation system based on the outputs mentioned models andalgorithms for sustainable smart cities
From November 18 OnlineASEAN IVO Project Review 2021

7Scientific Contribution: Presentations at International Conferences
Affiliation

Conference
nameThe date oftheconference

The venueof theconference*NICT

IEA/AIE

2629/07/2021

VirtualConferenceMMM

2224/01/2021

SoMET

2123/09/2021*NICT

IEA/AIE

2629/07/2021

VirtualConference

No

Paper title:Author names

1.

Image-2-AQI: Aware of the
Surrounding Air Qualification by a
Few Images

Minh-Son Dao*, K. Zettsu,
Rage Uday Kiran

2.

MNR-Air: An Economic andDynamic Crowdsourcing
Mechanism to Collect PersonalLifelog and Surrounding
Environment Dataset. A Case
Study in Ho Chi Minh City, Vietnam

D.H. Nguyen, T.L.. NguyenTai, M.T. Nguyen, T.B.
Nguyen, Minh-Son Dao*3.

An Effective AQI Estimation Using
Sensor Data and Stacking
Mechanism

Q.D. Duong, M.Q. Le, T.L.
Nguyen-Tai, D.H. Nguyen,
Minh-Son Dao*, T.B.
Nguyen4.

Discovering Spatial High Utility
Itemsets in High-Dimensional
Spatiotemporal Databases

S.C. Bommisetty, P.
Ravikumar, R. Uday Kiran,
Minh-Son Dao*, Koji Zettsu

5.

Efficient Discovery of Partial
Periodic-Frequent Patterns in
Temporal Databases

S. Nakamura, R. Uday Kiran,
L. Palla, P. Ravikumar, Y.
Watanobe, Minh-Son Dao*,
K. Zettsu, M. Toyoda*NICTDEXA

2730/09/2021

VirtualConference

6.

ICDAR@ICMR 2021: Proceedingsof the 2021 Workshop on
Intelligent Cross-Data Analysis andRetrieval

Minh-Son Dao*, D.T. DangNguyen, M. Riegler*NICT

ICMR – ICDAR
workshop

1619/11/2021

VirtualConference

From November 18 Online

*NICT

*NICT

ASEAN IVO Project Review 2021

VirtualConference

VirtualConference

8Scientific Contribution: Presentations at International Conferences
AffiliationConference
name

The date oftheconference

The venueof theconference
VirtualConference

NoPaper title:Author names

7.

Overview of MediaEval 2021: Insights
for Wellbeing Task：Cross-Data
Analytics for Transboundary Haze
Prediction

Asem Kasem**, Minh-Son Dao*, Effa
Nabilla Aziz**, D.T. Dang-Nguyen, C.
Gurrin, M.T. Tran, T.B. Nguyen, Wida
Suhaili**

*NICT
**UTB
(Universiti
Teknologi
Brunei)MediaEval

12-14/12/2021

8.

Discovering Periodic-Frequent
Patterns in Very Large Uncertain
Temporal Databases

L. Palla, R. Uday Kiran, Minh-SonDao**NICT

ICONIP

8-12/12/2021

VirtualConference

9.

MM-trafficEvent: An Interactive
Incident Retrieval System for Firstview Travel-log Data

Minh-Son Dao*, Phu Nguyen, DuyPham, Binh Nguyen, Koji Zettsu

IEEE Big Data

15-18/12/2021

VirtualConference*NICT

Published Journal Papers and Book Chapters
No:

Paper title:

1.

Research on Traffic
Congestion Detection fromCamera Images in a Locationof Dalat2.

[Book Chapter] Insights forUrban Road Safety: A new
Fusion-3DCNN-PFP Model toAnticipate Future Congestion
from Urban Sensing Data

From November 18 OnlineAuthor names

Nguyen Thi
Luong***

Minh-Son Dao*,
R.Uday Kiran,
Koji Zettsu

Affiliation

Journal name

The publisherof the Journal***DLU (DalatUniversity)

Dalat University
Journal ofScience

Dalat University,Vietnam*NICT[Edited book]
Periodic Pattern
Mining: Theory,
Algorithms, andApplications

ASEAN IVO Project Review 2021

Springer
Singapore

The volume
number andPages
Volume 11, Issue
4, 2021 pp. 63-75
HardcoverISBN978-981-163963-0
eBook ISBN978981-16-3964-7

9

Scientific Contribution: Social Impacts
1. Open public datasets:- Haze Transboundary: ASEAN Archives of weather and air pollution data.
- Environment-visual datasets in Dalat city, Vietnam: Dalat city archive ofweather, air pollution, and CCTV videos.
2. Challenges:- MediaEval 2021 Insight for Wellbeing: Cross-Data Analytics for(transboundary) Haze Prediction(https://multimediaeval.github.io/editions/2021/tasks/wellbeing/)- 10 teams registered
3. Conference special session and workshops:- ICMR2021 workshop on Intelligent cross-data analytics and retrieval (ICDAR)(https://www.xdata.nict.jp/icdar_icmr2021/index.html)- 17 submitted papers, 5 accepted regular papers, and 4 short papers.
- 1 keynote , 1 invited talk, and 1 panel.
- MMM2022 Special session on Multimedia Analytics for Contextual HumanUnderstanding (MACHU) (http://mmm2022.org/ssp.html#machu)- 7 submitted papers
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Conclusion:
1. Scientific and technological• Researched and developed several topics and methods that contribute to the success ofthe project including haze transboundary prediction on ASEAN area data, interactive
incident retrieval in dashcam videos, periodic frequent patterns mining, air pollution
estimation and prediction using images, and safe route navigation planning.
2. Application (or system) development• MM sensing system (including MM-trafficEvent, MM-trafficNet, MM-mobility-AQI)• A risk-avoidance navigation system• Dengue Early Warning System architecture• APIs library and manual instruction website
3. Experiments including field testing• Evaluated (transferred) haze transboundary prediction models in ASEAN dataset• Evaluated MM-trafficEvent in Tokyo, Dalat city, and youtube datasets• Evaluated MM-mobility-AQI in Tokyo, Dalat city, and India datasets.
• Evaluated risk map in Dalat city dataset• Evaluated MM-trafficNet in Dalat city dataset
4. Datasets• Tokyo environment-lifelog dataset• Dalat city environment-lifelog-tourism-CCTV dataset• Cauayan city Dengue dataset• ASEAN environment-air pollution dataset
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Future works:
1. Scientific and technological• Continue ongoing scientific and technological purposes mentioned above• Research and Develop more topics and methods focusing on improving the smart ofdata, the flexible ability of Reusable, Sharable, and Transferable of the system.
2. Application (or system) development• Smart environmental Tourism and Sustainable Mobility for Dalat city, Vietnam• Smart Dengue Early Warning System for Cauayan City, Philippines• Smart Outdoor Activities for Singapore• Transboundary Air-Pollution Forecasting for ASEAN countries• Open dataset for open science data community• Completed xDataPF – xDataEdge and MM sensing system with high privacy protection
3. Experiments including field testinga) Field experiment of environmental quality data collection by residents using MMsensing and customization of short-term prediction of environmental quality of
tourist spots (Dalat City, Vietnam) and environmental health (Cauayan City,Philippines) using collected data.
b) Benchmarking to attract the attention from industry-academy-government onenvironment-human topics, expected to be organized in NUS

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