Emerging Ubiquitous Knowledge Services: From Mobile Sensing to

Ubiquitous Crowdsourcing and Beyond

Uichin Lee, Howon Lee*, Bang Chul Jung**, Junehwa Song***

KAIST Knowledge Service Engineering*KAIST Institute ICT

**Kyungsang University ***KAIST Computer Science

Oct. 11, 2011

Knowledge Service Innovation

• Traditional knowledge services: mainly delivered by experts with domain specific knowledge

• Dramatic change of knowledge services due to recent advances of ICTs (information and communication technologies) and networked collaboration among people

Smart Devices Social NetworkingWeb 2.0

Major Contributors

• Human: crowdsourcing, human computation• Device: processing, sensing, networking• Network: in-network services • Application: Web 2.0, service mashup, data mining

InternetSmart home/office

On the move Applications

Content provider

Fixed access

Content

Networking

Radioaccess

Device

Network

Application

Human

CrowdsourcingHuman computation

Our focus: ubiquitous knowledge services with mobile sensing and crowdsourcing

Mobile Sensing

• Sensors in smart devices (smartphones, pads): accelerometer, magnetometer, gyroscope, light, proximity, camera, voice, GPS

• Wireless communications: Bluetooth, Wi-Fi, 3/4G

• Sensor applications:– User experience enhancement

• Resizing screen/tilt, • Gaming, augmented reality

– Mobile sensing apps: • Traffic information systems• Location-based services

Crowdsourcing• “Crowd" + “Outsourcing"

– “distributed labor networks over the Internet to exploit the spare processing power of millions of human brains” – best example, Wikipedia

• Related concepts: collaborative system, wisdom of crowd, human computation, collective intelligence, wikinomics

해결책의 폭

비용

감소

가치실

현시간

(Time-to-Value) 단

축

크라우드소싱 (Crowdsourcing)

아웃소싱 (Outsourcing)

인소싱 (insourcing)

인간계산 위키피디아소셜 Q&A ( 지식인 )

노동 마켓플레이스

모바일 소셜네트워크 스마트폰을 이용한 모바일센싱

Ubiquitous Knowledge Services

Ubiquitous Knowledge Services

• Goals:– Seamlessly integrate content from various sources

at large scales • Content: data, information, knowledge• Sources: databases, grassroots (sensors, humans)

– Infrastructure dependence is minimal (compared to existing approaches)

– Also derive new values for end users in ways that the contributor of the content did not plan or imagine

교통정보수집 공동체의식제고 도시계획 현장조사 모바일 UX 테스트 연구지원 범죄수사

Examples of Ubiquitous Knowledge Services

Contents

• UKS Applications– Vehicular apps

• Traffic engineering, ride quality monitoring (cracks, potholes)

– Community-awareness apps (e.g., health and wellness)

– Social sensing with Twitter

• UKS Platform Design– Unique features– UKS platform

Potholes

Air pollution (CO2)

Social networks

• Acceleration data gathering from vehicles (geo-tagged)

• Simple data processing to detect a pothole, and statistical processing (clustering) for accurate detection

Pothole Patrol

Smooth Road

Pothole

The Pothole Patrol: Using a Mobile Sensor Network for Road Surface Monitoring, Eriksson et al, MobiSys, 2008

Community Awareness: Health and Wellness

• Personal environmental impact report (PIER) on “health and wellness”

• Participants use mobile phones to gather location data and web services to aggregate and interpret the assembled information (e.g., air pollution, CO2 emission, fast food exposure)

CO2 emissions

Fast food exposure

Air pollutionexposure(PM 2.5)

Existing Infrastructure

Annotation/Inferences

Scientific Models

Activity Classificatione.g., staying, walking, driving

GIS Data Annotatione.g. weather, traffic

Impact and Exposure Calculation

Data Aggregation

Tracklog formatSchool,hospital,fast

food restaurant locations

Weather, traffic data

User profile

            "Sensing Pollution without Pollution-Sensors”

PEIR, the Personal Environmental Impact Report as a Platform for Participatory Sensing Systems Research, Mun et al., Mobisys 2009

Social Sensing with Twitter

some users posts“earthquake right now!!”

some earthquake sensors

responses positive value・・・ ・・・ ・・・

tweets

Probabilistic model

Classifier

observation by sensorsobservation by twitter users

target event target object

Probabilistic model

values

Event detection from twitter Object detection in ubiquitous environments

・・・・・・

search and classify them into

positive class

detect an earthquake

detect an earthquake

earthquake occurrence

Earthquake shakes Twitter users: real-time event detection by social sensors, Takeshi et al, WWW 2010

Building Ubiquitous Knowledge Service (UKS) Platform

• Research community: – ArchRock, SensorBase (UCLA), SensorMap (Microsoft), IrisNet (CMU),

and many others..

• Standardization efforts:– Semantic Web Enablement (SWE)– Semantic Sensor Web (SSW)– Machine-to-Machine (M2M) – Internet of Things (IoT), e.g, EPCglobal Network

• Essential features of UKS:– Humans are part of the systems (e.g., crowdsourcing, human

computation)• Exploiting social networks is also important

– Due to resource constraints (e.g., battery), mobile operations must be optimized, which may require service-device/-network interactions

– System should perceive the intention of a user and provide the customized knowledge services at any place and any time

Building Ubiquitous Knowledge Service (UKS) Platform

• Key components of UKS: – Smart device, knowledge gateway, knowledge server– User agents, service-device/network interactions and

optimization, content integration/negotiation

Conclusion• Knowledge service innovation with recent advances of ICT

(i.e., device, network, and application intelligences) and networked collaboration among people

• Ubiquitous knowledge services aim at (1) seamlessly integrating content from various sources at large scales, and (2) deriving new values for end users in ways that the contributor of the content did not plan or imagine

– Example services: vehicular applications (pothole detection), community awareness (health and wellness), SoundSense, event detection with Tweets

• Building a ubiquitous knowledge service (UKS) platform that can integrate grassroots knowledge (and also existing content) and dynamically generate new values to end users