1. 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

2. 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 Networking Web 2.0

3. Major Contributors Human: crowdsourcing, human computation Device: processing, sensing, networking Network: in-network services Application: Web 2.0, service mashup, data mining Internet Smart home/office On the move Applications Content provider Fixed access Content Networking Radio access Device Network Application Human Crowdsourcing Human computation Our focus: ubiquitous knowledge services with mobile sensing and crowdsourcing

4. 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

5. 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 가치실현시간 (Time-to-Value) 단축 크라우드소싱 (Crowdsourcing) 아웃소싱 (Outsourcing) 인소싱 (insourcing) 인간계산 위키피디아 소셜 Q&A ( 지식인 ) 노동 마켓플레이스 모바일 소셜네트워크 스마트폰을 이용한 모바일센싱 Ubiquitous Knowledge Services

6. 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 교통정보수집공동체의식제고도시계획현장조사모바일 UX 테스트연구지원범죄수사 Examples of Ubiquitous Knowledge Services

7. 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

8. 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

9. 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 pollution exposure (PM 2.5) Existing Infrastructure Annotation /Inferences Scientific Models Activity Classification e.g., staying, walking, driving GIS Data Annotation e.g. weather, traffic Impact and Exposure Calculation Data Aggregation Tracklog format School,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

10. Social Sensing with Twitter some users posts “earthquake right now!!” some earthquake sensors responses positive value ・・・ tweets Probabilistic model Classifier observation by sensors observation 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 earthquake occurrence Earthquake shakes Twitter users: real-time event detection by social sensors, Takeshi et al, WWW 2010

11. 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

12. 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

13. 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