International Collaboration - Internet of Things (IoT) Marimuthu (Palani) Palaniswami Department of Electrical and Electronic Engineering The University of Melbourne, Australia ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing

ISSNIP – ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing –Access to an extended network of over 200 researchers and post-graduate students, as well as extensive links throughout Australia, the USA, Europe and Asia –50 primary participants –50 affiliate researchers & post-docs –75 research students –10 Australian universities and partner organisations –30+ Industry linkages –Nationwide sensor network research infrastructure (GBROOS, BigNet) Funding ARC DEST DIISR NSF DARPA EU Partners Universities National International Industry Research Institutions Melbourne ISSNIP 2

ISSNIP ( ) – International Outlook Member Organizations26 Affiliated Organizations83 Active Researchers CIs48 Affiliated Researchers66 ECRs38 Students97 Funded ECRs and students Publications Books/book Chapters72 Journals201 Conference papers283 New grants112 Events (conferences, workshops, meetings, etc)

ISSNIP - European Linkages 4 IoT Engagement (H2020) Citizen centric IoT Future Internet and IoT Infrastructure for IoT Co-creating Smart Cities, Citizen Services

5 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

City Environment – Particulate Matter (PM) > 4.6 million people die annually from the direct impact of air pollution – WHO Major cause of respiratory conditions –Asthma, Bronchitis, chronic obstructive, pulmonary disease PM are small enough to –penetrate the deepest portions of the lungs –absorbed into the bloodstream In Australia –8.36% increase in cardiovascular related hospital admissions in Adelaide with a 10μg/m3 increase in PM2.5 – 4% increase in respiratory related emergency hospital admissions in Brisbane with an increase of 10μg/m3 in PM10 In six USA cities: –26% more likely to die prematurely than those exposed to lower PM concentrations 6 PM10: < 10 micro meter PM2.5: < 2.5 micro meter PM1 : < 1 micro meter Images From : Sources of PM : industrial processes, motor vehicles, mining, Domestic fuel burning, Diesel exhaust, bushfires, windblown dust and salt spray from oceans

7 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

Infrastructure System – Transport Applications –Fastest route –Taxi Availability –Parking availability –Traffic route management –Driver behaviour (anomaly) 8 Road trajectory clustering Finding anomalies in traffic flow –Suspicious activity detection –Informing authorities about any anomalous activity Data (Beijing and Singapore) -_and_left-hand_traffic introduces-live-traffic-alerts-in-australia-26359

9 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

10 Tropical cyclone Hamish formed in the northern part of Australia and tracked through the main part of the reef Coming within 130 kilometres of the sensor network stations at Heron and One Tree Islands on the 9th of March Event Detection: Cyclone Hamish (March 2009) Detection Ecosystem – Great Barrier Reef - Monitoring

11 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

Emergency - Crowd Monitoring at MCG Stadium Case Study: Crowd Monitoring Analytics at MCG –100,000 people –Previously manual counting Analytics include: –Count traffic in real-time –Relationship between people traffic and area available –Predict unforeseen scenarios –Evacuation strategies in emergencies –Understanding of people’s behaviour and their movements –Automated and robust crowd controlling mechanism (close/open gates) 12 Crowd Analytics CountingDensityTracking Behaviour Instances Camera network 350 IP Cameras Industry Partners: Funding: ARC Linkage Grant (LP )

13 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

14 Community Health – Mobile Health Internet Cloud Analytics Medical Professional Mobile Kiosk Community Funding and partners: Mobile Health: Pneumonia Epilepsy Stroke Rehabilitation Aged care

15 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

Citizen Engagement – Participatory Sensing 16 Participatory Sensing: Individuals and communities use mobile phones and cloud services to collect and analyse data City of Melbourne – Open data platform –“… increase transparency, improve public services and support new economic and social initiatives.” S. Marusic, J. Gubbi, H. Sullivan, Y. W. Law, M. Palaniswami. “Participatory Sensing, Privacy, and Trust Management for Interactive Local Government”, IEEE Technology and Society Magazine, vol.33, no.3, pp.62,70, Fall Open Data: Internet of Things Innovation New Knowledge Policymaking SMEs Development Privacy Security Pedestrian Counting –28 Sensor locations –24 x 7 –Live data Live Data:

17 Infrastructure System City Environment Ecosystem Emergency & Disaster Management Community Health Citizen Engagement Particulate Matter Environment Management Environment Management Crowd Monitoring Mobile Health Participatory Sensing Participatory Sensing Smart City - Fundamental Components Transport End

Smart City, New Innovations – Better Life 18 J. Gubbi, R. Buyya, S. Marusic, M. Palaniswami, "Internet of Things (IoT): A vision, architectural elements, and future directions." Future Generation Computer Systems 29.7 (2013):