Smart City
Australia
Slaven Marusic
Department of Electrical and Electronic Engineering The University of Melbourne, Australia
ARC Research Network on Intelligent Sensors, Sensor Networks and
ISSNIP – ARC Research Network on Intelligent
Sensors, Sensor Networks and Information Processing
– Over 200 researchers
– Australia, the USA, Europe, Asia, South America
– 10 Australian universities and partner organisations
– 30+ Industry linkages
– Nationwide sensor network research infrastructure
Melbourne
ISSNIP
www.issnip.unimelb.edu.au 2
SmartSantander - Experimental testbed facility The Internet of Things Initiative (IoT-i)
Smart City Support Infrastructure
Infrastructure to underpin the IoT is being rolled out as the
government funded National Broadband Network (NBN) to deliver high speed broadband to 100% of Australian premises (93% at one gigabit per second) through a mixture of FTTH, fixed wireless and satellite links.
Target applications
telehealth services for remote communities; eLearning initiatives;
intelligent transportation; smart grids.
– The Smart Grid-Smart City Initiative
– Victoria is rolling out Zigbee enabled smart meters to all premises allowing remote metering, control, flexible tariffs and energy usage feedback for consumers.
Citizens
Healthcare triage, patient monitoring, personnel monitoring, disease spread modelling and containment - real-time health status and predictive information to assist
practitioners in the field, or policy decisions in pandemic scenarios Emergency services,
defence
remote personnel monitoring (health, location); resource management and
distribution, response planning; sensors built into building infrastructure to guide first responders in emergencies or disaster scenarios
Crowd monitoring crowd flow monitoring for emergency management; efficient use of public and retail spaces; workflow in commercial environments
Transport
Traffic management Intelligent transportation through real-time traffic information and path optimisation
Infrastructure monitoring sensors built into infrastructure to monitor structural fatigue and other
maintenance; accident monitoring for incident management and emergency response coordination
Services
Water water quality, leakage, usage, distribution, waste management
Building management temperature, humidity control, activity monitoring for energy usage management - Heating, Ventilation and Air Conditioning (HVAC)
Environment Air pollution, noise monitoring, waterways, industry monitoring
Early use case deployments
WSN parking meter systems
Public transport systems: electronic ticketing systems (Myki), real-time scheduling and time-of-arrival updates (VIcRoads; SmartBus,
TramTracker, TaxiTracker).
Highway electronic tolling systems together with traffic monitoring systems
Infrastructure monitoring: road, rail and bridge monitoring and maintenance
Consumer products and household appliances providing another medium for information
access.
• Rural and Agricultural: Livestock monitoring; intelligent irrigation control and waterway management
Research Programs
Australian Urban Research Infrastructure Network (AURIN)
– supplies aggregated datasets and information services for real time information sharing,
MUtopia
– Integrated Modelling platform
Creating Smart Cities through IoT
– ARC Linkage Project (University of Melbourne, City of Melbourne, Arup)
– ARC LIEF Project, research infrastructure (UniMelb, City of Melbourne, University of South Australia, Adelaide City Council, Deakin University, Queensland University of Technology, Queensland Department of Roads and Transport)
– Institute for a Broadband Enable Society (IBES) – “Participatory sensing - enabling interactive local governance.” (Dept of EEE and Centre for Public Policy).
Creating Smart Cities through IoT
Focus areas:
Energy efficient sensing
– Uninterrupted collection of environmental parameters such as CO2 concentration, temperature, humidity and noise levels.
Information extraction algorithms to manage spatio-temporal data Visualization strategies to aid decision making using artificial
intelligence.
Autonomic resource provisioning algorithms for supporting real-time
Case study: Noise Mapping
Exposure to excessive noise levels is known to negatively impact quality of life. These effects, though largely subjective, can be categorized as:
Annoyance (affective–emotional response) Affected concentration
Communication disturbance Sleep disruption
Some of these effects include:
stress, anxiety contributing to mental illness; pain (at 120dB); hearing damage (at 85dB); sleep disorders, hypertension; heart diseases
Noise Monitoring - Architecture
10
Noise Mapping - Results
What is the issue?
The cost of video analytic systems comes in making them robust to real world conditions that we all take for granted.
The developer needs to make the video analytic system “intelligent” enough to
handle differences in lighting, depth, position of the sun, weather, etc.
Video Analytics: Crowd Monitoring
350 Cameras Challenge: Sensing (existing infrastructure) and analytics capability Informs:
High density crowd flows Evacuation strategy and
resource deployment
Video Analytics - Objectives
Existing Surveillance Infrastructure
Designers and Consultants -
New design
Venue managers and Emergency services -
Improved crowd management Real-time analysis, and
machine learning
Develop models to
predict events based on current conditions
Use in simulation of new designs
MUtopia Integrated Modelling Platform
What would a Zero CO2 emission city look like?
Precinct Information Model BIM + GIS
CoE on Smart Cities
Vision: Technologically empower Australia to manage future urban challenges. Mission: Creation of a technological platform that closes the loop of urban design,
management and living
Mapping future scenarios Sustainable Infrastructure Design Smart Transportation Disaster Management Structural Health Monitoring Networked Sensing RFID Optical Sensors MEMS and Nano Sensors Cloud Computing and Data Management Protocols and Routing Security and Privacy Spatial Data Analysis Big-Data Analytics Unsupervised Deep Learning Spatio-temporal analysis Anomaly and event detection Participatory Sensing Interpretation and Visualization Information design Geo-referenced 3D platform 3D City visualization
SmartCities for Citizens
Case study:
Participatory sensing: Enabling interactive local governance
through citizen engagement
Focus: identify and address the key hurdles impacting the uptake of this ICT enabled capability from both citizen and government perspectives.
Aim: bridge the gap between the needs of local government to be able to deliver effective services on the basis of rich new information streams and the needs of citizens for a local environment that supports their activities.
Challenges:
(1) Citizen engagement: incentivisation, system security, privacy.
(2) Governmental requirements: Data quality, integrity and reliability is necessary to meet specific needs at different levels of government. (city planners , compliance officers, councils).
Smart City Outcome
Better City, Better Communities, Better Life
Integration of physical and virtual world
Efficient use and real-time monitoring of resources: water, energy etc Improved mobility - effective traffic congestion control
Active citizen engagement in a connected city
Enhanced quality of experience through assured public safety and liveability
Smart tools to increase productivity for business and consumers
Scalable to apply to regional, rural and underdeveloped domains that are implicitly linked to cities
The 9th International Conference on
Intelligent Sensors, Sensor Networks and Information Processing
ISSNIP 2014
Singapore, April 21-24
