IEEE 4th World Forum on Internet of Things
05-08 February 2018 – Singapore

Distinguished Speakers

Sonia Aplin, Vice President, Head of Marketing, Communications and Sustainability and Corporate Responsibility, Ericsson South East Asia, Oceania and India

Sonia AplinAs Vice President and Head of Marketing, Communications and Sustainability and Corporate Responsibility (SCR), for Ericsson South East Asia, Oceania and India, Sonia Aplin has responsibility for the execution of Ericsson’s SCR strategy as well as the building and management of Ericsson’s brand positioning.

Ericsson’s SCR activities in this region includes the deployment of the company’s largest Connect to Learn project. The project enables 21,000 students in Myanmar to experience a 21st century education through internet access, devices, specialized content and teacher training. Another initiative includes the world-first Connected Mangroves project. Recognized in the 2016 UN Momentum for Change Awards, this project combines cloud, machine-to-machine and mobile broadband to help the local community of Selangor better manage the growth of new mangrove saplings – a vital part of Malaysia’s ecosystem.

Prior to joining Ericsson, Sonia worked across several industries including healthcare, not-for-profit and finance. She holds a Masters in Communications and a Bachelor of Arts (Journalism), both from Australia.

Presentation: Telecommunications and connectivity as the keystone in crisis response

Based on Ericsson Response’s 16 years of experience, telecommunications and connectivity play a crucial role in the management of all crises.  Ericsson Response is a volunteer initiative that deploys around 140 trained volunteer employees and telecom equipment to support the UN and other humanitarian organizations in times of disaster and crisis.  The Ericsson Response team’s main tasks are to set up mobile networks for voice and data communication as well as supporting partners in training and knowledge sharing. We will share how Ericsson Response was able to provide communications expertise, equipment and resources in more than 40 relief efforts in more than 30 countries.

We will also discuss how Ericsson Response is helping to transform emergency response, by working with aid agency partners including the UN Office for the Coordination of Humanitarian Affairs (OCHA), the UN World Food Programme (WFP), the UN High Commissioner for Refugees (UNHCR), UNICEF and others.

Some of the largest deployments we have had to date include supporting over 90 humanitarian sites, including community care centers and Ebola treatment units, in Sierra Leone, Guinea, and Ghana; supporting the Philippines when super typhoon Haiyan devastated a large part of the country and helping in the aftermath of recent hurricanes in the US and Caribbean.

Greg Foliente, University of Melbourne

Greg FolienteProf. Greg Foliente is an Enterprise Professor at the University of Melbourne and the Manager of its Centre for Disaster Management and Public Safety (CDMPS). He leads interdisciplinary and transdisciplinary research, education, consulting and collaboration initiatives that advance innovation in the built environment and urban systems sectors, with a primary focus towards improved sustainability, liveability and resilience. He has an International reputation in diverse areas that include engineering safety and performance assessment under extreme events, quantitative risk analysis and system reliability, disaster mitigation, socio-economic impacts and resilient design, spatial diffusion of technology and innovation, sustainability and more recently, community wellbeing and resilience. He is a strategic leader and facilitator, with a number of internationally recognised achievements and successful projects, including those undertaken with UN agencies, the World Bank, AusAID and various Australian federal and state agencies. He has an extensive and diverse scholarly publications record, has received numerous international honours and awards and appointments in important scientific committees and positions. For further details, see:

Presentation:  Black Swans, Perfect Storms and Cascading Failures: Emerging R&D challenges in infrastructure systems analysis, disaster resilience and the assessment of socioeconomic impacts of failure in extreme events

Global trends towards higher concentrations of population and economic activities in urban mega-centres have brought increasing complexity and infrastructure interdependencies in the delivery of critical urban services such as energy, water, transport and communication. This presentation identifies critical research and development challenges from the perspective—and for the benefit—of key stakeholders, considering their primary decision goals and context. From this vantage point, the critical evaluation framework is extended to include a classification of disruptions and extreme events and an overview of infrastructure modeling approaches and broader socioeconomic impacts assessment methods. Mapping the range of modeling and assessment methods against different decision contexts, critical gaps in knowledge and tools are identified to support the latter. Deep uncertainties characterize the challenge as each major component in the information and decision-making chain—from the frequency and intensity of a disruptive event, to assessing the first-order and immediate impacts of an infrastructure failure, to estimating the nature, extent and impact of cascading failures—multiplies the uncertainties. The emerging research challenges to deal with these interdependencies and uncertainties are explored.

Neil Gordon, Defence Science and Technology Group

Neil Gordon received a PhD in Statistics from Imperial College London in 1993. He was with the Defence Evaluation and Research Agency in the UK from 1988-2002 working on missile guidance and statistical data processing. In 2002 he moved to the Defence Science and Technology Group in Adelaide, Australia where he is currently head of Data and Information Fusion. In 2014 he became an honorary Professor with the School of Information Technology and Electrical Engineering at the University of Queensland. He is the co-author/co-editor of two books on particle filtering and one on the search for MH370.

Presentation: The search for MH370

On 7th March 2014 Malaysian Airlines flight MH370 from Kuala Lumpur to Beijing lost contact with Air Traffic Control and was subsequently reported missing. An extensive air and sea search was made around the last reported location of the aircraft in the Gulf of Thailand without success. Signals transmitted by the aircraft’s satellite communications terminal to Inmarsat’s 3F1 Indian Ocean Region satellite indicated that the aircraft continued to fly for several hours after loss of contact. In this talk I will describe how nonlinear/non-Gaussian Bayesian time series estimation methods have been used to process the Inmarsat data and produce a probability distribution of MH370 flight paths that defined the search zone in the southern Indian Ocean. I will describe how probabilistic models of aircraft flight dynamics, satellite communication system measurements, environmental effects and radar data were constructed and calibrated. A particle filter based numerical calculation of the aircraft flight path probability distribution will be outlined and the method is demonstrated and validated using data from several previous flights of the accident aircraft. A short book is freely available for download from

Ged Griffin, Victoria Police Australia

Ged GriffinGed Griffin, Inspector with Victoria Police Australia and currently a PhD Candidate at the University of Melbourne where he is researching the next generation of emergency management. He holds a Master of Arts (Police Practice), a Master of Professional Education and Training and a number of subordinate degrees. He has been a police officer for 28 years where he has performed duties in general duties, emergency management, marine policing, criminal investigations, intelligence and counter terrorism operations. He has also performed a wide range of roles in East Timor including duties at the UN Serious Crimes Unit, Victoria Police Contingent Commander and as Liaison Officer supporting the former Victorian Premier the Hon Mr Steve Bracks during his work assisting Xanana Guasmao and the new government of East Timor. He is a member of the Australian Civil Corps and has been appointed as the Team Leader for the Post Disaster Response Team. He is currently an Inspector in the State Emergency Response Coordination Division at the Victoria Police Force.

Presentation:  Public Safety Mobile Broadband – To bravely go where no one has gone before

Abstract coming soon.

Marimuthu Swami Palaniswami, Professor of Electrical Engineering, University of Melbourne and Director/Convener Sensor Networks and Information Processing (ISSNIP)

Marimuthu Swami PalaniswamiMarimuthu Palaniswami is a Fellow of IEEE and a distinguished lecturer of the IEEE Computational Intelligence Society. He received his Ph.D from the University of Newcastle, Australia before joining the University of Melbourne, where he is a Professor of Electrical Engineering and Director/Convener of a large ARC Research Network on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP) with about 100 researchers on various interdisciplinary projects. Previously, he was a Co-Director of Centre of Expertise on Networked Decision & Sensor Systems. He served in various international boards and advisory committees including a panel member for National Science Foundation (NSF). He has published more than 450 refereed journal and conference papers, including 3 books, 10 edited volumes.

He was given a Foreign Specialist Award by the Ministry of Education, Japan in recognition of his contributions to the field of Machine Learning and communications. He received University of Melbourne Knowledge Transfer Excellence Award and Commendation Awards. He served as associate editor for Journals/transactions including IEEE Transactions on Neural Networks, Computational Intelligence for Finance. He is editor of Journal of Medical, Biological Engineering and Computing and the Subject Editor for International Journal on Distributed Sensor Networks. Through his research, he supported various start-ups, local and international companies.

As an international investigator, he is involved in FP6, FP7 and H2020 initiatives in the areas of smart city and Internet of Things (IoT). In order to enhance outreach research capacity, he founded the IEEE international conference series on sensors, sensor networks and information processing and served as General Chair for over 15 IEEE and IEEE sponsored Conferences. He has given several keynote/plenary talks in the areas of sensor networks, IoT and machine learning. His research interests include Smart Sensors and Sensor Networks, Machine Learning, IoT and Biomedical Engineering and Control.

Presentation: Real-time Crowd Behavior Analysis for Public Safety Using Networked Cameras and Cloud Analytics

With increasing population and human activities, it has become essential to monitor public places for effective disaster management. Anomalous events may include a person loitering about a place for unusual amounts of time; people running and causing panic; the size of a group of people growing over time at a particular point of entry or exit etc. A stadium like Melbourne Cricket Ground (MCG) which can accommodate nearly 100,000 spectators for any sporting event, can cause people to panic and break out commotion. It will be a daunting task to control crowd. Hence, continuous monitoring of the behavior of the people moving within the limits of stadium is of utmost importance.

Automated detection of such anomalous crowd behavior is still a challenge, given the enormous amount of computation and detection challenges in detecting objects, tracking, and analyzing video in real-time.  Current systems offer limited functionality, particularly in their reliance on centralized processing of gathered information.  However, the prevalence of camera networks for surveillance, together with the decreasing cost of infrastructure, has produced a significant demand for robust monitoring systems.

This talk addresses end-to-end system challenges of camera networks, integrating cameras across the spatial, spatiotemporal and decision domains. The talk highlights the nature and complexity of algorithms to monitor MCG (350 networked IP cameras) to deliver unique long-term behavior analysis in highly crowded environments. It highlights the video analytics capabilities to count people, track, and detect suspicious behavior, suitable for crowd management, modelling, and urban planning. It also provides automated analysis of such behaviors to detect and alert the anomalous crowd behavior in almost real-time, which is a necessity for safety and security public using Internet of Things (IoT).

Yu-Hsing Wang, Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology (HKUST)

Dr. Yu-Hsing Wang received his B.S. and M.S. degrees in Civil Engineering from National Taiwan University and a Ph.D. in Civil Engineering from Georgia Institute of Technology where he received the George F. Sowers Distinguished Graduate Student Award for Ph.D. Students. Currently, he is a Professor at the Department of Civil and Environmental Engineering and director of Data-Enabled Scalable Research (DESR) Laboratory, HKUST. The DESR Lab is a physical Makerspace, specialized in the applications of Geotechnical Internet of Things (Geo-IoT), Big Data Analytics, and Deep Learning on sustainable urban development and city resilience. The DESR Lab is also an open platform for geotechnical academics and practitioners to collaborate and share resources. His research interests include innovative wave-based characterizations of geomaterials (using mechanical and electromagnetic waves), applications of 3D printing techniques on innovation of geotechnical testing devices and sensing techniques, development and applications of Smart Soil Particle sensors (OpenSSP), applications of geotechnical internet of things (GeoIoT), Big Data analytics, and deep learning on geotechnical engineering, health monitoring and predictive maintenance. In 2005, he received the ASTM International Hogentogler Award. In 2008 and 2017, he received the School of Engineering Teaching Award, HKUST. In 2013, he received the Distinguished Alumni Award from the Department of Civil Engineering, National Taiwan University. He has been invited for Keynote and theme lectures in the internal conferences and served as an associated editor and editorial board member in different journals.

Presentation: A Real-time and Long-term Scalable IoT-AI Stack for Natural Hazard Resiliency Assessment and Management of Critical Infrastructure

Lifelines and critical infrastructure will be exposed to higher risks of degradations, damages or failures in the coming decades as unprecedented larger scales of typhoons and extreme precipitations are becoming a norm. Such challenging times call for data-enabled decision making through constant monitoring in order to carry out timely maintenance and upgrade works of the lifelines and critical infrastructure. Predictive maintenance of critical infrastructure relies heavily on large-scale and long-term monitoring, particularly vibrations at different parts of the structural elements. In this talk, we will showcase how we build a realtime, long-term scalable operational IoT stack for low-cost dynamic monitoring with reference to our live landslide monitoring operations in Taiwan and Hong Kong since 2014. Linear scalability is the core design principle of the IoT stack as both cost-effectiveness and performance are the major reasons why we stop short of widespread and continuous dynamic monitoring. We then discuss how we deploy AI – deep learning – on these large-scale dynamic observations pouring in by a second for real-time anomaly detections and classifications. With the entire IoT-AI stack facilitating real-time data discovery, evaluations and disseminations of the dynamic performances of the lifelines and critical infrastructure, efficient decision-making and resource allocation through predictive maintenance is now possible.

Keywords: IoT, AI, critical infrastructure, predictive maintenance, natural hazard, dynamic monitoring