Mobile Drone Computing
Luca Mottola, Politecnico di Milano, Italy
Security and Privacy Challenges for the Internet of Things
Biplab Sikdar, University of Singapore, Singapore
Scene Understanding in Emergency Applications: Challenges and Lessons Learnt
Niki Trigoni, University of Oxford, United Kingdom
Mobile Drone Computing
Luca Mottola
Politecnico di Milano
Italy
Brief Bio
Luca Mottola is an Associate Professor at Politecnico di Milano (Italy) and a Senior Researcher at RI.SE Sweden. His lab focuses on modern networked embedded systems, including intermittent computing, mobile embedded computing, Internet-connected robotics, and low-power wireless. To date, he is the only European researcher to be granted multiple times with the ACM SigMobile Research Highlight and to ever win Best Paper Awards at multiple flagship conferences of both ACM SigMobile and ACM SigBed. He is General Chair for ACM/IEEE CPS-IoT Week 2022 and past PC chair for ACM MOBISYS, ACM SENSYS, ACM/IEEE IPSN, and EWSN. He is a Google Faculty Award winner and an associate editor of IEEE Transactions on Mobile Computing, ACM Transactions on Sensor Networks, and Elsevier Computer Networks. He holds or held visiting positions at Uppsala University, NXP Technologies, TU Graz, and USI Lugano.
Abstract
Autonomous drones are emerging as a powerful new breed of mobile sensing platform. Small embedded computers that move almost unconstrained while carrying rich sensor payloads, such as cameras and microphones, bring sensing where no other technology can reach. Notwithstanding recent advancements, the current use of drone technology is often limited to manual control of individual devices by skilled individuals. The gap between this and large-scale autonomous operation remains significant. The challenges span diverse disciplines, from computer science and engineering up to regulatory and legal aspects. In this talk, we discuss the research efforts we are carrying out to overcome some of these challenges. Our work includes programming and operating systems, flight control, as well as realistic experimentation and is constantly fed by real-world deployments we carry out in a range of application domains, including aerial photogrammetry and 3D reconstruction.
Security and Privacy Challenges for the Internet of Things
Biplab Sikdar
University of Singapore
Singapore
Brief Bio
Biplab Sikdar is an Associate Professor in the Department of Electrical and Computer Engineering at the National University of Singapore where he also serves as the Vice Dean in the Faculty of Engineering. He received the B. Tech. degree in electronics and communication engineering from North Eastern Hill University, Shillong, India, in 1996, the M.Tech. degree in electrical engineering from the Indian Institute of Technology, Kanpur, India, in 1998, and the Ph.D. degree in electrical engineering from the Rensselaer Polytechnic Institute, Troy, NY, USA, in 2001. His research interests include IoT and cyber-physical system security, network security, and network performance evaluation. He is a recipient of the NSF CAREER award, the Tan Chin Tuan fellowship from NTU Singapore, the Japan Society for Promotion of Science fellowship, and the Leiv Eiriksson fellowship from the Research Council of Norway. Dr. Sikdar is a member of Eta Kappa Nu and Tau Beta Pi. He served as an Associate Editor for the IEEE Transactions on Communications from 2007 to 2012 and as an Associate Editor for the IEEE Transactions on Mobile Computing from 2014-2017. He received the best paper award from IEEE GLOBECOM (2007) and the IEEE Consumer Electronics Magazine (2020).
Abstract
The Internet of Things (IoT) represents a great opportunity to connect people, information, and things, which will in turn cause a paradigm shift in the way we work, interact, and think. The IoT is envisioned as the enabling technology for smart cities, power grids, health care, and control systems for critical installments and public infrastructure. This diversity, increased control and interaction of devices, and the fact that IoT systems use public networks to transfer large amounts of data make them a prime target for cyber attacks. In addition, IoT devices are usually small, low cost and have limited resources. Therefore, any protocol designed for IoT systems should not only be secure but also efficient in terms of usage of chip area, energy, storage, and processing. This presentation will start by highlighting the unique security requirements of IoT devices and the inadequacy of existing security protocols and techniques of the Internet in the context to IoT systems. Next, we will focus on security solutions for the IoT, with special focus on protection against physical and side channel attacks. In particular, we will focus on mutual authentication protocols for IoT devices based on security primitives that exploit hardware level characteristics of IoT devices.
Scene Understanding in Emergency Applications: Challenges and Lessons Learnt
Niki Trigoni
University of Oxford
United Kingdom
Brief Bio
Niki Trigoni is Professor at the Oxford Department of Computer Science, heading the Cyber Physical Systems Group. Her interests lie in the tight integration of sensing and machine intelligence for context inference, control and human-machine interaction. She has applied her work to a number of application scenarios, including mobile autonomy, asset monitoring, and localisation systems for emergency situations, as well as workforce safety and efficiency. Trigoni has founded and served from 2014-2019 as Director of the Centre for Doctoral Training on Autonomous and Intelligent Machines and Systems. Driven by her passion for research translation, in 2015, she founded Navenio Ltd, a deep tech Oxford spinout on infrastructure free indoor positioning, and a 2020 KPMB Best British Tech Pioneer. In 2020, she won the CTO of the Year award at the UK's Women in IT Awards, demonstrating impact from translating positioning tech to improve efficiency in the healthcare sector.
Abstract
Emergency situations present some of the most challenging and unusual scenarios for sensing and scene understanding; yet, it is in these situations, where situation awareness is of paramount importance and where technology is needed the most to help protect human lives. In this talk, I will present some of the key challenges faced by sensing and machine learning algorithms in emergency situations, including lack of pre-installed sensing infrastructure, lack of training data, sensor failure, and limited visibility and connectivity. I will then present recent research directions that we have pursued to address these challenges including multi-modal sensing, cross modality training and human-robot interaction.