Announcement: IPSN 2021 will be virtual
The COVID-19 pandemic has imposed unprecedented changes in our lives. After much consideration, we have taken the decision to organize IPSN 2021 in an entirely virtual format. Please, stay tuned for details.
The ACM/IEEE Information Processing in Sensor Networks (IPSN) 2021 conference welcomes exciting demonstrations of novel technologies, applications, and hardware as well as posters showing promising early work. We seek participation from both industry and academia for demonstrations and posters. The selection will be based on a short abstract, evaluated based on technical merit and innovation as well as the potential to stimulate interesting discussions and exchange of ideas at the conference.
The demo and poster session is a great forum to share your early-stage work with a broader audience. Accepted abstracts will appear in the regular conference proceedings. At least one author of every accepted demonstration or poster abstract is required to register and participate in the conference.
We welcome all topics that align with the IPSN conference topics of interest. More detailed information about this may be found here.
- Multiple Event Detection using Minimum Inputs
Shashini Wanniarachchi, Jens Dede, Anna Förster (University of Bremen, Germany)
- Protecting User Data Privacy with Adversarial Perturbations
Ziqi Wang, Brian Wang, Mani Srivastava (University of California, Los Angeles, USA)
- Game-Theoretic Optimization of the TSCH Scheduling Function for Low-Power IoT Networks
Omid Tavallaie (The University of Sydney, Australia), Javid Taheri (Karlstad University), Albert Zomaya (The University of Sydney, Australia)
- Low-Cost, Perspective Invariant and Personalized Thermal Comfort Estimation
Peter Wei, Yanchen Liu, Xiaofan Jiang (Columbia University, USA)
- User Identification Across Multiple Smart Pill Bottle Systems
Murtadha Aldeer, Richard Howard, Richard P. Martin, Jorge Ortiz (Rutgers University, USA)
- Improving Acoustic Detection and Classification in Mobile and Embedded Platforms
Stephen Xia, Xiaofan Jiang (Columbia University, USA)
- Non-parametric Bayesian Learning for Newcomer Detection using Footstep-Induced Floor Vibration
Yiwen Dong (Stanford University, USA), Jonathon Fagert (Carnegie Mellon University, USA), Pei Zhang (University of Michigan, USA), Hae Young Noh (Stanford University, USA)
- Detecting Human-Induced Changes in Powerline Signals: A Human Sensing System Design
Tian Zhou, Lin Zhang (Tsinghua University, China)
- Are Android Malware Detection Models Adversarially Robust?
Hemant Rathore (Birla Institute of Technology and Science, India), Sanjay K. Sahay (Birla Institute of Technology and Science, India), Mohit Sewak (Microsoft R&D, India)
- A Multi-source Unsupervised Domain Adaptation Method for Wearable Sensor based Human Activity Recognition
Baiqiang Zhang (Harbin Institute of Technology, China), Rong Zheng (McMaster University, Canada), Jie Liu (Harbin Institute of Technology, China)
- VoiSense: Harnessing Voice Interaction on a Smartwatch to Collect Sensor Data
Sirat Samyoun, John Stankovic (University of Virginia, USA)
- Hands-On IoT Education with Mobile Devices
Devin Jean, Gordon Stein, Ákos Lédeczi (Vanderbilt University, USA)
- Distributed Virtual CPS Environment for K12
Gordon Stein, Devin Jean, Ákos Lédeczi (Vanderbilt University, USA)
- A Novel Architecture for Semi-Active Wake-Up Radios Attaining Sensitivity Beyond -70 dBm
Giannis Kazdaridis, Nikos Sidiropoulos, Ioannis Zografopoulos, Thanasis Korakis (University of Thessaly, Greece)
If you have any questions, please contact the posters and demo chairs:
|Olga Saukh Graz University of Technology|
|Alberto Cerpa University of California, Merced|
|Péter Völgyesi Vanderbilt University|
|Luca Mottola Politecnico di Milano, Italy and RI.SE, Sweden|