SPAWC21 is hosting two dataset competitions which focus on robust and accurate localization for Industry 4.0 and rapid wideband spectral awareness for efficient spectrum access, monitoring, and coordination in communications systems. Both of these challenges are positioned at the intersection of wireless communications and machine learning, and introduce unique new challenges which build on developing areas of research and development to challenge the academic and industry community with increasingly cross-domain and difficult operating assumptions which are faced in real world operating conditions.
For any information, please contact the Data Competition Organizers:
Challenge #1 focuses on Industry 4.0 centric robust and versatile positioning of robotic devices using a combination of Camera-based, IMU-Based and ultra-wideband (UWB) based data observations requiring the fusion of multiple domains of observation to maximize precision. As robust and precise radio emitter localization is a key component in future industry and factory applications, we are excited to launch this data-driven challenge as part of SPAWC21.
Kaggle link: https://www.kaggle.com/c/ieeespawc21localization/
Challenge #2 focuses on rapid spectrum awareness and signal recognition to enabled radio spectrum access coordination, anomaly detection, spectrum sharing, and monitoring applications. As real-time spectrum awareness and spectrum aware decision making may be key components to beyond-5G communications systems, we are excited to launch this data-driven competition as part of SPAWC this year to compare and contrast promising approaches.
We are soliciting both Kaggle competitors to compete using their best algorithms and approaches to each of these challenges alongside full papers submissions describing algorithmic approaches to each challenge as submissions to the workshop.
Full papers must be submitted until July 5, 2021 in PDF format (see formatting instructions below).
Algorithm competition submissions may be submitted via Kaggle above.