The rapid emergence of Internet of Things (IoT) devices has dramatically transformed modern society. Recently, with the rapid development of Artificial Intelligence (AI) and the Internet of Things (IoT), their combination, i.e., the Artificial Intelligence of Things (AIoT), is emerging. The broad penetration of IoT devices in consumer market enables unprecedented sensing capabilities by providing fine-grained, heterogeneous and temporal data. By exploring the enriched data generated by IoT devices, numerous AIoT applications ranging from smart homes and smart vehicles to large-scale smart cities and smart factories are being developed. However, the current AIoT applications are subject to a variety of limitations including resource-constrained devices, energy-efficient communication/computing, data privacy, and small sample problem, etc. With the broad application of deep learning (DL) algorithms, the fusion of DL and IoT (DL-IoT) is on the rise to address the aforementioned challenges.
We are organizing DL-IoT at ICDM 2020, to be held in Sorrento, Italy, on November 17 2020. The workshop’s primary goal is to examine the potential challenges of deep learning algorithms in the IoT era, and to explore advanced deep learning algorithms and edge intelligence for IoT applications. This workshop will provide an interactive forum for discussion on recent and ongoing developments, key issues and challenges, and practices related to deep learning for Internet of Things. We welcome contributions within a broad range of AIoT and DL-IoT.
Topics of Interest
This workshop will provide an interactive forum for discussion on recent and ongoing developments, key issues and challenges, and practices related to DL-IoT. Researchers and practitioners from academia, industry, and government are invited to present their work and perspectives and participate in the workshop.
Topics of interest include, but are not limited to:
- Deep learning for IoT and industrial IoT
- Distributed learning in IoT
- Edge intelligence for IoT
- Cross-domain knowledge transfer in IoT
- Advanced deep learning for the security issues in IoT
- Energy-efficient deep learning algorithms for IoT
- Advanced deep learning for big data and streaming analytics in IoT
- Novel applications of deep learning in smart home, smart city, smart transportation, business, and smart factory