IEEE PerCom 2021

First IEEE International Workshop on Deep Learning in Pervasive Computing (PerDL)

March 22nd, 2021, FULL VIRTUAL


Monday, March 22 8:45 - 10:30

S1: Intelligence to the edge of the networks

Chair: Riccardo Pecori (University of Sannio, Italy)

Keynote: Edge Intelligence - Emerging Solutions and Open Challenges

Mario Luca Bernardi (2Research Centre on Software Technology (RCOST), University of Sannio, Italy)

LAMBDA: An Open Framework for Deep Neural Network Accelerators Simulation

Enrico Russo (Università di Catania, Italy); Maurizio Palesi (University of Catania, Italy); Salvatore Monteleone (University of Enna, KORE, Italy); Davide Patti, Giuseppe Ascia and Vincenzo Catania (University of Catania, Italy)

Keyword Spotting for Industrial Control Using Deep Learning on Edge Devices

Fabian Hölzke and Hameem Ahmed (University of Rostock, Germany); Frank Golatowski (University of Rostock & Institute of Apllied Microelectronics and Computer Engineering, Germany); Dirk Timmermann (University of Rostock, Germany)

Monday, March 22 11:00 - 12:00

S2: Intelligence in IoT and mobile devices

Chair: Marta Cimitile (Unitelma Sapienza University, Italy)

Keynote: ARES: A Deep Reinforcement Learning Tool for Black-Box Testing of Android Apps

Andrea Romdhana (University of Genoa, Italy); Alessio Merlo (DIBRIS - University of Genoa, Italy)

Keynote: Intelligent IoT Architectures to Support Distributed Cognitive Applications

Marco Picone (University of Modena and Reggio Emilia, Italy)

Monday, March 22 12:00 - 12:35

S3: Explainable Deep Learning and conclusions

Chair: Riccardo Pecori (University of Sannio, Italy)

Keynote: Explainable-By-Design Deep Learning

Plamen Angelov (Lancaster University, United Kingdom (Great Britain))

The IEEE PerDL workshop aims to address all relevant technologies, researches and discoveries in the field of distributed and pervasive Deep Learning (DL) techniques. The usage of deep learning techniques is becoming more and more widespread and needs to be properly incorporated into pervasive and distributed computing and communication architectures, in order to foster a fully connected environment of intelligent systems. The great development of Internet of Things devices and applications is fostering more and more pervasive communication paradigms, but smart devices and gateways need further capabilities to become fully connected intelligent things. What is still lacking is an in-depth study of the modalities and technologies to properly integrate all deep learning aspects and algorithms in all possible distributed and pervasive systems, making them actual intelligent distributed systems. The main aim is to support fast and on-the-field DL-based computations that may foster novel and fast services in the near future contexts, such as smart cities, smart agricultures, smart health, smart distance education, smart automotive, industry 4.0, and many more. On the other hand, DL could help in finding out better distributed and parallel configurations to increase the performance of pervasive computing itself.

The objective of the PerDL workshop is to encourage the integration between the distributed and pervasive computing community and the deep artificial neural network community. This with the aim to foster the development of more and more widespread deep learning techniques in all computing and communication systems, as well as to increase pervasive computing performance by means of deep learning strategies.

Contact Email: rpecori [at]