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Distributed and Adaptive Edge-based AI Models for Sensor Networks (DAISeN)

Date
2022
Academic Conference
IoT-ECAW: 6th Workshop on Internet of Things - Enablers, Challenges and Applications
Authors
Veselka Boeva (Blekinge Institute of Technology)
Emiliano Casalicchio (Blekinge Institute of Technology)
Shahrooz Abghari (Blekinge Institute of Technology)
Ahmed Abbas Mohsin Al-Saedi (Blekinge Institute of Technology)
Vishnu Manasa Devagiri (Blekinge Institute of Technology)
Andrej Petef (Sony Europe, B.V.)
Peter Exner (Sony Europe, B.V.)
Anders Isberg (Sony Europe, B.V.)
Mirza Jasarevic (Sony Europe, B.V.)
Research Areas
AI & Machine Learning

Abstract

This position paper describes the aims and preliminary results of the Distributed and Adaptive Edge-based AI Models for Sensor Networks (DAISeN)1 project. The project ambition is to address today’s edge AI challenges by developing advanced AI techniques that model knowledge from the sensor network and the environment to support the deployment of sustainable AI applications. We present one of the use cases being considered in DAISeN and review the state-of-the-art in three research domains related to the use case presented and directly falling into the project scope. We additionally outline the main challenges identified in each domain. The developed Global Navigation Satellite Systems (GNSS) activation model addressing the use case challenges is also briefly introduced. The future research studies planned for the remaining period of the project are finally outlined.

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