With the massive amount of data produced by ambient environmental sensors, many AI-based solutions are emerging to support new smart cities’ applications. However, these data may contain sensitive personal information, calling for responsible AI solutions. FBK proposes a privacy-preserving subsystem with a set of technological components that enable responsible AI and prevent unauthorised usage of personal data at the data storage and during data transmission under the context of Smart Cities. We demonstrate the proposed solution under an EU project MARVEL, where both video and audio anonymisation components are deployed at the edge level, enabled by a model compression component for complexity reduction. We discuss each component’s technical challenges, current progress, and future directions.

Responsible AI at the edge: towards privacy-preserving smart cities

Luca Zanella;Yiming Wang;Nicola Dall’Asen;Alberto Ancilotto;Francesco Paissan;Elisa Ricci;Elisabetta Farella;Alessio Brutti;Marco Pistore
2022-01-01

Abstract

With the massive amount of data produced by ambient environmental sensors, many AI-based solutions are emerging to support new smart cities’ applications. However, these data may contain sensitive personal information, calling for responsible AI solutions. FBK proposes a privacy-preserving subsystem with a set of technological components that enable responsible AI and prevent unauthorised usage of personal data at the data storage and during data transmission under the context of Smart Cities. We demonstrate the proposed solution under an EU project MARVEL, where both video and audio anonymisation components are deployed at the edge level, enabled by a model compression component for complexity reduction. We discuss each component’s technical challenges, current progress, and future directions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11582/331374
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