tinyML for crime prevention: detecting violent conversations

Anwar, A ORCID: https://orcid.org/0000-0001-5347-4996 and Kanjo, E ORCID: https://orcid.org/0000-0002-1720-0661, 2023. tinyML for crime prevention: detecting violent conversations. Nottingham: Nottingham Trent University.

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Abstract

Our work focuses on using tinyML for detecting violent language on edge devices, such as mobile phones and wearables, in the context of preventing domestic violence. Our multimodal algorithm uses natural language processing (NLP) and audio processing to detect violent conversation from short audio-text segments. The algorithm is converted to a tinyML model using TensorFlow Lite, which enables the detection to run on edge devices such as mobile phones and smart home sensors. Our mobile application enables near-real-time detection of violent conversations to enable victims or potential victims to detect and report crimes to close or trust contacts.

Item Type:	Working paper
Creators:	Anwar, A. and Kanjo, E.
Publisher:	Nottingham Trent University
Place of Publication:	Nottingham
Date:	25 June 2023
Identifiers:	Number Type 1795526 Other
Divisions:	Schools > School of Science and Technology
Record created by:	Jonathan Gallacher
Date Added:	29 Aug 2023 15:50
Last Modified:	29 Aug 2023 15:50
URI:	https://irep.ntu.ac.uk/id/eprint/49623

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