Tiny machine learning (TinyML) is a new field aimed at miniaturizing machine learning algorithms to the point that app developers can integrate them into IoT devices. Since TinyML delivers AI capabilities to embedded devices, it is also known as edge AI or embedded AI. TinyML allows bringing AI to devices like smartphones, tablets et al., too. Since these mobile devices have currently surpassed desktop computers as the primary computing device for most users, it allows the possibility to engage even more end-users in crowdsourcing data for the IoT world. In this chapter, we will review the current status of TinyML by illustrating its underlying technologies and methodologies and showing some relevant examples where this new area is being used to provide novel applications, thanks to crowdsourcing as a way to engage the final user.

Crowdsourcing Through TinyML as a Way to Engage End-Users in IoT Solutions / Manzoni P.; Zennaro M.; Ahlgren F.; Olsson T.; Prandi C.. - ELETTRONICO. - 1100:(2023), pp. 359-385. [10.1007/978-3-031-32397-3_14]

Crowdsourcing Through TinyML as a Way to Engage End-Users in IoT Solutions

Prandi C.
Ultimo
2023

Abstract

Tiny machine learning (TinyML) is a new field aimed at miniaturizing machine learning algorithms to the point that app developers can integrate them into IoT devices. Since TinyML delivers AI capabilities to embedded devices, it is also known as edge AI or embedded AI. TinyML allows bringing AI to devices like smartphones, tablets et al., too. Since these mobile devices have currently surpassed desktop computers as the primary computing device for most users, it allows the possibility to engage even more end-users in crowdsourcing data for the IoT world. In this chapter, we will review the current status of TinyML by illustrating its underlying technologies and methodologies and showing some relevant examples where this new area is being used to provide novel applications, thanks to crowdsourcing as a way to engage the final user.
2023
Wireless Networks (United Kingdom)
359
385
Crowdsourcing Through TinyML as a Way to Engage End-Users in IoT Solutions / Manzoni P.; Zennaro M.; Ahlgren F.; Olsson T.; Prandi C.. - ELETTRONICO. - 1100:(2023), pp. 359-385. [10.1007/978-3-031-32397-3_14]
Manzoni P.; Zennaro M.; Ahlgren F.; Olsson T.; Prandi C.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/963650
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