Edge AI and TinyML: Enabling Intelligent Systems at the Edge
Artificial Intelligence has traditionally relied on centralized cloud infrastructures for data processing and model inference. However, this architecture poses challenges, including latency, privacy concerns, and network dependency. Edge AI addresses these issues by performing AI computations on edge devices like smartphones, sensors, and microcontrollers. TinyML is a subset of Edge AI that focuses specifically on the deployment of machine learning algorithms on ultra-low-power microcontrollers.
Institutions
- State University of Semarang (ID)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-07
- DOI
- https://doi.org/10.5281/zenodo.15358169
- Primary Topic
- IoT and Edge/Fog Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00