[1] TINY ML MEETS EDGE AI: INNOVATIONS IN EMBEDDED AI FOR IOT AND SMART SYSTEMS: ARTICLE INFO: Date of Submission: Mar 9, 2026, Revised: Mar 21, 2026, Accepted: Apr 1 , 2026, CrossRef d.o.i : https://doi.org/10.56815/ijmrr.v5i4.2026.1-15. HOW TO CITE: Reena (2026). Tiny ML Meets Edge AI: Innovations in Embedded AI for IoT and Smart Systems. International Journal of Multidisciplinary Research & Reviews. 5(4). 1-15.

Reena

Authors

Reena Assistant Professor, Dept. of Computer Science, Guru Nanak Govt. College, G.T.B. Garh, Moga, Punjab, India.

Abstract

Tiny ML and Edge AI are changing the IoT and smart devices and embedded systems by making it possible to perform real-time ondevice decision-making. These technologies enable devices to do the processing locally and limit dependence on the cloud-based system, minimize latency, as well as, increase privacy and security. TinyML allows devices with limited resources to perform intelligent tasks in IoT applications, which do not need high-level computation power.This review discusses how Edge AI combined with TinyML is
transforming such sectors as autonomous vehicles, smart cities, healthcare and industrial automation. We talk about energy-saving
algorithms, low-latency usage, and scalable designs and such issues as memory constraints, power usage, and data privacy. Future
research in the areas of federated learning, hardware-software co design and on-device learning is also mentioned in the paper. In the
IoT ecosystem, Tiny ML and Edge AI together are laying the groundwork for increasingly independent, effective, and intelligent systems.