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.