The concept of "Right to be Forgotten," especially in the realm of IoT, is derived from "European Union (EU) Regulations." EU regulations emphasize individuals' right to have their personal data erased, which impacts IoT data privacy.

Rust is known for its lightweight and efficient characteristics, making it a suitable choice for resource-constrained devices like smart wearables. While Python, Java, and C are widely used, they may not be as efficient on such devices.

The primary layers of IoT architecture typically include the Application Layer, which is responsible for interacting with end-users and applications. It's where data is processed and used for various IoT applications.

RTOS stands for "Real-Time Operating System." It is an operating system designed for real-time applications where tasks have specific timing constraints.

Energy efficiency is a fundamental aspect of IoT device power management. IoT devices are often battery-powered or have limited power resources, so optimizing energy consumption is critical to prolong battery life and ensure continuous operation.

In the context of IoT (Internet of Things), edge computing involves processing data closer to the data source, often at or near the IoT devices themselves. This approach reduces latency, conserves bandwidth, and allows for real-time data analysis. Edge computing is especially useful in scenarios where immediate data processing and decision-making are critical.

Edge Computing is a critical component for seamless IoT and AI integration in edge devices. It allows processing data closer to the source, reducing latency and enhancing efficiency.

A wearable IoT device is a device that can be worn on the body and is connected to the internet to collect and transmit data. A fitness tracker is a prime example of a wearable IoT device, as it's worn on the wrist to monitor health and activity data like steps, heart rate, and sleep patterns.

After defining objectives in an IoT project like this, the next crucial step is data collection and sensor deployment, as this is essential to gather the necessary data for predicting maintenance needs accurately.

The Raspberry Pi supports programming in Python, which is one of the most commonly used languages for developing applications on this platform. While other languages like C# and Ruby can be used on the Raspberry Pi, Python is particularly popular due to its extensive support and libraries.