The evolution of the Internet of Things is primarily attributed to advancements in wireless communication technologies. Wireless networks, including Wi-Fi, cellular, and low-power protocols, have played a crucial role in enabling the connectivity of a wide range of IoT devices.

In addition to Secure Boot, Intrusion Detection is an important security layer. It monitors the system for any unauthorized access or tampering, providing an additional level of security to ensure device integrity. Device Authentication and Secure Enclave serve other security functions.

The use of IoT in predicting machinery failure in industries based on real-time data is known as "Condition Monitoring." IoT sensors and data analytics are employed to continuously monitor the condition of machinery and equipment to predict when maintenance or repairs are needed, ultimately improving efficiency and reducing downtime.

In IoT architecture, the component that facilitates communication between the device layer and the processing layer is called a Broker. Brokers are responsible for routing and managing messages between IoT devices and other parts of the IoT infrastructure. They play a critical role in ensuring efficient communication and data flow within an IoT system.

The integration of AI in IoT is enabling enhanced data analytics, allowing IoT devices to make intelligent decisions based on vast amounts of data. This includes real-time data analysis, predictive maintenance, and more, making it a transformative aspect of IoT.

This scenario involves the use of sensors and data exchange to enable machines to adapt based on real-time data. It fits the category of IoT, as it involves connecting physical objects (machines) to the internet to collect and exchange data, allowing for remote monitoring and control.

C++ is often preferred for resource-constrained IoT devices due to its low-level capabilities, which allow for efficient memory and resource management. Python, Java, and JavaScript are higher-level languages.

For real-time data processing and minimal latency, C++ is often preferred due to its low-level capabilities, and Arduino is a popular choice for IoT hardware development. Python, Java, and JavaScript are less suitable for these requirements.

AI integration with IoT is beneficial because it allows for enhanced data analysis. AI algorithms can process and derive insights from the vast amount of data generated by IoT devices, enabling smarter decision-making. Lower IoT device costs, increased latency, and improved battery life are important factors in IoT but not the primary reason for AI integration.

In the early 1990s, the development of an early IoT concept for supply chain monitoring was mainly based on RFID technology. RFID allowed the tracking of products or assets using radio waves, making it a crucial technology for early IoT implementations.