The integration of "5G" technology marked a significant evolution in the capabilities of IoT devices. The high-speed, low-latency nature of 5G networks enables faster and more efficient communication between IoT devices, paving the way for new applications and functionalities.

In an agriculture scenario where immediate data processing is needed, edge computing is the suitable choice. Edge computing processes data locally (in the drones) without the need to send it to a central cloud, reducing latency and improving efficiency for real-time applications.

In the context of agriculture, the integration of AI with soil moisture sensors primarily serves to enhance water efficiency, ensuring that irrigation is applied precisely where and when it's needed, conserving water resources.

In smart homes, when you use voice commands to control lighting, this is an instance of "Voice" communication. It's a communication method where you are using your voice to interact with the home automation system to control various devices like lighting, thermostats, and more.

Mbed OS is a lightweight and open-source operating system designed for IoT devices, particularly those with limited resources. Windows 10, Ubuntu Linux, and macOS are not specifically tailored for IoT and are typically used in larger systems.

Kevin Ashton, who coined the term "Internet of Things," related it primarily to the idea of connecting physical objects to the Internet to enable them to communicate and share data. His vision laid the groundwork for the IoT we know today.

This scenario exemplifies the use of IoT (Internet of Things) for Smart Traffic Management, where sensors collect real-time data and AI is applied to predict traffic congestion and optimize traffic flow.

A primary concern in IoT data security is unauthorized access and data breaches. IoT devices often handle sensitive information, making them targets for cyberattacks. Ensuring that data remains secure and protected from unauthorized access is a critical consideration.

In IoT projects, the study of successful implementations to understand best practices is often referred to as "Lessons Learned." This involves analyzing successful cases to identify strategies, approaches, and practices that can be applied to future projects.

IoT security standards primarily involve best practices and technical specifications for securing IoT devices and data, while regulatory compliance pertains to legal requirements set by authorities.

Real-time analytics in IoT deployments relies on stream processing technology. Stream processing allows IoT systems to process data as it arrives, enabling real-time analysis, monitoring, and decision-making. It is essential for handling high-velocity data from IoT devices effectively.

Python is favored for data-intensive IoT applications due to its extensive libraries for data processing and analysis. It's versatile and has a large community, making it suitable for a wide range of data-related tasks in IoT. While C, R, and Swift have their strengths, Python stands out in this context.