The Deployment phase in the IoT project lifecycle involves testing the solution in real-world conditions. It's the stage where the IoT system is put into operation and evaluated in a real environment. Development and Testing are earlier phases, while Evaluation typically follows deployment.

The integration of 5G in IoT is expected to revolutionize all of these sectors. In healthcare, it will enable remote patient monitoring and real-time data transmission. In agriculture, it will enhance precision farming. In transportation, it will improve autonomous vehicles and smart traffic management.

The concern raised by citizens about tracking and storing their movements without anonymization pertains to data privacy. It highlights the need for privacy safeguards in IoT-based systems, especially in public infrastructure.

The M2M (Machine-to-Machine) communication model is most prevalent in applications such as home automation systems where machines (devices) communicate with each other to control various functions like lighting, heating, and security. This model is designed for seamless communication between machines to automate tasks and processes.

RFID technology played a significant role in the early development of IoT concepts. RFID tags and sensors allowed physical objects to be uniquely identified and tracked, which was a crucial foundation for the Internet of Things.

One of the main challenges in deploying WSN in IoT is the limited battery life of sensor nodes. This is because many sensor nodes are often deployed in remote or inaccessible locations, making it challenging to replace or recharge their batteries.

In a typical IoT system, the Data layer is responsible for processing and analyzing the collected data. This layer is crucial for handling, storing, and making sense of the data gathered from various sensors and devices in the IoT ecosystem.

Data visualization in IoT is essential for monitoring and understanding data. It allows stakeholders to interpret complex data easily, identify trends, and make informed decisions. Effective data visualization is crucial for deriving actionable insights from IoT data.

The main difference is that a general-purpose OS is not optimized for resource-constrained IoT devices. IoT OS is designed to run efficiently on devices with limited processing power and memory.

Early IoT was primarily focused on industrial automation and monitoring. It was used to improve processes, gather data from sensors in manufacturing and logistics, and increase efficiency in various industries. IoT's roots can be traced back to applications like remote monitoring and control of industrial equipment.