Cameras: To monitor real$-$time traffic at intersections.

Vehicle Count Sensors: To collect data on the number of vehicles passing through

intersections.

Speed Sensors: To gather information on the speed of the traffic flow.

Smart Traffic Lights: To control the traffic based on data received from sensors and

the central management system.

Other things such as motion sensors$,$ parking light, etc

Connectivity: Implement both wired and wireless connections using routers, switches, and

IoT gateways as needed. Add both PCs and Phones for LTE connectivity.

Part $2$: Smart Parking System

System Management: Use the City IoT Server for real$-$time control and monitoring of the

smart parking infrastructure.

City Office Remote Control: Operate and monitor parking systems via networked

computers within the city offices, accessing the City IoT Server.

Public Access Interface: Develop a public$-$facing interface on smartphones,

allowing citizens to view and interact with real$-$time parking availability data.

Program the Raspberry Pi with Python to process data locally at intersections before

sending it to the central traffic management system.

Simulate the central server to handle HTTP and MQTT communications, managing

data flow and issuing commands based on real$-$time analytics.

Part $3$: Smart Traffic Management

Emergency Vehicle Prioritization: Simulate and implement a system where emergency

vehicles communicate with traffic control devices to facilitate immediate passage.

Adaptive Traffic Control: Program traffic lights to automatically adjust when

emergency vehicles are detected, ensuring swift and safe passage through

intersections.

Part $4$: Reflection and Analysis

Smart Decision Making: Evaluate how the integration of sensors$,$ software, and server

capabilities can enhance decision$-$making processes in a smart city. Cloud Computing in Smart Cities: Analyze how cloud computing supports the scalability

and efficiency of city operations, managing data from diverse sources for better city

planning and response.

Part $5$: Challenge

Smart Furniture Design: Engage in a creative exercise to design a smart chair that uses sensors

to monitor and record the weight and usage patterns of its users, demonstrating the versatility and

potential of IoT applications.

Deliverables:

A detailed project report that includes network diagrams, IoT device configurations, data

flow diagrams, and analysis of system performance. Including $.$PKT file

Students will design a simulated intelligent traffic management system for a city section. The

system will include the integration of various IoT devices such as traffic sensors$,$ cameras, and

smart traffic lights, alongside advanced components like an LTE$-$enabled smartphone, a Raspberry

Pi board running Python, and a central server managing IoT communications.

Part $1$: Smart City Exploration

IoT Devices: Utilize the following specific sensors and actuators available in Packet Tracer

v$8$: