The group intends to take advantage of the existing lighting network to implement on it a series of plug & play sensors and controller devices (where needed), and make of it the main smart urban infrastructure. Deploying and installing multiple sensors can allow the creation and set up of a network. The whole network is then remotely manageable and monitorable thanks to the use of a user-friendly software platform.
· Controllers
· Sensors
· Software/App user interface
Having in place the above elements would mean being able to:
· Collect data (traffic is one of these)
· Efficient the energy usage overnight (“light on demand”)

The controllers allow communication amongst lampposts whilst sensors detect and record information. All data collected with regards to energy either traffic are communicated to a gateway and stored in a cloud space for a time interval sufficiently long to have periodical reports and assess the situation. All the reports are easily accessible through the software and also a real-time report can be accessed.

Innovation – But is more than that

ThinkL(AI)ghT is equipped with an Artificial Intelligence (AI) brain and capable to take actions and address the users’ choice based on a specific logics algorithms according to real-time data collected and past events scenarios that have occurred.
So to the great advantage of collecting traffic real time data, it plays a significant role for the Road Safety and the Network and traffic management, improving the mobility.
ThinkL(AI)ghT collect data from sensors installed and provide traffic reports useful for realizing simulations and traffic models.
Properly integrated with AI (Artificial Intelligence) and its appropriate configuration, the system is capable to make decisions and interact with the surrounding environment to ensure higher safety conditions and optimize operations.
The AI is the lifeblood of the solution. It receives information from the sensors and check whether, according to past and “standard” situations is anything unusual.
If this check has a negative response, the system follow specific instructions, warning the infrastructure department and record the action requested by the latter. Is therefore capable to learn.
TLT can now detect anomalies and take actions like:
· Redirect and address traffic
· Prevent accidents and dangerous situations
· Warn road users
· Communicate with entities, users and authorities

Figure 1 – ThinkL(AI)ghT, obstacle on the way case (night).

The network will therefore be able to make autonomous decisions based, in fact, on the formulation of a strategic thought helping managing traffic and make proper mobility plan, furthermore can addressing the users to safer behaviors.