A simulation model for the financial evaluation of smart streetlight technologies.

The simulation creates a streetlight installation using the specified configuration and compares its lifecycle value against other lighting options. The streetlight installation can also add sensor systems to enable traffic-aware on-demand adaptive road lighting to reduce electrical and maintenance costs.

The simulation provides a breakdown of costs and net-present value comparisons against existing technologies. Three Queensland cities were used as a basis of a case-study, and the simulation used traffic data from those locations to precisely inform the likely dimming scenarios.

The data files contain potentially valuable IP and are currently stored in the secure section of the Tropical Data Hub. The zip archive includes:

• Pipfile - Pipenv virtual environment configuration file - see https://realpython.com/pipenv-guide/#the-pipfile

• calculator_classes.py - Simulation model classes

• Streetfighter_Simulation.ipynb - Simulation Jupyter notebook file

• traffic_data.csv - Traffic dataset used in the simulation. Derived from the Department of Transport and Main Roads (https://data.qld.gov.au/dataset/queensland-traffic-data-averaged-by-hour-of-day-and-day-of-week) which has licensed the data for re-use under Creative Commons BY 4.0