9.2.4. Evaluation

The simulation with the *SEJAM* simulator was able to be performed with more than 1000 nodes, hundreds of beacons, and more than 10000 explorer agents. Real-time values for one simulation step depend on the number of active agents to be processed, node and agent mobility (graphics and communication), and ranges from 1 ms to 1 s. For this use-case, a real-time simulation step of 1 s is more than sufficient to control lights in streets and on places (or within buildings). The minimal response time from sensor input to actuator control is about 5 s.

The user feedback from crowd sensing surveys performed by mobile agents is used to optimise illumination in public areas like streets with respect to user and energy management constraints. Energy saving up to 30% can be achieved, light pollution can be decreased, and citizen satisfaction can

be optimised. Combined with machine learning, the simulation (mapping a real-world city region) can be used to predict future light demands based on crowd sensing and using other physical sensors (e.g., crowd and traffic flow sensors).
