Intelligent street lighting monitoring and control

Recent advances in technology enabled the development of street lighting systems with integrated measuring sensors and enhanced communication between the lights. Some of the main features of such systems are their ability to improve the lighting quality and increase their energy efficiency by leveraging the data they retrieve from the environment. In this Master's thesis we collaborate with Garex, who provided us with the necessary lighting infrastructure, and propose an intelligent control algorithm to optimise the lighting system's performance. We thoroughly review scientific literature and relevant regulations and analyse in detail the installed lighting system. We tackle the problem by proposing a time-based adaptive lighting solution that leverages the ambient illuminance and traffic density measurements to periodically generate forecasts for the lighting regimes. Due to data quality issues, we evaluate its performance in terms of its energy efficiency on an artificially generated dataset only. The simulations indicate that, while complying with the regulations and without compromising the lighting quality, the electricity consumption of the analysed street lighting system could be reduced by more than 50% annually. Sodobni tehnološki napredek je omogočil razvoj sistemov ulične razsvetljave z integriranimi merilnimi senzorji in izboljšano komunikacijo s svetilkami. Nekatere izmed glavnih prednosti takih sistemov so njihova sposobnost izboljšanja kvalitete same razsvetljave in predvsem povečanje energetske učinkovitosti z izkoriščanjem podatkov iz okolice, pridobljenih z nameščenimi senzorji. V magistrski nalogi, v sodelovanju z Garexom, ki je priskrbel vso potrebno svetilno infrastrukturo, z namenom optimizacije učinkovitosti ulične razsvetljave predlagamo pameten algoritem za njeno upravljanje. Izvedemo temeljit pregled razpoložljive znanstvene literature in trenutno veljavnih predpisov na tem področju ter podrobno analizo nameščenega sistema razsvetljave. Kot rešitev postavljenega izziva predlagamo časovno opredeljeno prilagodljivo razsvetljavo, ki izkorišča meritve osvetljenosti okolice in gostote prometa za generiranje napovedi režimov svetilnosti. Zaradi slabe kvalitete določenih podatkov lahko delovanje in energetsko učinkovitost predlagane rešitve ocenimo samo na umetno generirani podatkovni množici. Simulacije nakazujejo, da lahko ob upoštevanju veljavnih predpisov in brez ogrožanja kakovosti razsvetljave v obravnavanem sistemu ulične razsvetljave prihranimo na letni ravni preko 50% električne energije.