'Intelligent Cities' - Interdependent Time Series Graphically Analyzed. Strategies in Traffic Control and Street Lighting

摘要

An "Intelligent City" feels (collects) data, learns, thinks, reacts, feels the new impulses, understands the results, learns, re-thinks, reacts and so on, the process being continuous and lively. When the City understands its limitation and potential, it can struggle to become efficient and sustainable. Prediction of events can generate system adjustment leading to the increase of the population comfort level and economic benefits up to avoiding disasters. The Time Series concept can be applied to forecast and control traffic in street intersections or to reduce energy consumption in street lighting, thus we can analyze graphically a certain behavior (each working day between 6 and 10 a.m. or 4 and 6p.m.). The system gather specific data in specific places and using integrator algorithms is capable of machine learning and pattern recognition, can take action, analyze the results and retake action in real time. Talking about the traffic control, the system is structured based on a network of sensors, build in traffic lane, connected for each lane, a system of local computers which gathers data and has limited access to decisions, a central computer which integrates data and takes decision at a higher level, providing the traffic fluency. Also decisions can be taken about the street's lighting level according to the traffic level. When emergency occurs, specific "emergency scenarios" can be put in action. All above mentioned can reduce the lost time, the pollution caused by stationary traffic and the energy consumption by decreasing lighting in the absence of traffic.