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Ubiquitous street lighting is essential for urban areas. While nowadays, LED-based "smart lamps" are commercially available, municipalities can only switch to them in the long run due to financial constraints. Especially, older types of lamps require frequent bulb replacements to maintain the lighting infrastructure's function. To speed up the detection of defects and enable better planning, a non-invasively retrofittable IoT sensor solution is proposed that monitors lamps for defects via visible light sensors, communicates measurement data wirelessly to a central location via LoRaWAN, and processes and visualizes the resulting information centrally. The sensor nodes are capable of automatically adjusting to shifting day- and nighttimes thanks to a second sensor monitoring ambient light. The work specifically addresses aspects of energy efficiency essential to the battery-powered operation of the sensor nodes. Besides design considerations and implementation details, the paper also summarizes the experimental validation of the system by way of an extensive field trial and expounds upon further experiences from it. [ABSTRACT FROM AUTHOR]

The need for certification standards for new convergence products, such as a smart LED streetlight system, has been identified as a critical issue. This study proposes simulation modeling for smart LED streetlight systems and suggests three certification standards: the minimum time to initiate dimming-up, the duration of the dimming-up period, and the number of concurrently controlled streetlights. We utilized Relux to model streetlights and roads in terms of luminance levels, and used analytical formulas to compute the braking distances of oncoming vehicles. The two models were integrated into a smart LED streetlight system model using Simio. Simulation experiments were conducted with two objectives: to provide certification standards, and to apply and verify them in real-world cases. We experimented with 630 scenarios, modeling various dynamic situations involving roads and vehicles, and applied the model to two actual roads in the Republic of Korea to test its validity. The model was subsequently applied to roads for which traffic-volume data were available, to determine potential energy savings. The proposed simulation method can be applied to a smart LED streetlight system and to new products that lack certification standards. Furthermore, the proposed certification standards offer alternative approaches to operating streetlight systems more efficiently. [ABSTRACT FROM AUTHOR]

Evidence about the relationship between lighting and crime is mixed. Although a review of evidence found that improved road / street lighting was associated with reductions in crime, these reductions occurred in daylight as well as after dark, suggesting any effect was not due only to changes in visual conditions. One limitation of previous studies is that crime data are reported in aggregate and thus previous analyses were required to make simplifications concerning types of crimes or locations. We will overcome that by working with a UK police force to access records of individual crimes. We will use these data to determine whether the risk of crime at a specific time of day is greater after dark than during daylight. If no difference is found, this would suggest improvements to visual conditions after dark through lighting would have no effect. If however the risk of crime occurring after dark was greater than during daylight, quantifying this effect would provide a measure to assess the potential effectiveness of lighting in reducing crime risk after dark. We will use a case and control approach to analyse ten years of crime data. We will compare counts of crimes in 'case' hours, that are in daylight and darkness at different times of the year, and 'control' hours, that are in daylight throughout the year. From these counts we will calculate odds ratios as a measure of the effect of darkness on risk of crime, using these to answer three questions: 1) Is the risk of overall crime occurring greater after dark than during daylight? 2) Does the risk of crime occurring after dark vary depending on the category of crime? 3) Does the risk of crime occurring after dark vary depending on the geographical area? [ABSTRACT FROM AUTHOR]

The article presents selected results of research on improving pedestrian traffic safety. Based on annually-updated accident statistics made available by the police, as well as the new pedestrian traffic regulations in force, detailed work was undertaken to assess the level of visibility of pedestrians by drivers in pedestrian crossing areas. The research was carried out by analyzing several characteristic cases of pedestrian crossings occurring in Poland, in which there was only dedicated lighting for crossings, only street lighting, and a variant of coexistence of both of the above lighting solutions. Illuminance measurements were made in the horizontal and vertical planes of pedestrian crossings, and the results were confronted with the relevant guidelines. The next step involved a complementary measurement of the luminance distribution of the vertical plane containing the pedestrian and a portion of the sub- and super-horizontal background. Visibility pedestrians was considered in positive and negative contrast variants, and was then related to the obtained results of the illumination distribution. The analysis of the results of the study indicated the possibility of limited visibility of pedestrians at the crossings despite the satisfactory results obtained from measurements of the illuminance distribution within the crossings. [ABSTRACT FROM AUTHOR]