Citation :

Jhonny Roy Condori Cahuaya, Bryan Gomez Pacheco, Jezzy James Huaman Rojas, "Illuminance Evaluation in Urban Roadways using UAV and IoT for Dark Zone Detection and Public Lighting Inspection," International Journal of Electrical and Electronics Engineering, vol. 13, no. 9, pp. 136-147, 2026. Crossref, https://doi.org/10.14445/23488379/IJEEE-V13I9P111

Abstract

Conventional public lighting inspections have difficulty capturing illumination reductions in certain areas, as they only cover a specific geographical location. This study develops and tests a UAV-IoT system to analyze the distribution of illumination from LED lighting within three urban districts. The proposed system combines equipment that includes a BH1750 sensor and an ESP32-C3 microcontroller, along with UAV data collection and transmission of the data to an IoT system. The campaign included 90 spatial positions distributed between roadway and sidewalk areas, three runs per segment, and 20,250 samples acquired at a nominal height of 0.5 m. The lowest levels were consistently located around longitudinal position X3, with minimum values at X3-Y3 for both evaluated surfaces. T2 had the highest average illuminance, whereas T3 had the lowest. Comparison with a reference lux meter at 24 spatial positions yielded a MAPE of 0.183%, an RMSE of 0.245 lux, and an R² of 0.99998. IoT communication showed an overall packet loss of 0.69%. The system provides a multipoint representation of the illuminance distribution and enables the location of sectors requiring subsequent photometric verification.

Keywords

LED public lighting, Illuminance, Internet of Things, Unmanned Aerial Vehicle, Low-illuminance zones.

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