LiSense: Monitoring City Street Lighting During Night using Smartphone Sensors

Munshi Yusuf Alam, Shahrukh Imam, H. Anurag, Sujoy Saha, S. Nandi, M. Saha
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引用次数: 5

Abstract

Adequate illumination of city streets during night hours is essential to ensure road safety. However, even for developed cities, monitoring streetlights still remain a tedious task that relies on manual inspection reports. Existing systems mostly rely on vehicle-mounted camera or sensors fitted at every light post that is not cost-effective and scalable. In contrary, in this paper, we develop a novel cost-effective system LiSense to monitor illumination levels of street lights and detect as well as localize malfunctioning light posts. The system utilizes ambient light and GPS sensors and uses crowdsourcing. Sensor trails collected by our App from 2-wheeler covering 160 km suburban city road detects all malfunctioning street lights more than 96% in accuracy with a mean localization error of 6 meters. To the best of our knowledge, this is the first of its kind approach to monitoring street light condition which is cost-effective, scalable and suitable for developing regions.
LiSense:夜间使用智能手机传感器监控城市街道照明
夜间城市街道的充足照明对确保道路安全至关重要。然而,即使在发达城市,监控路灯仍然是一项繁琐的任务,依赖于人工检测报告。现有的系统大多依赖于安装在每个灯柱上的车载摄像头或传感器,这既不划算,也不具可扩展性。相反,在本文中,我们开发了一种新颖的具有成本效益的系统LiSense来监测路灯的照明水平,并检测和定位故障灯柱。该系统利用环境光和GPS传感器,并采用众包方式。我们的App从覆盖160公里郊区城市道路的两轮车收集的传感器轨迹检测到所有故障路灯的准确率超过96%,平均定位误差为6米。据我们所知,这是第一个监测路灯状况的方法,具有成本效益,可扩展且适合发展中地区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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