research-article

CityLightSense: A Participatory Sensing-based System for Monitoring and Mapping of Illumination levels

Authors:

Asif Iqbal Middya,

Debjani ChattopadhyayAuthors Info & Claims

ACM Transactions on Spatial Algorithms and Systems (TSAS), Volume 8, Issue 1

Article No.: 5, Pages 1 - 22

https://doi.org/10.1145/3487364

Published: 26 October 2021 Publication History

Abstract

Adequate nighttime lighting of city streets is necessary for safe vehicle and pedestrian movement, deterrent of crime, improvement of the citizens’ perceptions of safety, and so on. However, monitoring and mapping of illumination levels in city streets during the nighttime is a tedious activity that is usually based on manual inspection reports. The advancement in smartphone technology comes up with a better way to monitor city illumination using a rich set of smartphone-equipped inexpensive but powerful sensors (e.g., light sensor, GPS, etc). In this context, the main objective of this work is to use the power of smartphone sensors and IoT-cloud-based framework to collect, store, and analyze nighttime illumination data from citizens to generate high granular city illumination map. The development of high granular illumination map is an effective way of visualizing and assessing the illumination of city streets during nighttime. In this article, an illumination mapping algorithm called Street Illumination Mapping is proposed that works on participatory sensing-based illumination data collected using smartphones as IoT devices to generate city illumination map. The proposed method is evaluated on a real-world illumination dataset collected by participants in two different urban areas of city Kolkata. The results are also compared with the baseline mapping techniques, namely, Spatial k-Nearest Neighbors, Inverse Distance Weighting, Random Forest Regressor, Support Vector Regressor, and Artificial Neural Network.

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Cited By

Middya ARoy SMandal S(2022)User recognition in participatory sensing systems using deep learning based on spectro-temporal representation of accelerometer signalsKnowledge-Based Systems10.1016/j.knosys.2022.110046258:COnline publication date: 22-Dec-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.110046
Gabinet NPortnov B(2022)Investigating the combined effect of ALAN and noise on sleep by simultaneous real-time monitoring using low-cost smartphone devicesEnvironmental Research10.1016/j.envres.2022.113941214(113941)Online publication date: Nov-2022
https://doi.org/10.1016/j.envres.2022.113941

Index Terms

CityLightSense: A Participatory Sensing-based System for Monitoring and Mapping of Illumination levels
1. Human-centered computing
  1. Ubiquitous and mobile computing
    1. Ubiquitous and mobile computing systems and tools
    2. Ubiquitous and mobile devices
      1. Smartphones
2. Information systems
  1. Information systems applications
    1. Spatial-temporal systems

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Published In

cover image ACM Transactions on Spatial Algorithms and Systems

ACM Transactions on Spatial Algorithms and Systems Volume 8, Issue 1

March 2022

184 pages

ISSN:2374-0353

EISSN:2374-0361

DOI:10.1145/3488003

Editor:
Walid G. Aref
Purdue University, USA

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 26 October 2021

Accepted: 01 September 2021

Revised: 01 July 2021

Received: 01 January 2021

Published in TSAS Volume 8, Issue 1

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UGC-NET Junior Research Fellowship
“Participatory and Realtime Pollution Monitoring System For Smart City”
Department of Science & Technology, Government of West Bengal, India

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Cited By

Middya ARoy SMandal S(2022)User recognition in participatory sensing systems using deep learning based on spectro-temporal representation of accelerometer signalsKnowledge-Based Systems10.1016/j.knosys.2022.110046258:COnline publication date: 22-Dec-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.110046
Gabinet NPortnov B(2022)Investigating the combined effect of ALAN and noise on sleep by simultaneous real-time monitoring using low-cost smartphone devicesEnvironmental Research10.1016/j.envres.2022.113941214(113941)Online publication date: Nov-2022
https://doi.org/10.1016/j.envres.2022.113941

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