Artificial Neural Network Based Smart and Energy Efficient Street Lighting System: a Case Study for Residential Area in Hosur

Smart city is the term described to integrate all facilities to the people in a frequently accessible manner. Street lighting system is one of the part of the facility provided in smart cities. The unwanted utilization of the street lighting affects the economic status of the country indirectly. Power consumption through street lighting is major problem, hence action plan is taken to promote the reduction policies of the power consumption. Reducing the unnecessary power consumption is not a simple task, but with soft computing approaches power consumption can be reduced. The objective of this article is to present an ANN based energy efficienct smart street lighting systems. The proposed design were implemented and executed in a residential area, hosur and the results are carried out at different scenarios and various seasons. The decision making module exploits the analysis factors obtained via lighting sensor, motion sensor, PIR sensor, etc. Artificial Neural Network and Fuzzy Logic Controller makes an efficient decision making process for demand based utilization and to avoid the unnecessary utilization of street lights. The five levels of scenarios are tested and implemented in a real time. Through this work, the smart and energy efficiency street lighting system reduced the unwanted utilization by 34% and reduced the power consumption rate of 13.5%.

• Record URL:
  • https://doi.org/10.1016/j.scs.2019.101499
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S2210670718317530
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/22106707
• Supplemental Notes:
  • © 2019 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Mohandas, Prabu
  • Dhanaraj, Jerline Sheebha Anni
  • Gao, Xiao-Zhi
• Publication Date: 2019-7

Language

• English

Media Info

• Media Type: Web
• Features: Figures; Photos; References; Tables;
• Pagination: pp 101499
• Serial:
  • Sustainable Cities and Society
  • Volume: 48
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 2210-6707
  • Serial URL: http://www.sciencedirect.com/science/journal/22106707?sdc=2

Subject/Index Terms

• TRT Terms: Automatic controllers; Energy consumption; Fuzzy logic; Neural networks; Residential areas; Sensors; Street lighting
• Geographic Terms: Hosur (Tamil Nadu, India)
• Subject Areas: Data and Information Technology; Energy; Highways;

Filing Info

• Accession Number: 01708997
• Record Type: Publication
• Files: TRIS
• Created Date: Jun 27 2019 2:41PM