IoT enabled intelligent sensor node for smart city: pedestrian counting and ambient monitoring

Fowzia Akhter; Sam Khadivizand; Hasin Reza Siddiquei; Md Eshrat E. Alahi; Subhas Mukhopadhyay

doi:10.3390/s19153374

IoT enabled intelligent sensor node for smart city: pedestrian counting and ambient monitoring

Fowzia Akhter, Sam Khadivizand, Hasin Reza Siddiquei, Md Eshrat E. Alahi, Subhas Mukhopadhyay

School of Engineering

Research output: Contribution to journal › Article › peer-review

57 Citations (Scopus)

371 Downloads (Pure)

Abstract

An Internet of Things (IoT) enabled intelligent sensor node has been designed and developed for smart city applications. The fabricated sensor nodes count the number of pedestrians, their direction of travel along with some ambient parameters. The Field of View (FoV) of Fresnel lens of commercially available passive infrared (PIR) sensors has been specially tuned to monitor the movements of only humans and no other domestic animals such as dogs, cats etc. The ambient parameters include temperature, humidity, pressure, Carbon di Oxide (CO₂) and total volatile organic component (TVOC). The monitored data are uploaded to the Internet server through the Long Range Wide Area Network (LoRaWAN) communication system. An intelligent algorithm has been developed to achieve an accuracy of 95% for the pedestrian count. There are a total of 74 sensor nodes that have been installed around Macquarie University and continued working for the last six months.

Original language	English
Article number	3374
Pages (from-to)	1-19
Number of pages	19
Journal	Sensors
Volume	19
Issue number	15
DOIs	https://doi.org/10.3390/s19153374
Publication status	Published - 1 Aug 2019

Bibliographical note

Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

intelligent sensor
the direction of travel
ambient monitoring
smart city

Access to Document

10.3390/s19153374Licence: CC BY

Publisher version (open version)Final published version, 4.8 MBLicence: CC BY

Cite this

@article{c972d14449084341acb6c3b478a511d1,

title = "IoT enabled intelligent sensor node for smart city: pedestrian counting and ambient monitoring",

abstract = "An Internet of Things (IoT) enabled intelligent sensor node has been designed and developed for smart city applications. The fabricated sensor nodes count the number of pedestrians, their direction of travel along with some ambient parameters. The Field of View (FoV) of Fresnel lens of commercially available passive infrared (PIR) sensors has been specially tuned to monitor the movements of only humans and no other domestic animals such as dogs, cats etc. The ambient parameters include temperature, humidity, pressure, Carbon di Oxide (CO2) and total volatile organic component (TVOC). The monitored data are uploaded to the Internet server through the Long Range Wide Area Network (LoRaWAN) communication system. An intelligent algorithm has been developed to achieve an accuracy of 95% for the pedestrian count. There are a total of 74 sensor nodes that have been installed around Macquarie University and continued working for the last six months.",

keywords = "intelligent sensor, the direction of travel, ambient monitoring, smart city",

author = "Fowzia Akhter and Sam Khadivizand and Siddiquei, {Hasin Reza} and Alahi, {Md Eshrat E.} and Subhas Mukhopadhyay",

note = "Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",

year = "2019",

month = aug,

day = "1",

doi = "10.3390/s19153374",

language = "English",

volume = "19",

pages = "1--19",

journal = "Sensors",

issn = "1424-8220",

publisher = "MDPI",

number = "15",

}

TY - JOUR

T1 - IoT enabled intelligent sensor node for smart city

T2 - pedestrian counting and ambient monitoring

AU - Akhter, Fowzia

AU - Khadivizand, Sam

AU - Siddiquei, Hasin Reza

AU - Alahi, Md Eshrat E.

AU - Mukhopadhyay, Subhas

N1 - Copyright the Author(s) 2019. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2019/8/1

Y1 - 2019/8/1

N2 - An Internet of Things (IoT) enabled intelligent sensor node has been designed and developed for smart city applications. The fabricated sensor nodes count the number of pedestrians, their direction of travel along with some ambient parameters. The Field of View (FoV) of Fresnel lens of commercially available passive infrared (PIR) sensors has been specially tuned to monitor the movements of only humans and no other domestic animals such as dogs, cats etc. The ambient parameters include temperature, humidity, pressure, Carbon di Oxide (CO2) and total volatile organic component (TVOC). The monitored data are uploaded to the Internet server through the Long Range Wide Area Network (LoRaWAN) communication system. An intelligent algorithm has been developed to achieve an accuracy of 95% for the pedestrian count. There are a total of 74 sensor nodes that have been installed around Macquarie University and continued working for the last six months.

AB - An Internet of Things (IoT) enabled intelligent sensor node has been designed and developed for smart city applications. The fabricated sensor nodes count the number of pedestrians, their direction of travel along with some ambient parameters. The Field of View (FoV) of Fresnel lens of commercially available passive infrared (PIR) sensors has been specially tuned to monitor the movements of only humans and no other domestic animals such as dogs, cats etc. The ambient parameters include temperature, humidity, pressure, Carbon di Oxide (CO2) and total volatile organic component (TVOC). The monitored data are uploaded to the Internet server through the Long Range Wide Area Network (LoRaWAN) communication system. An intelligent algorithm has been developed to achieve an accuracy of 95% for the pedestrian count. There are a total of 74 sensor nodes that have been installed around Macquarie University and continued working for the last six months.

KW - intelligent sensor

KW - the direction of travel

KW - ambient monitoring

KW - smart city

UR - http://www.scopus.com/inward/record.url?scp=85071070692&partnerID=8YFLogxK

U2 - 10.3390/s19153374

DO - 10.3390/s19153374

M3 - Article

C2 - 31374837

AN - SCOPUS:85071070692

SN - 1424-8220

VL - 19

SP - 1

EP - 19

JO - Sensors

JF - Sensors

IS - 15

M1 - 3374

ER -

IoT enabled intelligent sensor node for smart city: pedestrian counting and ambient monitoring

Abstract

Bibliographical note

Keywords

Access to Document

Other files and links

Fingerprint

Cite this