IoT Enabled Intelligent Sensor Node for Smart City: Pedestrian Counting and Ambient Monitoring

被引:40
作者
Akhter, Fowzia [1 ]
Khadivizand, Sam [1 ]
Siddiquei, Hasin Reza [2 ]
Alahi, Md Eshrat E. [3 ]
Mukhopadhyay, Subhas [1 ]
机构
[1] Macquarie Univ, Dept Engn, Sydney, NSW 2109, Australia
[2] Uttara Univ, Dept Elect & Elect Engn, Dhaka 1230, Bangladesh
[3] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen 518055, Peoples R China
关键词
intelligent sensor; the direction of travel; ambient monitoring; smart city; TRACKING;
D O I
10.3390/s19153374
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
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 RangeWide 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.
引用
收藏
页数:19
相关论文
共 30 条
[1]  
Akkaya K, 2015, IEEE WIREL COMMUNN, P58, DOI 10.1109/WCNCW.2015.7122529
[2]  
[Anonymous], P IEEE INT C VID SIG
[3]  
Balaji Bharathan, 2013, P 11 ACM C EMB NETW
[4]   Edge-Computing Video Analytics for Real-Time Traffic Monitoring in a Smart City [J].
Barthelemy, Johan ;
Verstaevel, Nicolas ;
Forehead, Hugh ;
Perez, Pascal .
SENSORS, 2019, 19 (09)
[5]   Smart sustainable cities of the future: An extensive interdisciplinary literature review [J].
Bibri, Simon Elias ;
Krogstie, John .
SUSTAINABLE CITIES AND SOCIETY, 2017, 31 :183-212
[6]  
Bounceur A., 2017, P INT C ADV TECHN SI, P1
[7]   Low-Power LoRa Signal-Based Outdoor Positioning Using Fingerprint Algorithm [J].
Choi, Wongeun ;
Chang, Yoon-Seop ;
Jung, Yeonuk ;
Song, Junkeun .
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2018, 7 (11)
[8]   Occupancy Counting With Burst and Intermittent Signals in Smart Buildings [J].
Ciftler, Bekir Sait ;
Dikmese, Sener ;
Guvenc, Ismail ;
Akkaya, Kemal ;
Kadri, Abdullah .
IEEE INTERNET OF THINGS JOURNAL, 2018, 5 (02) :724-735
[9]   ESCAPE: Evacuation Strategy through Clustering and Autonomous Operation in Public Safety Systems [J].
Fragkos, Georgios ;
Apostolopoulos, Pavlos Athanasios ;
Tsiropoulou, Eirini Eleni .
FUTURE INTERNET, 2019, 11 (01)
[10]  
Gorbil G., 2011, COMPUTER INFORM SCI