A smart parking system using IoT

Gopal, Deepthi; Jerlin, M. Asha; Abirami, M.

doi:10.1504/wremsd.2019.099409

Cited by 10 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It troubles the undergraduates, workers, and accidental patients to a notable level [8]. It additionally reasons financial harm to industrial areas like malls, amusement grids, as humans stay extra probably not to go to these locations due to this parking threat [9]. As we are proceeding with time, the guided automobile parking scheme in industrial areas is growing a difficulty that is initiating consumption of time and some financial damages as well.…”

Section: Methodsmentioning

confidence: 99%

Smart parking for smart cities: a novel approach to reducing frivolous parking zone determination

Atiqur

Liton

2023

IJ-ICT

View full text Add to dashboard Cite

Internet of things (IoT) infrastructures are rapidly expanding, which will lead to an unanticipated rise in demand for smart cities. The concept of a "smart city" has recently gained traction in urban planning circles. An IoT based smart parking system is the focus of this article, and it allows a motorist to locate a car park and an available parking space in an indoor metropolis, all from the comfort of their own vehicle. Additional efforts are made to reduce the time spent defining parking zones. Reduced fuel use helps to cut down on pollution, as well as avoid needless travel through congested parking lots, which can help to reduce unlawful parking and alleviate traffic congestion in the city we all live in. These innovations include automobile particular identification via radio frequency identification (RFID) tags, unoccupied slot detection through the use of ultrasonic sensors, and cost calculating based largely on parking duration. The technology we've used is unique in that it runs on separate parts of the system for the hardware and the software.

show abstract

Section: Methodsmentioning

confidence: 99%

Smart parking for smart cities: a novel approach to reducing frivolous parking zone determination

Atiqur

Liton

2023

IJ-ICT

View full text Add to dashboard Cite

show abstract

“…ESP 32 is compatible with mobile devices and Internet of Things (IoT) applications (Athallah Muhammad Yazid & Agung Permana, 2022). IoT has already been implemented in many projects such as for smart cities (In, 2017), smart parking systems (Ganesh Gopal et al, 2019;Gopal et al, n.d.;Khanna & Anand, 2016), and also implement to the smart home systems (Ravikumar & Kavitha, 2021;Utari, 2021). It is also used for developing firefighting robotic (Aulia et al, 2021) and a system monitoring in aerodrome airfield lighting system (Beacon et al, 2021).…”

Section: A Introductionmentioning

confidence: 99%

SMART CADETS Prototype Design: Data-based RFID for Cadet Academic Hours Optimization Using ESP32 Microcontroller Media

Putra,

Parjan,

Syahputra

et al. 2023

IJER

View full text Add to dashboard Cite

This paper focuses on Palembang Aviation Polytechnic cadets as students are directed to be able to form better personalities through mental, character, and physical development. Palembang Aviation Polytechnic forms the character of cadets who are disciplined, firm, and punctual. Cadets are required to take part in 8 hours of active learning by the Palembang Aviation Polytechnic's Cadet Code of Conduct (PT3). For time efficiency and ease of monitoring cadets' compliance with compulsory education, a data-based RFID tool was designed using an Arduino as an open and close system controller when a cadet taps an RFID card. Cadets are required to tap the RFID card that each individual has to ensure that cadets arrive and leave on time during learning hours. The system will not transmit data if cadets arrive before the specified time. After that, the data will be distributed to a spreadsheet as material for assessing each cadet.

show abstract

“…As we all know, with the rapid development of computer technology, intelligent control and deep learning theory have been widely applied to various research fields, such as the intelligent vehicle environment perception, smart parting, and food supply chain management in smart cities [1][2][3][4]. At present, research institutions and researchers at home and abroad have carried out extensive studies on pedestrian target detection and tracking using deep learning theory.…”

Section: Introductionmentioning

confidence: 99%

Research on Pedestrian Detection and DeepSort Tracking in Front of Intelligent Vehicle Based on Deep Learning

et al. 2022

View full text Add to dashboard Cite

In order to improve the tracking failure caused by small-target pedestrians and partially blocked pedestrians in dense crowds in complex environments, a pedestrian target detection and tracking method for an intelligent vehicle was proposed based on deep learning. On the basis of the YOLO detection model, the channel attention module and spatial attention module were introduced and were joined to the back of the backbone network Darknet-53 in order to achieve weight amplification of important feature information in channel and space dimensions and improve the representation ability of the model for important feature information. Based on the improved YOLO network, the flow of the DeepSort pedestrian tracking method was designed and the Kalman filter algorithm was used to estimate the pedestrian motion state. The Mahalanobis distance and apparent feature were used to calculate the similarity between the detection frame and the predicted pedestrian trajectory; the Hungarian algorithm was used to achieve the optimal matching of pedestrian targets. Finally, the improved YOLO pedestrian detection model and the DeepSort pedestrian tracking method were verified in the same experimental environment. The verification results showed that the improved model can improve the detection accuracy of small-target pedestrians, effectively deal with the problem of target occlusion, reduce the rate of missed detection and false detection of pedestrian targets, and improve the tracking failure caused by occlusion.

show abstract

A smart parking system using IoT

Cited by 10 publications

References 0 publications

Smart parking for smart cities: a novel approach to reducing frivolous parking zone determination

Smart parking for smart cities: a novel approach to reducing frivolous parking zone determination

SMART CADETS Prototype Design: Data-based RFID for Cadet Academic Hours Optimization Using ESP32 Microcontroller Media

Research on Pedestrian Detection and DeepSort Tracking in Front of Intelligent Vehicle Based on Deep Learning

Contact Info

Product

Resources

About