IoT Based Economic Smart Vehicle Parking System

Patil, Minal; Chakole, Vijay; Chetepawad, Krushna

doi:10.1109/iciss49785.2020.9315919

Cited by 18 publications

(2 citation statements)

References 5 publications

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“…With this solution, users can rapidly search for nearby parking lots as well as the current availability in each parking lot. The recommended system [33] implemented using the Arduino-Uno board, and the suggested technique is implemented by connecting the parking lot to the internet or other online resources using Node-MCU. To collect information about available parking spots, the recommended method places an infrared sensor in each slot.…”

Section: IImentioning

confidence: 99%

Real-Time Parking Assistance using Arduino and Sensors

Bhatti¹,

Rai²,

Siddiqui³

et al. 2023

IJRASET

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Automated Parking System can fulfil parking operations quickly and safely without wastage of time and energy. This study describes a scale model of an automated parking system with an LCD screen that can regulate and manage the number of vehicles that can be parked in a certain area at any given time based on the availability of parking spaces. The employment of sensors during car entry and exit is known as automatic parking. Most current systems aren't fully automated and require some amount of human interference or interaction in or with the system, according to our analysis of a few of the existing systems. We have examined some of the existing systems, and the results indicate that most of them aren't fully automated and need some amount of human involvement.

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Section: IImentioning

confidence: 99%

Real-Time Parking Assistance using Arduino and Sensors

Bhatti¹,

Rai²,

Siddiqui³

et al. 2023

IJRASET

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“…Also, these devices are expanding rapidly and playing a pivotal role in human daily life. They have been used in many applications such as smart city, home, and car applications [1]- [3]. Consequently, there will be a community of interconnected smart things sharing and exchanging data in the world.…”

Section: Introductionmentioning

confidence: 99%

Intrusion detection method for internet of things based on the spiking neural network and decision tree method

Zarzoor¹,

Al-Jamali

Qader

2023

IJECE

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The prevalence of using the applications for the internet of things (IoT) in many human life fields such as economy, social life, and healthcare made IoT devices targets for many cyber-attacks. Besides, the resource limitation of IoT devices such as tiny battery power, small storage capacity, and low calculation speed made its security a big challenge for the researchers. Therefore, in this study, a new technique is proposed called intrusion detection system based on spike neural network and decision tree (IDS-SNNDT). In this method, the DT is used to select the optimal samples that will be hired as input to the SNN, while SNN utilized the non-leaky integrate neurons fire (NLIF) model in order to reduce latency and minimize devices’ power usage. Also, a rand order code (ROC) technique is used with SNN to detect cyber-attacks. The proposed method is evaluated by comparing its performance with two other methods: IDS-DNN and IDS-SNNTLF by using three performance metrics: detection accuracy, latency, and energy usage. The simulation results have shown that IDS-SNNDT attained low power usage and less latency in comparison with IDS-DNN and IDS-SNNTLF methods. Also, IDS-SNNDT has achieved high detection accuracy for cyber-attacks in contrast with IDS-SNNTLF.

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