Back close

Conceptual approach on smart car parking system for industry 4.0 internet of things assisted networks

Publication Type : Journal Article

Source : Measurement: Sensors, Volume 24, December 2022

Url : https://www.sciencedirect.com/science/article/pii/S2665917422001088#!

Campus : Chennai

School : School of Engineering

Department : Computer Science and Engineering

Verified : No

Year : 2022

Abstract : The deployment of Internet of things (IoT) technology has enhanced various applications in scientific disciplines such as medical, agriculture, social sciences, and computer sciences, as well as non-scientific sectors such as government, society, and industry, among others. IoT manifests itself in a variety of fields that are divided into categories based on the issues that may be handled, such as health, agriculture, networks, cities, and sports. Parking guidance development entails the creation of an IoT-based system that transmits information about available and occupied parking spaces via a web/mobile application. Each parking space has an IoT gadget, which includes sensors and embedded systems. The user is given a real-time update on the availability of all parking spaces and is given the option to pick the optimal position. This study is centered on fully automated parking area utilizing image analysis, as well as or before parking places with sensing and OTP generating. The car park reduces the need for user interaction, increases wage costs, and allows for space well before. The Autonomous Vehicle Parking System allows users to park their cars without the need for human interaction and operates 24 h a day, seven days a week. The Pre-Booking software allows the user can reserve a parking space via this app, reducing the customer's time spent hunting for a parked spot and energy usage. There is still a notification that shows if a space is reserved or available.

Cite this Research Publication : Suthir, Nivethitha, et.al., “Conceptual approach on smart car parking system for industry 4.0 internet of things assisted networks”, in Measurement: Sensors, Volume 24, December 2022, https://doi.org/10.1016/j.measen.2022.100474

Admissions Apply Now