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Low Cost Parking System For Smart Cities: A Vehicle Occupancy Sensing And Resource Optimization Technique Using Iot And Cloud Paas
[Full Text]
AUTHOR(S)
Ayaskanta Mishra, Abhijit Karmakar, Abhirup Ghatak, Subhranil Ghosh, Aayush Ojha, Kaustav Patra
KEYWORDS
Vehicle Parking, Smart Cities, IoT, Vehicle Occupancy Sensing, Platform as a Service (PaaS), Cloud, Resource Optimization, Sensors, Cyber-Physical System, Dynamic Parking Tariff
ABSTRACT
Modern smart city is facing numerous technological as well as administrative challenges in many fronts involving man and machines. One of these is the smart transportation system aided with cutting edge public transit modes like bus, monorail, metro and so on so forth. However needless to say only having an adequate public transport system will not suffice the need of end to end mode of transport. Hence an efficient and hassle free parking system is inevitable for any modern day smart city. With advancements of technologies like Internet of Things (IoT) and cloud platforms it is now technologically feasible to design and deploy systems to incorporate automation in traditional parking systems and hence making vehicle parking more organized and hassle-free and would require very less human interventions. In this paper, a Low cost IoT based vehicle parking system for smart cities is proposed using a cloud computing model: Platform-as-a-Service (PaaS). A HCSR-04 based ultrasonic sensor in used to detect the proximity of a car in a parking slot to detect the status of occupancy of a slot in the parking zone. An IR sensor in deployed at the Entry and Exit gate to sense the number of car in the parking zone. This prototype and proof of concept has been designed using Arduino UNO aided with an ESP-32 NodeMCU for sending the sensor data to a ThingSpeakTM cloud. A Blynk Android app PaaS is used to give user notification for the availability of parking online to users. A resource optimization technique is proposed based on the real time sensor data. This optimization technique would aid in a dynamic parking tariff and load balancing strategy for parking spaces in smart cities.
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