I-POST: Intelligent Point of Sale and Transaction System
Farid Khan

TL;DR
I-POST is an automated, intelligent point-of-sale system utilizing machine learning and facial recognition to streamline shopping by enabling users to walk in, collect items, and exit without queuing.
Contribution
The paper introduces a novel POS system that leverages CNN-based object detection and facial recognition for real-time, automated checkout, improving efficiency over traditional systems.
Findings
Object recognition accuracy of 97%
System enables queue-free shopping experience
Potential for broad application in retail environments
Abstract
We propose a novel solution for the cashier problem. Current cashier system/Point of Sale (POS) terminals can be inefficient, cumbersome and time-consuming for the users. There is a need for a solution dependent on modern technology and ubiquitous computing resources. We present I-POST (Intelligent Point of Sale and Transaction) as a software system that uses smart devices, mobile phone and state of the art machine learning algorithms to process the user transactions in automated and real time manner. I-POST is an automated checkout system that allows the user to walk in a store, collect his items and exit the store. There is no need to stand and wait in a queue. The system uses object detection and facial recognition algorithm to process the authentication of the client and the state of the object. At point of exit, the classifier sends the data to the backend server which execute the…
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Taxonomy
TopicsSmart Parking Systems Research · Vehicle License Plate Recognition · Advanced Manufacturing and Logistics Optimization
MethodsConvolution
