Designing an Intelligent Parcel Management System using IoT & Machine Learning

Abstract

Parcels delivery is a critical activity in railways. More importantly, each parcel must be thoroughly checked and sorted according to its destination address. We require an efficient and robust IoT system capable of doing all of these tasks with high accuracy and minimal human interaction. In this paper, We created a fully-fledged solution using IoT and machine learning to assist trains in performing this operation efficiently. In this study, we covered the product, which consists mostly of two phases. Scanning is the first step, followed by sorting. During the scanning process, the parcel will be passed through three scanners that will look for explosives, drugs, and any dangerous materials in the parcel and will trash it if any of the tests fail. When the scanning step is over, the parcel moves on to the sorting phase, where we use RFID to retrieve the details of the parcels and sort them properly. The simulation of the system is done using the blender software. Our research shows that our methodology significantly enhances both accuracy and the review of cutting edge technology existing techniques.

Status - Published
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