  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 great precision and minimal human interaction. This paper
discusses, 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 QR codes 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 procedure significantly improves accuracy as well as the
assessment of cutting-edge technology and existing techniques.
