Fleet Fox
Identify the status of inbound/outbound vehicles without human intervention in a fleet
Created on 6th August 2022
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Fleet Fox
Identify the status of inbound/outbound vehicles without human intervention in a fleet
The problem Fleet Fox solves
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A working infrastructure wherein, when a vehicle passes through a checkpoint and the solution identifies as many features as it can regarding the situation of the vehicle like
o Vehicle entry/exit
o Vehicle details -
Cost effective solution that can be implemented easily within Indian markets/or similar regions.
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DarkNet Deep Learning model was used to in detection of number plate of vehicle.
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Can have a track of all vehicles details inside a particular premises such as
o AssetID - Unique identifier of the asset
o AssetName - Name of the asset (Make|SerialNumber)
o DriverName/OperatorName - Name of the asset operator
o EntryType - Type of entry/exit
o GateNumber - Number of the gate through which the vehicle entered/exit
o EventTime - Event date and time at which the vehicle entered/exit
o LatLon - Latitude or longitude of the asset
o Location - Location of the asset -
The solution can alert the management of illegal vehicle inside the premises.
Challenges we ran into
- Training Deep learning model was time consuming,
- We ran into issues related to REST API .
- We were new to Django Rest Framework and it took us quite some time to learn it.
- CORS error in API fetching using axios.
- Creating Api Logics was tough.
- Routing in React JS using React routers 6 .
Technologies used