The hardware part is based on the installation of cameras on viewpoint rams and IoT devices containing GPS trackers and sensors on each truck.
The software part is developed in the form of a complex web application that provides the required real-time analysis of the data received from them and namely:
- Video streams that allow detecting each particular vehicle's arrival and departure from the selected ramps to detect reasons for occasionally appeared delays.
- GPS data allows tracking time and location of the truck on the road to ensure the route and delivery period conformity with the one approximated during planning.
- Device info allows discovering any malfunctions or breaks concerning connectivity or devices timely to avoid receiving incorrect data or their complete absence.
IoT fleet management solution provides managers and board members with custom scheduled or on-demand analytical reports.
ML Fleet Management System
About Project
Our team created a complex truck monitoring solution to ensure timely delivery and optimal vehicle usage for the bakery manufacturer.
The project is built using machine learning algorithms based on Python programming language and OpenCV technology.
The project is built using machine learning algorithms based on Python programming language and OpenCV technology.
Client's goal
The main product idea was to raise the level of service by ensuring on-time reception of the goods supplied to the local vendors within the operated region.
At the same time, the client's goals were to make sure that company truck drivers didn't spend unnecessary time loading and that vehicles were used effectively.
At the same time, the client's goals were to make sure that company truck drivers didn't spend unnecessary time loading and that vehicles were used effectively.
About Project
Our team created a complex truck monitoring solution to ensure timely delivery and optimal vehicle usage for the bakery manufacturer.
The project is built using machine learning algorithms based on Python programming language and OpenCV technology.
The project is built using machine learning algorithms based on Python programming language and OpenCV technology.
Client's goal
The main product idea was to raise the level of service by ensuring on-time reception of the goods supplied to the local vendors within the operated region.
At the same time, the client's goals were to make sure that company truck drivers didn't spend unnecessary time loading and that vehicles were used effectively.
At the same time, the client's goals were to make sure that company truck drivers didn't spend unnecessary time loading and that vehicles were used effectively.
Product
Result
The product resulted in the minimization of the number of delays during everyday deliveries through the increase of related KPIs and the whole process's cost-efficiency in the long run.
The solution integration also allowed avoiding inconvenient fulfillment of partnership agreements and expenses spent on the irresponsible workforce, fuel, etc.
The solution integration also allowed avoiding inconvenient fulfillment of partnership agreements and expenses spent on the irresponsible workforce, fuel, etc.
Just take a look
The project is under NDA, so all the demonstrated materials are as close as possible, but do not repeat the original.
Desktop
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