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Brief

A modern logistics company must deliver more value to customers in order to increase revenues and customer satisfaction. The problem is that margins are tight so the operations costs must be optimized.

Business case

Any logistics company deals with lot of operations costs: drivers, fuel, maintenance are the top ones. There's room for cost optimization, but first data from the field must be collected.
On the other hand their customers, companies, are expecting top level services such as realtime monitoring and, in some cases, datalog reports for each shipment.
A simple GPS tracker is not enough to solve the whole business case, so Iomote X400 gateway plus some extra sensors has been the best choice for

Hardware Setup

The main controller of the whole system is Iomote X400 gateway with 3G connectivity. This is installed inside the cab of the truck and powered directly from the vehicle battery.
Each modern vehicle has a communication port (OBD) and with a commercial OBD to serial converter the X400 is able to read vehicle parameters such as fuel level, engine rpm, speed and others.
A professional active GPS has been interfaced to X400 with a simple 2 wires serial UART.
For the pallet monitoring a battery-powered, wireless 868Mhz sensors have been selected. These sensors are sending data to a receiver that is connected to the X400 gateway via RS232 connection.
That's it, this is the whole hardware setup.
Then all the logic has been developed and running on the Arduino-compatible App processor inside X400. Dare are packed in a simple Json format and sent, with a timestap, to the Cloud.

Application

A web application has been developed quite easily leveraging on the data coming from the field. The application serves several users: the logistic company IT department and the final customer that can receive a link to monitor each shipment on a map, in realtime.
Plus an integration engine has been created in order to connect data from OBD and GPS to an driving optimization software that analize the drivers performance to highlight the best drivers that are saving fuel. Leveraging on these data the company is now training and rewarding its drivers to save on fuel.
Data are also crossed with maintenance routines to create automatic alerts to drivers when their vehicle is needed to stop for garage operations in order to avoid costly unexpected reparations.

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