The trucking industry has become a crowded marketplace for competing technologies vying for space within the truck cabin, the operations office and elsewhere in trucking business. This makes it difficult to look at solutions holistically. Especially when individual components within a convergent system may come from different suppliers.
In the case of a truck with all of the ancillary equipment fitted, there is plenty of data coming from items like dash cameras, driver facing cameras, fatigue detection devices, distraction detection devices, accelerometers monitoring harsh braking and hard acceleration, plus all of the data coming out of the vehicle’s CANbus.
“Our objective was to have one black box, and with that have the individual capability to interface at any given time with any data and bring it all together in the best way possible way for the client in order to save time and to save lives,” says Craig Forbes. “The in-cab convergence is not just about wanting all of the systems to talk to each other, it’s a little deeper than that. From a capability perspective, if there is an output on any device within the vehicle, can we make it talk to our unit.”
Quality, not quantity is needed, when it comes to the data streaming out of the truck and through a transport business’ systems. Where convergence can be very powerful is in the situation where something like artificial intelligence can monitor the streams and pull out some real strategic information which will be vital to the productive and safe running of an operation.
Systems are constantly producing a wealth of data and one of the challenges for developers is to create a system that suits trucking operators – who are looking for exceptions. They don’t need all of the data which has been streaming out of the truck, they only need information which will demonstrate whether a driver or a truck has been fully compliant and to keep a record of exceptions when required.
In the past, the emphasis has been on just getting the information out of the truck, but, in fact, the real strength of all of this data is not that it is there and available. It becomes more useful when it is interpreted within a system and made to improve the function of the entire operation.
It will be important to focus on a small segment of the data which relates to issues, interactions and transactions. The problem is wading through a mountain of data to find the important nuggets of information. Data not only needs to filtered it also needs to be interpreted so that anyone managing an operation will only need to be involved when an organic decision needs to be made.
The task of the telematics provider it’s not necessarily about the quality of the equipment provided and the ability to extract a lot of data out of a truck and other parts of the business. The most important task is to ensure it presents the information in a usable way to the operator to help them make their business more efficient, safer or simply better.
“Extracting the gold and presenting it to the operator helps give them the nuggets of information which they will need in order to address any issues that they may be in the operation,” says Craig.
In terms of convergence, this data can be pulled together and each set of data can be integrated with others to which it relates. For instance, if the accelerometer registers a hard braking event, this data can be compared to what is happening on the CANbus of the vehicle plus any distraction detection devices and the data from the driver facing camera. This convergence of information should help the system decide whether someone back at base needs to be informed.
Parameters need to be developed to categorise events and then to rank them in order of importance, and then decide to whom and when any details need to be presented in a dash board.