It’s been a while we are talking about Connected Vehicle and their benefits in the Logistics sector.
- Vehicle Utilization and Routing
- Real time Tracking etc
But with increased technology advancement, people are looking at the next level features .
First in the list from the business standpoint, is safety both from Vehicle and Driver standpoint. Calculating Driver fatigue, which can happen in many ways.
- Smart devices/wearables.
- Monitoring Eye movement and actions with real time camera feed and machine learning.
- Dash cams to monitor traffic and alerting driver.
Automated scheduling not only based on lowest cost or distance also checking for best fit. Most fleet management software today consider idle trucks and minimum distance to allocate trucks for the job. But today with machine learning, the software can take care of Vehicles already on route to the specific location, Vehicle’s home location and their preference of load and destination. Even it can plan ahead to create a connected trip which can get the driver back to his home location so that they can enjoy time with their families during their Time off period.
Finally the most important piece in the puzzle to solve is multi modal shipments. For cost benefits people use multiple mediums such us Road, sea and trains to deliver their goods in a single shipment. Current software mostly handle point-to-point loads. But for logistics companies that poses a very big challenge. New softwares with the machine learning can even suggest just like the google map which route take for most efficient and low cost routes.
Example of Multi Modal Logistics
On the technology side, Next wave of software’s are focusing more on securing the software so that they are less prone to hacks. But with tight security portability of the software becomes very limited. So companies are trying find out the best solution where people can use the choice of their technology but get the best in class software they need to be successful.
Machine Learning is become a large factor in this whole eco system. We talked about usage of machine learning just a while back, but machine learning is now also used to predict demand and making sure enough # of vehicles are available in that region to handle the load. That’s good for business as well as it reduces are adhoc nature of drivers job making sure their lives are also more predictable.
Finally getting towards a more integrated system, Right now logistics software run independently focusing mostly on one thing. But that is not enough, broken experiences between their booking, invoicing, logistics and CRM system is making it a very painful experience for them and most importantly for their customers. Creating a software which works and integrates well to the existing platforms of the operator is going to be key and will bring the required digital transformation in this space