With the apps like fleet management system (FMS), it is possible to observe driver’s behaviour in real-time and make a training plan
By Sumit Sharma
The Logistics sector has always been one of the most growing sectors and a laggard in the adoption of technology. But the advent of latest technologies like IoT, Artificial Intelligence (AI), and Machine Learning (ML) have set this sector on a path, which is soon going to not just transform the sector but also will give rise to a whole new breed of paradigms. Now, as the demand for logistics companies is growing, the driver’s safety has become a primary concern.
With the apps like fleet management system (FMS), it is possible to observe driver’s behaviour in real-time and make a training plan which can also solve the issue of employee’s long driving hours and breaks between drives with fully automated fleets. The availability of sensors and Bluetooth wireless technologies in the trucks have made it easier to add trucks to this burgeoning online network of supply chain data, providing last-mile visibility that was previously unattainable.
Logistics companies are using GPS systems and AI to track the location of their trucks, they can now set up geofences to enable alerts when a truck is nearing its destination, danger, optimise routes using real-time traffic data, improve vehicle utilisation, and automatically track driver hours and fuel tax reporting information. A user-generated input via smartphones is sent onto the drivers which helps them to know the route around construction or congested areas. So that they can avoid these routes and take an alternative route.
ML is also helping the logistics companies to get minute by minute details of the trucks. So that immediate action can be taken at the time of any mishappening. Every driver has an app that automatically clocks them in when they get into a truck and keeps track of their hours, keep the track when they reach to the warehouse or to the changing hub.
Firms have started using this technology for Fuel optimisation, Operational Planning & allocation based on Geospatial & status data, dynamic route management and control. In situations like human errors, traffic or accidents, AI predicts decisions based on data analysis and help to avoid accidents and maintain their safety.
(The author is the co-founder of GoBOLT, an end-to-end logistics service provider based out of New Delhi.)