An Advanced Fleet Management System for Trucking Companies 

Introduction

As a reputable software development vendor with significant expertise in the automotive industry, Avenga has consistently strived to push the boundaries in the areas of transportation and fleet management. 

With this objective in mind, we conduct thorough research and development activities in the automotive field, focusing on designing and engineering cutting-edge solutions that enhance driving safety and provide trucking companies with a competitive advantage. We have also collaborated with many industry-leading software companies, including Intel, on numerous automotive projects in the automotive and other industries. 

Notably, one of our fleet management initiatives has generated interest from local municipalities in Cordoba, Argentina, where one of our delivery centers is based. The work we have undertaken demonstrates considerable potential in terms of elevating driver monitoring, improving driver safety, and increasing fleet management efficiency. 

Challenge 

With cities worldwide undergoing rapid development, trucking companies are under mounting pressure to enhance fleet management, including tracking and coordinating driver and fleet behaviors. 

To address modern transportation needs, they need sophisticated fleet management tools, which could help streamline processes, prevent dangerous situations and, ultimately, increase their competitive advantage. In light of this, Avenga has decided to engineer an ML-based, non-ADAS tool tailored to these industry-specific requirements.  

Solution

Process

Discover

An in-depth review pinpointed pressing challenges in the trucking industry. Safety and efficiency gaps were clearly defined. 

Research findings laid the blueprint for innovation. Critical insights drove the vision for a tailored solution. 

Define

Collaboration with Intel sparked a detailed mapping of requirements. Key features for driver monitoring and fleet operations emerged. 

Design criteria focused on simplicity and robustness. The plan aligned technical feasibility with industry needs. 

Develop

Leveraging Intel’s OpenVino and cloud-edge capabilities fueled groundbreaking development. A state-of-the-art system was built for real-time insights. 

Predictive safety features were integrated to proactively mitigate risks. Seamless performance and scalability became core attributes. 

Deliver

The proof of concept (PoC) was finalized and rigorously optimized for real-world use. Fatigue detection and near-miss tracking were finely tuned. 

The well-structured, scalable system elevates driver safety and streamlines operations. A solid foundation for future applications was successfully established. 

Results

• We delivered a proof-of-concept (PoC) for an end-to-end fleet management solution that can optimize trucking companies’ processes, improve driver safety, and enhance their competitive edge. 

• This PoC has already gained the attention of the municipal authorities in Cordoba, Argentina, where our delivery center is located, and demonstrated significant potential for real-world applications. 

• We also engineered a powerful near misses detection system that employs machine learning algorithms to identify potentially hazardous situations at city intersections. 

• Finally, we achieved the integration of driver management and the near detection systems into Intel’s IoT DevCloud platform.

Explore what’s possible when safety and smart tech go hand in hand. 

Let’s talk

The PoC we have developed exhibits substantial potential for a wide range of real-world use cases. Specifically, it can assist truck drivers and help trucking companies address the changing transportation demands.