This follow-up study builds upon a prior publication investigating automotive exhaust aftertreatment systems, focusing on advancements made in response to avoiding early Diesel Particulate Filter (DPF) failure. This article is named “A driver-assist system for efficient DPF regeneration”. Through hardware updates and firmware modifications, the framework pre-sented in the previous study has been refined to adapt to evolving vehicle da-ta acquired from On-Board Diagnostics (OBD). In cases where specific DPF information remains inaccessible due to manufacturer constraints, the system integrates a further improved Fuzzy Logic algorithm to process alternative da-ta sources. The updated system offers enhanced communication capabilities, deliver-ing real-time insights into ongoing regenerations, DPF health status, and pre-dictive analysis of regeneration cycles, informing the driver through an inte-grated Thin-Film-Transistor (TFT) display. Additional road tests were per-formed to validate the system performance, demonstrate significant im-provements in preventing DPF obstructions and optimizing overall system ef-ficiency. This follow-up research presents advancements in detecting ongoing regen-erations more accurately, showcasing the successful integration of hardware and software updates to achieve the primary objective of prolonging DPF lifespan. The experimental tests conducted in real environment and presented ena-bled the validation of the system in terms of its operability and applicability.