Fleet Operation Predictive Maintenance (PdM)
Reduce road casualties using combined IoT and AI technologies. Helps local transit operators visualize their fleet's real-time driving quality, monitor sign of dangerous behavior, predict and warn driver about imminent accident before it happens.
Business Overview
With the conventional schedule-centric maintenance methods becoming obsolete, fleet managers whose priorities have shifted more toward modernizing and improving fleet maintenance.
Sensor AI partnered with a leading logistics operator to develop tailored Predictive Maintenance (PdM) solution for taking care of its 120 long-distance trucks operating round the clock.
Leveraging the modern digitalized vehicle telemetry, we built a proactive upkeep strategy that tracks vehicle and asset health and uses Machine Learning and statistical analytics to forecast when vehicles and assets will need maintenance so they can be addressed before breakdowns occur.
PdM has proven to boost the efficiency of a fleet and minimize downtimes and operational expenses.
Real-time vehicle fleet stats
By collecting on-board diagnostics and real-time vehicle operating telemetry streamed from digitized vehicles, our solution allow operators to manage the whereabouts of each vehicle as well as poin-in-time engine operating statistics.
Anomaly detection
Use sophisticated analytical models to find pattners and warning signs of potential vehicle failures, Our pdM solution manages to uncover defects, identify potential engine malfunctions and other issues that could hinder fleet health and disrupt operations before they occur.
Architectures
Relying on a combination of sensing devices, Internet of Things (IoT), machine learning (ML) and streaming data processing technologies, we built a robust and scalable PdM architecture on cloud in just 2 months.
