Built a purpose-designed transport management platform for Australian logistics providers with real-time asset tracking, driver fatigue compliance and revenue optimisation dashboards.
Transport and logistics operators in Australia face a specific set of operational constraints: fatigue management regulations that govern driver hours, complex asset utilisation tracking across variable load schedules and the commercial pressure to maximise revenue per vehicle per day while maintaining safety compliance.
Our client was building a purpose-designed platform for this market. The core challenge was that existing transport management systems were either too generic - built for global markets and not tuned for Australian compliance requirements - or too expensive for mid-market operators who needed the same capabilities.
Dispatch and job management (Node.js / Express)
The dispatch module manages job creation, vehicle assignment and driver scheduling. Key workflows include job creation with pickup and delivery locations, load type, weight and time windows; driver assignment with automatic conflict checking against existing bookings and working hours; and an electronic job diary where drivers record job milestones from a mobile view, creating a timestamped audit trail.
The backend was built on Node.js with PostgreSQL, hosted on Google Cloud Platform. Cloud SQL managed the database, with Cloud Run handling the API services for auto-scaling without container management overhead.
Driver fatigue audit system
Australian heavy vehicle fatigue management regulations define maximum work hours and minimum rest periods in specific patterns. Violations carry regulatory consequences.
We built an automated fatigue audit that evaluates each driver's planned and actual hours against the applicable ruleset for their accreditation level. The audit runs on completed job data to flag potential breaches and on proposed schedules before assignment to prevent creating non-compliant rosters.
Regulatory fatigue rules involve complex time-window calculations - cumulative work hours across rolling 24-hour, 7-day and 28-day windows with different limits depending on rest intervals taken. The rule engine was designed as a data-driven evaluation layer rather than procedural code, so rule parameters can be updated when regulations change without requiring code changes.
Asset utilisation and revenue dashboards (React)
The management dashboard surfaces real-time metrics for vehicle utilisation - hours loaded versus available hours, kilometres per day - and revenue performance including revenue per load, revenue per kilometre and empty kilometres as a percentage.
Dashboard data is aggregated from job completion records in near real time. We structured the aggregation queries to pre-compute daily summaries on job close rather than aggregating raw records on every dashboard load, keeping response times fast regardless of historical data volume.
Cloud Run was specifically chosen to avoid managing a Kubernetes cluster for a service with significant traffic spikes around shift start and end times. The scale-to-zero behaviour handles overnight quiet periods without idle infrastructure cost.
The fatigue rule engine as a data-driven evaluator was an important design choice. Fatigue legislation changes periodically. Hardcoding rule parameters would mean code changes for every regulatory update. Storing the parameters in configuration tables means an operator or compliance team can update thresholds without a deployment.
The platform launched to an initial operator cohort in Australia. The fatigue audit system caught scheduling conflicts during the first week of live use - cases where a dispatcher had manually created a roster that violated rest period requirements. The dispatch team used real-time dashboards to reallocate vehicles mid-day based on actual utilisation data, improving revenue per vehicle for the pilot operators.