Punctuality and reliability are among the most important criteria when it comes to choosing Public Transport. 

Pilotfish Bus Insight is your comprehensive off-board diagnosis system – providing deeper insights into a bus’s condition, covering both the driveline and its main components as well as the IT systems. Simply put, you no longer have to use various systems for the same level of overview and control.

Bus Insight provides one single platform where you can review and analyze all parameters affecting your fleet.  It opens the door to condition-based maintenance by using data more wisely across all operational aspects.

  • Corrective maintenance becomes more efficient
  • Better anticipation and planning becomes easier
  • Preventive maintenance is enabled
  • Improves communication to and from driver – leading to increased commitment

Bus Insight helps to plan operations and reduce down time. Bus Insight comes with three different features providing a 360 picture to support your operations:

Alerts

With the Bus Insight Alerts, you benefit from instant and pan-organizational awareness of vehicle misbehaviors, through desktop monitoring as well as SMS and e-mail.
Your daily bus operation will also work more efficiently through by providing drivers with checklists and the possibility to manually report issues.

Inventory Service

The Inventory feature within Bus Insight supports you to identify and name any of your on-board IT-equipment and to monitor available status. We provide full support for inventory management of any ITxPT equipment.

Inventory helps you to label your ITS equipment and to work more efficiently when an equipment reports failure or is disconnected.

Dashboards & Reports

Bus Insight provides the possibility to build customizable dashboards for deeper insights in operation and vehicle condition. More importantly – with the assistance of Pilotfish expertise, we can analyze the data and optimize your operations.

By tracking the most relevant KPI:s for optimized maintenance & service, you will increasingly be able to predict maintenance needs.