Predictive Maintenance Telematics & Analytics Platform

Background
The City of Long Beach is seeking proposals from qualified vendors to provide an advanced predictive maintenance telematics and analytics platform. This initiative aims to leverage real-time vehicle data, artificial intelligence, and predictive modeling to reduce downtime, improve reliability, and optimize maintenance operations for the City’s fleet managed by the Fleet Services Bureau.

The Bureau oversees a diverse fleet that includes light-duty cars, heavy-duty trucks, and specialized equipment essential for daily city operations.

Work Details
The awarded vendor will implement a complete predictive maintenance telematics and analytics system that utilizes real-time vehicle data and predictive analytics to identify early signs of problems, forecast component failures, prioritize fault codes, and recommend maintenance actions. The platform must integrate with existing telematics systems and support condition-based maintenance.

Key deliverables include:
- Implementation plan with milestones and risk management strategies.
- Supply of telematics hardware or confirmation of integration with existing devices.
- Deployment of an open standards-based API for integration with the City’s Fleet Management Information System (FMIS).
- Operational data pipelines supporting engine diagnostics and predictive sensor data.
- Training for City staff on system usage and administration.
- Ongoing support including performance reviews and updates.

Period of Performance
The contract will be for a period of two years with an option to renew for three additional one-year periods, totaling a maximum of five years.

Place of Performance
The services will be performed in Long Beach, California.

Bidder Requirements
Proposers must have at least three years of experience delivering predictive maintenance or telematics solutions in complex fleet environments. It is highly desirable that proposers have completed at least three comparable deployments within the past five years. Proposals must include references detailing project scope, fleet size, implementation dates, and contact information.