BANF and Silicon Labs Develop Real-Time Tire Monitoring System for Autonomous and Connected Fleet Vehicles

Why It Matters

The solution transforms tires into active data nodes, enabling autonomous fleets to improve safety, reduce downtime, and unlock new revenue streams through advanced analytics.

Key Takeaways

• Real-time tire data at thousands of samples per second
• BG22 SoC provides ultra‑low‑power Bluetooth LE connectivity
• Wireless power eliminates battery constraints inside tires
• Secure Vault safeguards data against tampering
• Enables predictive maintenance and fleet optimization

Pulse Analysis

The rise of autonomous and connected fleets has turned every vehicle component into a potential data source. Conventional tire pressure monitoring systems (TPMS) merely flag low pressure, offering little insight into the dynamic forces that affect safety and efficiency. As vehicles generate terabytes of sensor data, the tire—subject to friction, load, and temperature variations—remains one of the most under‑utilized nodes. Capturing high‑resolution telemetry in real time is now essential for algorithms that manage traction, energy consumption, and overall vehicle health. Regulators are also pushing for richer tire diagnostics to meet upcoming safety standards.

BANF’s partnership with Silicon Labs addresses this gap by embedding a BG22 ultra‑low‑power Bluetooth LE system directly inside the tire. The SoC processes acceleration, pressure, temperature and tread‑depth signals at thousands of hertz, performing edge analytics that filter out noise before transmission. A proprietary wireless power profiler mounted on the fender supplies continuous energy, removing the need for batteries that would otherwise fail under centrifugal stress. Secure Vault encryption further protects the stream from spoofing, meeting the stringent cybersecurity standards required for autonomous operation. The modular design allows OEMs to retrofit existing fleets without major redesign.

The immediate business impact lies in turning tires into predictive maintenance assets. Continuous condition data enables fleet managers to schedule replacements before wear‑related failures, reducing downtime and warranty costs. Combined with route‑optimization algorithms, the intelligence can adjust tire pressure on the fly to improve fuel efficiency and extend tire life. Insurers are also eyeing the granular telemetry for usage‑based policies. As more OEMs adopt edge‑enabled sensors, the market for smart‑tire solutions is poised to expand rapidly, reshaping vehicle economics and safety standards. Analysts project the smart‑tire market to exceed $1 billion by 2030, driven by autonomous adoption.