Design and Implementation of Energy-Efficient Wireless Tire Sensing System with Delay Analysis for Intelligent Vehicles
Shashank Mishra, Jia-Ming Liang
TL;DR
The paper designs an energy-efficient wireless tire sensing system (WTSS) for intelligent vehicles and develops a formal analytic scheme to bound the worst-case sensor transmission delay under wake/sleep scheduling and collision probabilities. It distinguishes cases based on the gcd between the sensor duty-cycle and the wake-sleep cycle, deriving closed-form expressions for the worst delay $W_{delay}$ and the total expected delay $E[W_{delay}^{total}]$, and validates results with simulations and field trials. The work demonstrates substantial energy savings via sleep periods while preserving real-time data delivery, supported by a cloud-based management system and multi-network connectivity. Practical impact includes safer, more fuel-efficient vehicular operation and a framework adaptable to other real-time, sensor-driven automotive applications. Avenues for future work include enhancing transmitter energy efficiency and expanding prototype validation across diverse vehicle platforms.
Abstract
The growing prevalence of Internet of Things (IoT) technologies has led to a rise in the popularity of intelligent vehicles that incorporate a range of sensors to monitor various aspects, such as driving speed, fuel usage, distance proximity and tire anomalies. Nowadays, real-time tire sensing systems play important roles for intelligent vehicles in increasing mileage, reducing fuel consumption, improving driving safety, and reducing the potential for traffic accidents. However, the current tire sensing system drains a significant vehicle' energy and lacks effective collection of sensing data, which may not guarantee the immediacy of driving safety. Thus, this paper designs an energy-efficient wireless tire sensing system (WTSS), which leverages energy-saving techniques to significantly reduce power consumption while ensuring data retrieval delays during real-time monitoring. Additionally, we mathematically analyze the worst-case transmission delay of the system to ensure the immediacy based on the collision probabilities of sensor transmissions. This system has been implemented and verified by the simulation and field trial experiments. These results show that the proposed scheme provides enhanced performance in energy efficiency and accurately identifies the worst transmission delay.