In the rapidly evolving digital era, smart devices play a critical role in daily life, yet efficient and automated tracking of device usage remains a significant challenge. Inspired by the operational principles of vehicle speedometers and odometers, this study proposes a mathematical modelling framework for cumulative usage tracking in intelligent electronic devices. The research investigates how dynamic measurement systems, traditionally used in vehicles to record distance as the time integral of velocity, can be adapted to model real-time usage behaviour in smart gadgets.

The proposed model represents device activity as a time-dependent function, where cumulative usage is formulated as an integral of activity rate over time. Using concepts from applied mathematics, dynamical systems, and signal modelling, this study develops a generalized mathematical structure capable of capturing continuous and discrete usage patterns. The framework incorporates sensor-driven input signals, temporal data accumulation, and algorithmic tracking mechanisms to simulate speedometer-like behaviour in modern devices.

Furthermore, the model explores potential applications in smart technology, including smartphones, IoT systems, wearable devices, and automated monitoring platforms, where accurate usage quantification is essential for performance optimization and resource management. The proposed approach contributes to the interdisciplinary intersection of mathematical modelling, computational intelligence, and intelligent system design.

This research aims to establish a theoretical foundation for automated cumulative tracking mechanisms in next-generation smart devices, offering a scalable and mathematically rigorous solution aligned with emerging trends in artificial intelligence and digital instrumentation.