This research aims to develop and implement a tree felling age detection device using piezoelectric sensors in urban forests. Urban forests play an important role in maintaining environmental quality and the well-being of urban communities. Despite the many benefits provided by trees, such as oxygen production and carbon dioxide absorption, the health condition of trees is often difficult to identify visually. Traditional methods of determining tree age, such as dendrochronology, are destructive and time-consuming, so a fast and accurate non-destructive method is needed. Piezoelectric sensors offer the potential for non-destructive detection of tree age by measuring the physical characteristics of trees that change with age, such as wood density, hardness and moisture content. The research involved sensor selection and calibration, data collection from trees in an urban forest, and signal processing and analysis to associate the extracted features with tree age. Test results show that the device can provide real-time tree age estimation, supporting sustainable urban forest management. This research also highlights the importance of integrating sensor technology with a comprehensive urban forest management system for better decision-making regarding tree planting, maintenance and felling.