Development an Web-Based Application for Predict Broiler Chicken Growth with LSTM model

This article introduces the development of an application system utilizing the Long Short-Term Memory (LSTM) model for the prediction of broiler chicken growth. By harnessing time-series data, including daily weight, feed intake, and environmental conditions, the system is designed to meticulously track the entire broiler production process, from the onset of rearing to the point of slaughter, organized into several functional modules. In addition to integrating essential functional modules, the incorporation of the LSTM model aims to enhance agricultural management's ability to monitor the growth conditions of broiler chickens. This enables a dynamic adjustment of feed intake and the regulation of growth environments, thereby optimizing poultry farming operations with a high degree of precision and professionalism.