Due to climate change, Spodoptera litura has the potential to become an increasingly severe pest because of increased habitat suitability. To support precision agriculture, it is essential to accurately predict the life cycle of Spodoptera litura, and use the information for pest control. This paper proposes BugTalk to predict the life of Spodoptera litura (Common Cutworm). Based on the Internet of Things (IoT) technology, BugTalk is a real-time prediction version of modified Insect Life Cycle Modeling software (ILCYM), an open-source software package that implements the functions used in the four models of the four life stages of Spodoptera litura. In this paper, we significantly improve the ILCYM functions and several models of the previous studies to improve the accuracy of the prediction. We develop the first real-time prediction system that can predict the number of Spodoptera litura for the farm fields in real-time. The results are compared with the measurements during 2014-2020. We extend the temperature-based ILCYM model to accommodate humidity for the larvae emergence stage, which further improves the accuracy of the model. The Mean Arctangent Absolute Percentage Error (MAAPE) between the measurements and the BugTalk prediction is 24.593%. This result has been practically utilized in farm management.