Internet of Things (IoT) Based Micro Climate Control Optimization System for Tropical Greenhouses in Responding to Climate Change

This research aims to develop an Internet of Things (IoT) based cooling system that is integrated with Blynk, using a fan cooling system to monitor and regulate temperature, humidity and light intensity in the room. This system was evaluated for eight days by comparing sensor data with conventional measuring instruments. The results show a low coefficient of determination (R^2), indicating high accuracy in data prediction. The study found that these IoT systems effectively provide real-time data, enabling rapid response to environmental changes with an overall average error rate of less than 5%. The main advantages of this system are its ability to perform continuous cooling and data integration that facilitates monitoring and allows timely intervention. However, these systems have limitations, including fluctuations in temperature and humidity measurements. Nevertheless, this system has proven effective in monitoring and managing environmental conditions. In conclusion, IoT-based monitoring with fan cooling systems offers a powerful solution for real-time environmental data collection and provides a foundation for future research that may include the integration of additional environmental variables as well as the use of machine learning algorithms for deeper data analysis and predictive capabilities . Recommendations for future research include improving sensor accuracy and exploring advanced data analysis to improve system performance. Keywords: IoT, fan cooling system, temperature, humidity, Blynk.