Data-driven decision-making presents new prospects to boost agricultural output as a result of the Internet of Things’ (IoT) rapid progress. An IoT- enabled smart farming system that combines sensor networks and meteorological data to optimize irrigation and track crop health is presented in this study. The meteorological department gathers weather information, such as temperature and humidity, at hourly and daily intervals, with a focus on the area a few kilometers from the farmer’s field. With the use of ESP32 and LoRa modules, this data is sent to a central Raspberry Pi device, which can travel up to 15 km. Furthermore, the Raspberry Pi stores locally collected field data from the farmer, such as crop kind and soil properties. Temperature, humidity, and soil moisture sensors are used to track field conditions in real time. The solution helps farmers make well-informed irrigation decisions by combining this data. Additionally, crop health and growth are tracked using image processing tools, which allow for the early identification of possible problems. The goal of this smart farming solution is to give farmers useful information that will help them manage crops more effectively, use water more efficiently, and eventually produce better agricultural results.