Effective utilization of embedded system and sensors with Wireless data monitoring for investigation of irrigation scheduling for Sugarcane crop

In this advanced technological era, farming methods and techniques also get upgraded to improve their yield so that farmers' profits improve. Precision farming uses drip irrigation techniques to optimize its resource utilization. Different technologies like the Internet of Things (IoT), artificial intelligence (AI), Sensors, and drones bring precise data that helps farmers better schedule and manage. This research paper aims to implement a sensor-based system that optimizes the irrigation schedule for Sugarcane crops in Satara, Maharashtra. In this research, two stages of sugarcane cultivation, i.e., Grand growth and maturation phases, are being monitored. Using a moisture sensor, real-time data is stored through a Wifi module, which determines the theoretical irrigation requirement using the Crop Water Requirement model. The theoretical irrigation requirement is compared with the current irrigation schedule. The study gives insights related to water requirements in different growth stages. During research, the Grand growth phase has a deficit of water as per their requirement. So, the irrigation schedule needs to be closely monitored with exact requirements that optimize the water resource. Conversely, the Maturation phase demonstrated a harmonious alignment between the irrigation schedule and crop water requirements. The research underscores the significance of precision irrigation with drip strategies attuned to specific growth stages for enhancing sugarcane yields. This study showcases the potential of sensor-driven monitoring and data-driven decisions to elevate agricultural practices, ensuring optimal water supply during pivotal growth periods and enhancing overall productivity and resource efficiency. The findings have implications for sustainable agricultural practices and contribute to advancing precision farming techniques.