In scientific irrigation scheduling, water is applied to a crop for the right amount of time to make sure it gets enough to suit its needs. A sugarcane crop's irrigation depth is determined by its maximum soil water deficit (MSWD) and is different for each soil. Irrigation scheduling methods that automatically control water application based on previously determined needed soil water deficit depth are effective. An auto-irrigation system that was created locally can accomplish this. The current effort focuses on designing, developing, and simulating a low-cost, fully automated, IoT-based auto-irrigation system for sugarcane crops that may considerably improve water management, increase the effectiveness of crop cultivation, and increase soil fertility. This device uses a moisture sensor to detect the depth of the soil's water deficiency and transmits actual data to an ESP-32 microcontroller. The designed circuitry can run for a long time on batteries or on dc voltages of 5 and 12 volts. This system is intended to examine the flow rate for providing sufficient water to sugarcane plantations. A key component of water management and irrigation systems is maximizing flow rates and reducing water loss. For four different types of soil—Coarse sand, Sandy loam, Silt loam, and Black cotton ploughed soil—the flow rate with the least amount of water loss has been determined using the WinSRFR 5.1.1 simulation software. The planned system has benefits for sugarcane crops, water conservation, and reducing soil deterioration.