Water scarcity and climate change necessitate efficient agricultural water management. Traditional irrigation is often wasteful, impacting crop yields. This paper details the design, implementation, and operation of an automated smart irrigation system leveraging Internet of Things (IoT) technology, centered on a Raspberry Pi edge device. The system integrates specific sensors: DHT11 (ambient temperature/humidity), capacitive soil moisture sensors, DS18B20 (soil temperature), BH1750 (light intensity), and a DS3231 Real-Time Clock (RTC), with actuation via a relay module and water pump. Sensor data is processed locally on the Raspberry Pi, which executes threshold-based control logic and performs local data logging for resilience. Data is transmitted using MQTT/HTTP protocols via appropriate communication modules to the ThingSpeak cloud platform for real-time monitoring, visualization, and secondary data logging. This paper presents the system methodology, including architecture and component integration, operational workflow, implementation challenges, and visualized operational data obtained from the ThingSpeak platform, demonstrating the system’s responsiveness and validating its core functionality. The automation minimizes human intervention, optimizes water usage potential, reduces energy consumption, and enhances crop productivity potential. While challenges like connectivity and sensor reliability persist, the results confirm the viability of this accessible edge-cloud approach. Future trends point towards enhanced edge AI and sensor integration for more adaptive systems contributing to sustainable agriculture.