The challenges that the world may face in the near future are the growing population, climate change, and water scarcity. Finding solutions to these challenges must be taken into account. Among these solutions, one is the optimization of resource use, such as energy and water, and the preservation of the soil quality. Now, one can ask how such challenges can be addressed, in which sustainable agriculture can be the answer. Agricultural activities are greatly enhanced through the use of IoT devices. The GreenPi, smart irrigation system proposed and designed in this paper will support sustainable agriculture with effective use of water. GreenPi employs real-time, distributed fog and edge computing and LoRa technology for the scheduling of irrigation based on information from the sensors and weather condition. GreenPi is a four-tier model with the following layers: 1) sensors and actuators to collect data from the field and send commands to actuator nodes like valves or water pumps; 2) the edge layer takes in sensors’ data and sends commands to actuators using ESP32 with LoRa; 3) a fog layer that exploits Docker containers for running applications to manage data processing, irrigation decisions, and communication with cloud and edge devices; and 4) a cloud layer to provide weather data and facilitate further data analysis. GreenPi is examined in real-time by continuously transmitting temperature, humidity, and soil moisture data to the fog. The proposed solution, with enhanced methodologies and reduced latency, achieves satisfactory outcomes for smart farming and automated irrigation. A small farm model is designed to showcase the GreenPi system’s effectiveness, which results in significant water savings, enhanced moisture level stability, and efficient energy saving that ensures sustainable operation of the system when compared to traditional irrigation methods, with the traditionally irrigated portion consuming 11.5 liters while the smartly irrigated portion consumed 10.6 liters. This system holds promise for sustainable water and energy management practices in agriculture.