This study focuses on the design and implementation of a cost-effective smart home system, which leverages Internet of Things (IoT) technologies, low-power communication via LoRa, and data processing to enable automation and remote management of household devices and environmental conditions. The growing need for more efficient, secure, and energy-sustainable homes makes such systems particularly relevant today. An ESP32 microcontroller is used as the core of the system, to which various sensors are connected, including temperature, humidity, motion detection, gas leak detection, fire detection, and others. The ESP32 is responsible for collecting and processing the sensor data, which is then transmitted via LoRa (Long Range) technology to The Things Network (TTN). TTN serves as an intermediary gateway, forwarding the data to an online monitoring and visualization platform, Datacake. There, the data is displayed in real-time through graphs and charts, allowing users to remotely monitor the home environment. Simultaneously, the data is also sent to a Raspberry Pi, which functions as the central processing unit of the system. The Raspberry Pi runs a control algorithm that analyzes the sensor readings and issues commands to activate or deactivate connected devices. Examples of such automations include turning on or off lighting, heating, or ventilation systems, and notifying the residents in case of emergencies. The proposed system integrates cutting-edge technologies to develop a smart, interconnected, and autonomous home environment, offering enhanced comfort, safety, energy efficiency, and cost-effectiveness for the user. The system is low-cost, scalable, and adaptable to various settings and needs.