This research focuses on the development and implementation of a sensor-based system for monitoring and controlling environmental conditions in a specific context (please provide context if available). The system consists of six layers that facilitate the communication of sensor readings from the field to mobile and cloud interfaces, enabling authorized users to access and control the system. The first and second layers incorporate temperature and moisture sensors, respectively, to sense the temperature of the surrounding environment and the moisture content of the soil. The data collected by these sensors is then transmitted to a local computer through a sink node comprising a microcontroller and Raspberry Pi. Zigbee technology is utilized for communication between the local computer and the cloud, where the uploaded data can be visualized through a mobile application. The fifth and sixth layers are responsible for maintaining the cloud and initiating actuator operations based on sensor readings. The system's autonomy eliminates the need for constant supervision, as it automatically analyzes the sensor readings and makes decisions regarding actuator operations, such as irrigation based on temperature and moisture levels. A prototype system was developed and tested to validate the proposed concepts, demonstrating accurate sensor readings and appropriate actuator responses. The research contributes to the field of sensor-based environmental monitoring and control systems by providing a practical framework for data communication, decision-making, and actuator control. The system's autonomous operation offers potential benefits such as improved resource management, increased efficiency, and enhanced productivity in the monitored context. The findings from this research serve as a foundation for further advancements and applications in sensorbased systems, paving the way for precision agriculture, smart cities, and industrial automation.