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## Conclusion
By adapting the project's foundation for operation on a Raspberry Pi, the workings of embedded systems become clearer. Code alone is insufficient; functionality depends on the interaction between the hardware, the communication protocol (I²C), the operating system (Raspberry Pi OS Lite) along with its kernel (Linux), and the developed application.
The HTU21D sensor uses address 0x40 within the I²C protocol, allowing for its unique identification on the communication bus. In this protocol, all devices share the same physical lines but are differentiated by specific addresses and operate using unique command sets for each component. This allows the Raspberry Pi to communicate with each sensor individually, sending precise instructions for data reading without generating transmission conflicts on the network.
The use of this module, along with the other components that will make up the micro-weather station, represents a highly efficient monitoring strategy. Unlike traditional fixed measuring stations—whose large size and high installation and maintenance costs considerably limit their coverage area—this design allows for the manufacture and installation of a complete network of micro-stations for a fraction of the cost of a single, larger unit. This advantage facilitates their distribution at various strategic points throughout the city, resulting in a much broader, more representative, and more specific collection of data that better supports informed decision-making.
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## Limitations
During the development of this project, several limitations were identified that represent areas of opportunity for future improvements:
1. **Limited Data Storage:**
Currently, the system only collects and displays data in real time, without a persistent storage mechanism. This prevents the generation of measurement histories within a database, limiting short-term analysis.
2. **Lack of Data Analysis Tools:**
The system lacks functionalities geared towards analyzing the collected information, such as generating graphs or statistics at different time intervals. This limitation hinders the identification of patterns and trends that could be useful for decision-making.
3. **Lack of Geospatial Integration:**
There is no integration with a mapping system (for example, through services like Google Maps) that would allow visualization of the micro-weather station's location within the city. Furthermore, address or location information is not displayed on the main interface.
4. **User-space driver implementation:**
The sensor driver is implemented in user space, which limits its efficiency and system integration. A kernel-level driver has not been developed, which would allow for more robust, efficient, and transparent device management within the operating system kernel.
