## 6 Analysis and Results
### Libellium Connector: Implementation and Observations
#### 6.2.1 ASCII Encoding
Therefore, the result is contained in the following 4 bytes and should be read in \"Little-Endian\" order, as shown in Listing 22. ```
{  name: \"Temperature Celsius\", description: \"Temperature in degrees Celsius\", unitOfMeasurement: {  name : \"Degrees Celsius\", symbol: \"C\", observationType:OM_Measurement, result: 27.25 }
```
Listing 22: DATASTREAM and OBSERVATION of temperature sensor. \(\blacksquare\) **0 FD7A3 CA42**: The last measurement corresponds to \"Atmospheric Pressure\", and it also has a value in float format (Listing 23). ```
1{
2 name : \"Pressure atmospherics\", description : \"Presusion atmosperics\", unifOfAssument : name :\"Kilo Pascal\", symbol :\"APA\", }, observationType :OM_Measurement, result : 101.32
```

Listing 23: DATASTREAM and OBSERVATION of pressure atmospherics sensor. ## 7 Discussion: Implications for Precision Agriculture

The Research Questions (RQs) addressed in this work have enabled the identification of suitable IoT standards and protocols to meet the design requirements of an interoperable architecture in precision agriculture. In accordance with RQ1, this work discusses the importance of IoT standards as a middleware layer that facilitates interaction between IoT applications and networks. The main requirements of IoT standards in agriculture include simplifying implementation, reducing both costs and the complexity of managing an IoT network [3]. Additionally, IoT standards aim to improve the portability and interoperability of applications, allowing them to operate across different platforms and devices [40]. Moreover, RQ1 proposes a common model for data transfer, thereby facilitating integration and scalability among various devices and systems in the context of precision agriculture. Building on the requirements identified in RQ1, RQ2 examines the IoT protocols that are most suitable for implementing these standards in precision agriculture. In particular, LPWAN (Low Power Wide Area Network) protocols are well-suited for collecting data from sensors and sending them to a Gateway (GW); indeed, they enable long-range communication with minimal energy consumption, making them ideal for large-scale agricultural deployments [68]. MQTT (Message Queuing Telemetry Transport) is generally used to connect the GWs to the Internet, but on certain occasions it can also be used to send data directly from the sensors to applications, as it allows for efficient transmission and is suitable for agricultural environments where connectivity may be unstable [102]. Finally, in order to create an interoperable architecture, the HTTP (Hypertext Transfer Protocol) is employed to connect the various connectors to web applications [103]. RQ3 focuses on determining the IoT standard best suited to implement an interoperable and scalable architecture for precision agriculture. In our solution, the OGC (Open Geospatial Consortium) SensorThings [104] standard was chosen because it fulfills all the necessary requirements for developing an IoT platform in this context. Its main features, such as the ability to interface with _connectors_ that act as intermediaries between various sensors, enhance communication between heterogeneous devices, making it an ideal solution. Regarding data security, the SensorThings API (Application Programming Interface) does not define security capabilities of its own; however, its design is compatible with IoT security best practices and integrates with general security capabilities, supporting cross-cutting security [105]. In fact, since the SensorThings API falls under the Service Support and Application Support Layer of the IoT reference model, security is treated as a cross-cutting component acting on all layers of the proposed architecture. RQ4 explores the requirements and challenges for creating an architecture capable of achieving interoperability across diverse IoT devices in precision agriculture.