## 6 Analysis and Results
### Libellium Connector: Implementation and Observations
#### 6.2.1 ASCII Encoding
Furthermore, the integration of specific and heterogeneous agricultural sensors, such as soil temperature, nitrogen concentration, leaf wetness, and atmospheric pressure, into a single architecture represents the novelty of this work. ## 8 Conclusions

This work highlights the crucial importance of IoT in precision agriculture, emphasizing how technology can address the challenges related to the scarcity of arable land and the increasing demand for food. However, the lack of shared communication standards among various IoT devices poses a significant barrier to the integration and efficiency of these systems. The proposal for an interoperable architecture is essential to overcome these challenges, allowing for smooth and comprehensible communication between heterogeneous devices. In this context, the OGC SensorThings standard plays a pivotal role. By providing a unified framework for interconnecting IoT devices, data, and applications, SensorThings facilitates _semantic interoperability_, enabling different devices to communicate effectively regardless of their underlying technologies. This standard supports resource-constrained devices and utilizes REST principles, JSON encoding, and various communication protocols, making it particularly suitable for the diverse needs of precision agriculture. To further enhance _interoperability_, we have developed specific connectors that serve as software interfaces between various sensors and the OGC SensorThings framework. These connectors are designed to translate and standardize the data from different sensor types, ensuring that information can be seamlessly integrated into the system. By enabling communication between devices from different manufacturers and accommodating various data formats, the connectors play a crucial role in achieving a cohesive and interoperable architecture. The adoption of the OGC SensorThings standard will not only enhance data collection and analysis but also contribute to more sustainable and productive agricultural management by ensuring that data from various sources can be integrated and understood seamlessly. This approach will ensure a more sustainable and productive future for global agriculture. Conceptualization, E.R. and M.R. ; methodology, N.L. and A.P. ; software, E.R. and N.L. ; validation, A.P., E.R. and M.R. ; formal analysis, A.P., E.R. and M.R. ; investigation, N.L. and A.P. ; writing--original draft preparation, N.L. ; writing--review and editing, A.P. and M.R. ; visualization, E.R. and M.R. ; supervision; E.R. and M.R. ; project administration, M.R. All authors have read and agreed to the published version of the manuscript. This work was partially supported by The European Union under the Italian National Recovery and Resilience Plan (NRRP) of NextGenerationEU, partnership on \"Telecommunications of the Future\" (PE00000001--program \"RESTART\"). Data available on request. The authors declare no conflicts of interest. ## References

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