## 2 Background and Paper Contribution
### Research Challenge and Problem Formulation  
However, in the collection of data from these sensors, a problem arises: when the system is composed of heterogeneous devices, there is currently no shared communication standard among all devices for data collection and communication. The current market offers multiple IoT devices for precision agriculture, some of which can be managed using proprietary software provided by the manufacturer, while others can be programmed by the user. Each device has its own method for collecting and transmitting data, resulting in a set of heterogeneous data sent with different specifications, making it difficult for the end user to consult. When a sensor sends data, especially in the IoT domain, the transmitted information is compressed to minimize resource consumption. Part of the information necessary for understanding the data (such as units of measurement, accuracy, type of measurement, etc.) is left implicit because, using the standard system provided by the sensor manufacturer, it is processed during the reception and data processing stages. If sensors from different manufacturers were to be used, the result would be a set of incomplete or undecipherable data that would be of little use for analysis. To better understand the problem, we analyse an example payload from a sensor, in this case, the SensorData sensor produced by Digital Matter [37], to which a sensor for measuring atmospheric pressure is connected. The payload sent by the sensor is as follows:  
\[\text{``}AF4D3276 CE5F3334801260618231006A18\text{''}\]Without the use of the software provided by the manufacturer, it would be impossible to decipher the information contained in the string, which represents the geographical position of the sensor and the value of two measurements taken.  
In this research, the problem is addressed by proposing a system architecture based on a standard that can be shared among the various connected IoT devices, in order to create a network that can accommodate different types of device without compromising the understanding and analysis of the final data. Furthermore, in order to propose an interoperable architecture, an intensive analysis was carried out of existing standards and protocols to be adopted in agricultural contexts. This analysis is defined by the following Research Questions (RQs):  
* **RQ1**: _What are the requirements to be met by IoT standards for precision agriculture?_
* **RQ2**: _Which IoT protocols are most suitable for precision agriculture?_
* **RQ3**: _What is the most suitable IoT standard to use in agriculture?_
* **RQ4**: _What are the requirements and challenges for building an interoperable architecture for precision agriculture?_
* **RQ5**: _Which open source software is best suited to implement an interoperable architecture in agriculture?_  
These Research Questions (RQs) aim to explore and define technological solutions to enhance the adoption of the Internet of Things (IoT) in precision agriculture. Specifically, RQ1 examines the key requirements that IoT standards must fulfil in this context, while RQ2 identifies the most suitable IoT protocols to optimize the efficiency of agricultural applications. Subsequently, RQ3 focuses on determining the most appropriate IoT standard to address the specific needs of agriculture. RQ4 addresses the challenges and requirements for designing an interoperable architecture, facilitating integration among diverse technologies and systems. Finally, RQ5 investigates the most suitable open-source software to implement such an architecture, emphasizing the role of open software in reducing implementation costs. This is a crucial factor in overcoming one of the primary barriers to large-scale IoT adoption in agriculture: high development costs. By lowering these costs, advanced technologies become more accessible, even for farmers with limited resources.