## 3 Information and Communication Technology Solutions for Precision Agriculture
### Data Storage and Distribution
#### 3.3.1 Sharing Platforms and Cloud Storage  
[PERSON] et al. demonstrate a distributed data sharing platform for multi-source IoT sensor agriculture and forestry data. The platform consists of data center, data adapter, data storage, data publishing, and data transmission subsystems. The data publishing subsystem provides standardized data query interfaces for single or multi-sensor real-time data as well as for historical data. The proposed platform bridges the gap between the data from different IoT sensors and the use of this data in various agriculture or forestry applications [69]. [PERSON] et al. demonstrate a knowledge sharing system for agriculture. This system enables sharing of two sources of data: data from sensors (e.g., temperature, humidity, CO\({}_{2}\) measurements) and work information from skillful farmers (e.g., experiences modeled in a digital Extensible Markup Language (XML) form). The proposed system helps maintain agricultural technology at high levels as well as promotes the concepts of PA [70]. [PERSON] et al. present a heterogeneous agriculture database sharing platform based on the XML. Utilizing a browser/server (B/S) architecture, this platform enables users to access heterogeneous databases through their web browser. Databases which could utilize this platform include: practical agrotechnique/agriculture, policy/agricultural scientific talents/market supply/market demand databases. Testing of this platform proved its reliability and usefulness for data sharing in PA [71]. [PERSON] et al. propose a data-exchange platform for farm management information systems. This platform consists of the data collection service and the data sharing service. Testing of the proposed system revealed its flexibility and extensibility in collecting data from heterogeneous sources, including web services and serial communication devices. In addition to this, the platform was found to be very accurate and efficient for sharing data among different farm management information systems [72].  
Cloud computing and its related services can very beneficial for PA. Cloud computing refers to the technologies enabling easy, ubiquitous, and on-demand access to a shared pool of computing resources, encompassing networks, storage, servers, services, etc. with minimal management/interaction needs [73]. [PERSON] et al. demonstrate a cloud-based remote sensing observation sharing framework for soil moisture mapping in PA. This framework consists of a cloud-based sensor observation service, a web processing service, and a distributed database subsystem. Testing of the proposed system indicated its contribution to improving earth observation data storage as well as to achieving large-scale mapping of soil moisture [74]. [PERSON] et al. propose a novel, reliable, and easily extensible PA system based on cloud computing and cloud storage enabling farmers to monitor their crops and plan their agricultural tasks from a PC, a smartphone, or a tablet. The use of cloud storage instead of local storage contributes to minimizing management efforts as well as to optimizing the use of resources [75].