## 3 Information and Communication Technology Solutions for Precision Agriculture
### Multi-Purpose Platforms
#### 3.4.1 Management Information Systems and Digital Platforms  
[PERSON] et al. propose a farm management information system (FMIS) which can be used for land mappings, data collection from various sources, monitoring parameters, data processing, as well as for decision-support. In particular, decision-making is supported by informing the farmer about new technologies, available resources, competitors, prices, financial forecasts, regulations, etc. A relevant ontology was also developed to represent the knowledge which can be used for understanding the main concepts and relations regarding the FMIS [82]. [PERSON] et al. demonstrate a FMIS which enables farmers to easily perform profitability analysis based on certain farm parameters, recorded transactions, and the performed agricultural tasks. This FMIS utilizes cloud computing technologies and was field tested on a winter wheat crop. It has the potential of facilitating decision-making of farmers regarding PA practices and use of resources [83]. [PERSON] et al. describe and evaluate an open-source environment for data management in PA. This solution aims to provide full and free support for common low-cost hardware, which is used to support various environmental sensors and their generated data. Visualization tools and several data management tools are easily accessible by the users. Sharing data among registered users and creating rules for executing simple operations are also available [84]. [PERSON] et al. present a dashboard for PA, which can be used for creating yield and fruit quality maps. The proposed solution utilizes GIS data as well as data from various libraries used for spatial data processing/analysis and provides the user with useful information in terms of farm management. Some of the benefits of the aforementioned dashboard include easier decision-making of farmers and optimized use of water, fertilizers, and pesticides [85]. [PERSON] et al. demonstrate an agricultural ontology which can be used for applying data science technologies in agriculture and can lead to increased productivity and more effective management. The knowledge base created in the context of this solution contains several semantic relations and hierarchies which can link diverse available resources. The ontology addresses many challenges which are present while pre-processing, transforming, analyzing, and integrating real-world big data in the agricultural domain. Furthermore, the proposed ontology is that it can serve as a basis for building bigger and more precise knowledge bases [86].  
Supervisory control and data acquisition (SCADA) technology is another example of a multi-purpose platform for PA. The term SCADA focuses on the supervisory level rather than representing a full control system. It is a software package which communicates with programmable logic controllers (PLCs) and/or other commercial hardware modules [87]. [PERSON] present a SCADA system for automated irrigation control of crops. This system enables real-time monitoring of the process variables (e.g., earth temperature/humidity, environment temperature/humidity, water pressure) as well as controlling the solenoid valves which are used for the irrigation. Optimized labor and water resources use, reduced costs, fewer diseases, and less stress on the plants were spotted as some of the potential benefits of the proposed solution [88]. [PERSON] et al. demonstrate a mobile SCADA system for automatic crop field management. According to the measurements of different sensors,irrigation is controlled automatically, and the proper fertilizer and pesticide amounts are dosed. This system is also capable of detecting disturbances at the crop field (e.g., animal intrusion) and providing alarms accordingly [89].