# Precision Agriculture: A Remote Sensing Monitoring System Architecture +
## 8 Use Case Study: The DIAS Architecture
### DIAS Architecture
Any kind of wild weeds or animal detection based on thermal imaging in the fields initiates alerts for immediate intervention and is taken into consideration as a note in the cultivation calendar created by the platform for the farmer. For this purpose, the OBIA algorithm is also used to recognize weeds or discriminate species. Object-based image analysis is based on the comparison between sets of similar pixels called image objects in measures of spectral properties (i.e., color), size, shape, and texture, as well as context. The OBIA algorithm is chosen since it is more suited to landscape-scale analyses and can filter out meaningless information and assimilate other pieces of information into a single object. After processing, all the collected sensor data are categorized and evaluated in accordance with the desired vegetation index values, moisture levels and general plant state for each month during the cultivation process. For these tasks, the DIAS platform employs powerful and well-known tools, the Apache Spark Framework focusing on Big Data analytics and the WEKA (Waikato Environment) Framework specializing in data mining tasks. The evaluation results will point out the vulnerable spots in the field with helpful statistical graphs and suggest possible solutions to the farmer, such as the use of fertilizer. In the Application Layer, each user can access the DIAS platform by using his/her own unique password. According to their authority and activities in the saffron field the users have different access rights in the DIAS platform. A user may be the administrator of the platform, a representative of the KSPC board, a farmer or a worker in the fields. For instance, a worker can only observe the evaluation results in order to aid the farmer in treating the plant growth, while the KSPC representative can add observation notes, can schedule and initiate sensor data collection in a specific field and also manage the flight plan of UAVs. On the other hand, the platform administrator is only one who can add new users and new saffron fields for cultivation to be observed in the system. Access in the DIAS platform is forbidden for non-authorized users. In the Application layer, the management of the four basic operational units of the DIAS system can be initiated. These are the Visualization Unit, the Data Management Unit, the Prediction Unit and the Data collection Unit. By entering the Data collection Unit, a user can initiate sensor data collection in a selected field or modify existing data in the platform. By entering the Data Management Unit, the user can evaluate orthophotographs and calculate vegetation indexes according to specific data in a specific saffron field with the help of Pix4 DMapper tool. The Visualization Unit is related to the presentation of statistical results and graphs regarding each saffron field, while the Prediction Unit employs the aforementioned data mining tools to produce a sufficient evaluation of the collected data. All system information is stored in the central server database. Based on the acquired and processed data, farmers can produce statistics regarding the progress in saffron production and avoid financial loss, while improving the quality of the crops and accomplishing a considerable rise in production.