Design of a Data Warehouse for a Dynamic Greenhouse Control System

Authors: Maryna Lendiel, Taras Lendiel, Nikolay Kiktev

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Relevance and purpose of the study

The relevance of the topic. During cultivation, an important stage is to study and analyze all the conditions which are necessary for the normal growth and development of the plant. In the process of plant growth, it is important to take into account the optimal greenhouse microclimate to increase the efficiency of resource use for growing crops.

The purpose of the study is to implement a data warehouse using OLAP and Data Mining technologies to increase the efficiency of growing vegetables and fruits in closed ground facilities.

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Mathematical model

• where i=1...n; n – number of blocks; Qt is the amount of heat coming from the heating system; Qs - amount of heat received from the sun, J; Qv – heat loss through the greenhouse roof and end walls, J; Qі+1, Q і-1 – amount of heat coming from neighboring temperature blocks, J; Q sr,i is the amount of heat absorbed by plants in the i-th block, J.

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• where Θi is the air temperature in the i-th block; Θ w,i is the temperature of the coolant in the i-th unit; Sb,i is the area of the side surface in the i-th block; S k,i – roof area in the i-th block

The topology of the system

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Hardware

• For the greenhouse workstation, a monitoring subsystem was developed that works with data in an operational database, together with hardware using temperature and humidity sensors connected to a Raspberry Pi single-board computer. The DHT22 air temperature and humidity sensor was used as a sensing element for measurement.

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Scheme of the operational database

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Structure of the data warehouse

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Results of the analysis

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Results of the analysis

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• Time series algorithm

• Dependency network based on the implemented associative rule algorithm

Conclusions

• In the process of developing the system, the structure of the operational database was presented. Modules for data entry, storage and analysis were developed. During the analysis, it was proposed to use OLAP and Data Mining technologies to perform intelligent analysis of large amounts of information.
• The received results of the system operation can be used in the process of forming management decisions of the greenhouse economy. This will help to direct the strategy for managing individual business processes in such a way as to increase the yield in greenhouses and, accordingly, the profitability of the farm.

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Thank you for attention!

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