The dataset contains information about roses cultivation in greenhouses. It is aimed at identifying corrective actions to improve the roses state. Data acquisition was done with an autonomous robot incorporating sensors such as: soil humidity, light, temperature and humidity, and CO2.

Instructions: 

1. Title:  Roses greenhouse cultivation database repository (RosesGreenhDB)

 

        Updated 17/07/2019  by Wilmer A. Champutiz

       

2. Sources:

     (a) Creators: Edison A. Fuentes-Hernández and Paul D. Rosero-Montalvo 

     (b) Date: July 2019

 

3. Relevant Information:

 The present dataset contains information about roses cultivation in greenhouses.

 It is aimed at identying corrective actions to improve the roses state.

 Correspondingly, the target variables (labels) are as follows:

 

1  Soil without water

2  Environment correct

3  Too much hot

4  very cold

 

Data acquisition was done with an autonomous robot incorporating sensors such as: soil humidity, light, temperature and humidity, and CO2. Resulting dataset is imblanced.

  

4. Number of Instances:  300 (125 soil without water

                               28 correct environment 

                               90 too much hot

                               57 very cold)

 

5. Number of Attributes: 5 numeric predictive attributes and the class

 

6. Attribute Information:

   1. Soil humidity in analog-digital conversion

   2. Light in lux

   3. Temperature in °C 

   4. CO2 in  analog-digital conversion

   5. Humidity relative 

 

   6. Class: 

           1  soil without water

           2  environment correct

           3  too much hot

           4  very cold

 

7. Missing Attribute Values: None

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