Sense-Making Journal - Urban Gardeners
====================

:::info
A report by the Urban Gardeners team 🌱 : Gerda, Fiorella, Paula, Emilio, Audrey and Busisiwe
:::


**Journal Index**

[TOC]

## From objectives to the hypothesis

### Brainstorming


### Project Goals
objective:
**I WANT TO PRODUCE MY FOOD.**

*Can I produce the ingredients of my meals at home or my neighborhood?*

hypothesis:
**I CAN PRODUCE THE INGREDIENTS OF MY MEALS AT HOME OR MY NEIGHBORHOOD.**

### Tips
We recommend that, in order to realize the experiment properly, we require to collect data during the year, because of the time of growth of the plants.

Nutritional data is required to estimate possible species to grow, and therefore the space demanded for a person to grow his food.

In addition, being aware that particles in the air and other gases might affect the correct development of plants.

And, try to not be around the sensor while it is doing the measurement because it affect the results.

## From hypothesis to data

### Tools selection

We chose the **CITIZEN SENSING TOOLKIT**
http://making-sense.eu/wp-content/uploads/2018/01/Citizen-Sensing-A-Toolkit.pdf




We selected it because we wanted to figure out how is the weather (temperature, humidity, light, eCO2, eVO2) in the possible free spots to grow food in the neighborhood and compare it to what the plants require to grow there.

### Tool usage documentation
The process can be replicated using the same **Citizen Sensing Toolkit**, what we recommend is to do it at different times a day and in all the seasons if it is referred to growing plants.

Check the *outliers* when you download the information.

#### Data capturing strategy
First, we choose the places that are already working as urban gardens, then we start thinking of possible places that might be used to check if they can be used to growing the food, and what types of food might be there.


The data was taken from 14:30pm to 16:30pm in 7 places that we checked before start.


Then we download the data in the laptop to start the cleaning of the information.


#### Materials needed

- Smart citizen kit sensor
- USB cable
- Computer to configure the SCK
- Cell phone to connect the SCK using WiFi connection, and take pictures and videos to documentation.

#### Detail setup instructions
- The first step is to connect the battery. The kit will light in red (configuration mode)
- Sign up to the Smart Citizen Platfom
- When the light is red, the CSK is ready to set up, either by WiFi or SD Card connection
- When the light is blue, the SCK is on Wi-Fi connection. In this way, the device will publish the data every minute on the smartcitizen.me platform
- When the SCK is pink, it is on offline mode and is saving the information on the SD Card
- When we measured, we pressed the button once until the light turnd pink, we measured for 10 minutes then switched it to standy turning the light red
Find a good and clear location to place the *Citizen Sensing Toolkit*. If you need to measure light, make sure it is "face up".



#### Data collected

Using the Smart citizen kit, we planned to visit 6 different locations to gather data on light quality, humidity, Temperature and particle matter.

MAP OF LOCATIONS WHERE DATA WAS RETRIEVED

IAAC-ROOFTOP

JARDINS DE MERCÉ

CONNECTHORT

AV. D'ICARIA

CEMETERY

PARC MARIPOSA

CARRER DE PUJADES

The raw data is provided in spreadsheets:

#### Tips

*We would have to measure with multiple devices in order to have the conditions in different places at the same time of the day and for a longer time*

## Data capture

### Data summary

| Data Summary | |
|--------------------------|--------------------|
| Project Title | Urban Gardeners |
| Capture Start | 11-11-2021 |
| Capture End | 12-11-2021 |
| Original Data Format | CSV file |
| Submitted format | CSV file |
| Total Data Points | 359 |
| Number of datasets | 2 |
| Data Repository | https://github.com/fablabbcn/mdef-a-world-in-data/tree/main/urban-gardeners |

## Optimal Conditions

## Data insights

- We compared the data captured in the 7 spots.

To improve the data:
- We would need to take measurements of all year and at the same time in different places.
- In order to have an efficient use of the space for producing the plants, we would have to measure characteristics of the soil as well (nutrients, chemicals, ph, etc.)
- Other parameters could be taken into account: available time of people to take care of it, space available.

**Raw data**

We used google sheet pivot tables to agregate data into averages by location and also to focus on specific parameters.

**Average of data by location**

**Focus of each location data to remove potential outliers**

**Comparision bubble chart**

* x = temperature
* y = light
* diameter of the bubbles = CO2 particules

We displayed the ideal location conditions needed for the 4 vegetables we studied above.

Potatoes, carrots : not any location studied respond to the requirement of light needed

Lettuce, tomatoes : only the rooftop of IAAC would allow us to grow these!

We need to continue the research on the vegetables that we can grow in the winter season with very little light.


### Tips and biais

We didn't pay attention to the noise sensor so we made some noise discussing just next to the sensor during the data capturing. It would be interesting to stay silent or go further during the recording so we can see how much frequentation there is in the different locations.

Scale the process : To record more accurate and more comparable data, it would be better to record a full day and not just 10 minutes to know how much light the location gets. Here we just recorded 10 minutes in each spot and not at the same time of the day (between 1pm and 4:30pm).