Atoq

https://docs.google.com/presentation/d/1PwSgR-Zen-GnU8BL-P2zBxz2UkTczTjQ/edit?usp=sharing&ouid=114761899101196032968&rtpof=true&sd=true

https://github.com/lanre97/aymuray

Do you want to know where you can sow effectively?

This application will be of great help to you. Through the information provided by NASA through the NASA POWER’s API we managed to make a study of how the environment has interacted in a specific area. With this information, the application estimates how advisable it is to plant a certain type of food and when it may be the best option to plant it.

What exactly does it do?

The user will be able to choose between the available vegetables, these are: potato, onion and corn.Similarly, you can choose the location you want thanks to the map provided by the app. Then, by pressing the button in the lower central part, you can find out if the soil in that area is useful for sowing the desired vegetable. In this same screen at the top you will be able to move between 2 sections, one is the recommendation for sowing, and the other, to evaluate the details of the climate. In the first section, the user will be able to see if it is advisable to sow in that place. It will also inform you at what time of year you can do it. In the second, the user will be able to view the details of the environment by graphs either for the same year or for the last 5 years.

¿Qué hace exactamente? 

El usuario podrá escoger entre los vegetales disponibles, estos son: papa, cebolla y maíz.

De igual manera, podrá escoger la localización que desee, ubicándolo en el mapa que provee la app. Luego, presionando el botón que se encuentra en la parte inferior central, podrá averiguar si es que la tierra de dicha zona es útil para sembrar el vegetal deseado. En esta misma pantalla en la parte superior podrá moverse entre 2 secciones, una es la recomendación para sembrar, y la otra, para evaluar los detalles del clima. En la primera sección, el usuario podrá visualizar si es recomendable sembrar en ese lugar. Además te informará en qué época del año lo puedes hacer. En la segunda , el usuario podrá visualizar los detalles del ambiente por gráficas ya sea por el mismo año o por los últimos 5 años.

What do you hope to achieve?

Help all farmers who do not have the necessary economy to pay a specialist to analyze the territory. Most of them have not carried out the necessary studies to know which crop is best for them to harvest. This problem can be solved thanks to Aymuray, as it would allow an easy and agile way to access highly relevant information so that farmers can make the best decisions, thus generating a great deal for agriculture.

What tools, coding languages,hardware or software you used to develop your project?

• For the development of the application we use the Flutter programming language.
• To design the mockup of the application, the software Figma was used
• We used Firebase as a database.
• We used the NASA POWER API to extract data from Global luminescence, Temperature at 2 Meters, Wind Speed ​​and others.
• Patron bloc to manage the logic business

How does it works?

Formula for estimating the probability of success about the harvest at a certain crop in a specific area: 

To make this calculation, we had to investigate information about the optimal conditions for cultivation and information on the environment.

The information considered pertinent about the crop is the following:

• Top optimal temperature: It is the highest value of the temperature range
• Lower optimal temperature
• Top limit temperature
• Lower limit temperature
• maximum supported wind speed
• maximum brightness
• minimum brightness
• optimal soil moisture
• maximum temperature variation supported and the information extracted from the NASA Power API is the following:
• Global luminance
• Temperature at 2 meters
• Temperature at 2 meters maximum
• Temperature at 2 meters minimum
• Root zone soil wetness
• Wind speed at 2 meters

With this information extracted from a specific location, the probability of success is calculated according to the ideal parameters of the specific harvest.

For the final result, first 5 weighted and a penalty metric are calculated:

Temperature weighted: this weighted calculates how optimal the average temperature of the environment is for the crop, the calculation is as follows: 

Legend of the crop data for this calculation:

• Top optimal temperature as Crop_TOS
• Lower Optimum Temperature as Crop_TOI
• Upper limit temperature as Crop_TLS
• Lower limit temperature as Crop_TLI

Legend of the API data for this calculation:

• Temperature at 2 meters as Env_T2M 

If Env_T2M is greater than or equal to Crop_TLS or less or equal than Crop_TLI respectively, the weighted will be considered 0.

If, on the other hand, Env_T2M is greater or equal than Crop_TOI and less or equal than Crop_TOS respectively, the weighted value will be 1.

Now if Env_T2M is between the range of Crop_TLI and Crop_TOI it will be calculated as follows:

Pt = (Env_T2M - Crop_TLI ) / (Crop_TOI - Crop_TLI )

Likewise, if Env_T2M is between the range of Crop_TOS and Crop_TLS, it will be calculated as follows:

Pt = (Crop_TLS - Env_T2M ) / (Crop_TLS - Crop_TOS )

Temperature variation weighting: this weighting calculates how optimal the average variation of the ambient temperature is for the crop, the calculation is as follows: 

Legend of the crop data for this calculation:

• Maximum temperature variation supported as crop_MaxVT

Legend of the API data for this calculation:

• Temperature at 2 meters maximum as Env_T2Max
• Temperature at 2 meters minimum as Env_T2Min

The variation of the environment is calculated as:

 Env_Var = Env_T2Max - Env_T2Min

Then if crop_MaxVT is less than Env_Var the weighted is 0

 Otherwise the weighted is calculated with the following formula:

Pvt =(crop_MaxVT - Env_Var) / crop_MaxVT

Temperature penalty: This penalty estimates that both the maximum and minimum temperatures of the environment escape the limit temperature range of the crop: 

In this case, the previously established legends will be used:

If the maximum and minimum temperatures of the environment are within the range of the limit temperatures of the crop, the penalty is 0.

Otherwise, the difference between Env_T2Max and Crop_TLS or Env_T2Min and Crop_TLI is first calculated, taking the greater difference as priority

Then if this difference now called DIF is greater than 20 ° C, the penalty will be 0.

If it is less, the penalty will be calculated as:

Penalty = 1 - (DIF/20)

Global Temperature Weighted: This weighted combines the previous weights and the penalty and is calculated as:

Legend:

• Global temperature weighted as Pglobal_temp
• Temperature weighted as Pt
• Weighted temperature variation as Pvt
• Temperature penalty as PenaltyTemp

Pglobal_temp = (Pt*0.8 + Pvt*0.2) * Penalty Temp

Weighted wind speed: This weighted calculates how optimal the wind speed is for the crop, the calculation is as follows: 

Legend of the crop data for this calculation: 

• Maximum wind speed supported as Crop_MaxWS

Legend of the API data for this calculation:

• Wind speed at 2 meters as Env_WS2

If Env_WS2 is greater than Crop_MaxWS the weighted is 0.

Otherwise the following formula is used:

Pws = (Crop_MaxWS - Env_WS2 ) / Crop_MaxWS

Luminescence weighted: This weighted calculates how optimal total luminescence for the crop, the calculation is as follows: 

Legend of the culture data for this calculation:

• Maximum brightness as Crop_MaxLUM
• Minimum brightness as Crop_MinLUM

Legend of the API data for this calculation:

• Global luminance as GI

MaxDistanceToCenter = Crop_MaxLUM - Crop_MinLUM

Center = MaxDistanceToCenter + Crop_MinLUM

if GI < Crop_MaxLUM - MaxDistanceToCenter and 

GI > Crop_MaxLUM +MaxDistanceToCenter

the weighted is 1- (abs(center-GI))/(2*maxDistanceToCenter)). 

In other cases, the penalty is 0.

We use NASA POWER’s data to obtain the information about:

• Top(upper) optimal temperature: It is the highest value of the temperature range
• Lower optimal temperature
• Top (upper) limit temperature
• Lower limit temperature
• maximum supported wind speed
• maximum brightness
• minimum brightness
• optimal soil moisture
• maximum temperature variation supported

Also, we use the GoogleMaps’ data to obtain specific ubications in our app.

How would you describe your experience with Space Apps? Did you learn?

It was an experience that we will never forget. During the planning and creation process, we learned many things as a team, the use of new programs, how important communication is in a work group, in the same way, we learned many interesting facts about crops and how the different climatological factors affect them. However, we considered that the most interesting thing was that we were able to witness how an idea we had became a reality.

How did your team resolve setbacks and challenges?

We solved all the setbacks by dividing the work acorder our abilities.

What inspired your team to choose this?

We thought something very useful for many people, since professional advice for these types of issues is not exactly cheap, so we are inspired to provide you with this type of information for free, which, without this app, would be much more tedious and expensive to obtain.

Challenges?

There were quite a few setbacks during the creation process, from difficulties in choosing the final design of the application, to code errors that delayed the pace of work, however, we believe that we were quite resilient in the face of the different problems that appeared. It was a challenge to finish this project, however, we can say that we were able to achieve it successfully.

What was your approach to developing this project?

We decided to focus on the most important features at our discretion. Because, due to the time limit, we prefer to focus on prioritizing the importance of each added feature, rather than the quantity. Our approach was always that, to deliver an application that is really useful to someone who is interested in this type of information.

How did your team resolve setbacks and challenges?

We solved all the setbacks by dividing the work into sections, assigning each one to the person who best mastered that area of ​​the project.

Is there someone you would like to thank and why?

Of course, we would like to thank the organizers of this event, for making this project possible, since, without the data and statistics provided by NASA, the idea of ​​creating this application could never have become real.

1.Intagri. (n.d.). Requerimientos de Clima y Suelo para el Cultivo de la Papa | Intagri S.C. Retrieved October 4, 2021, from https://www.intagri.com/articulos/hortalizas/requerimientos-de-clima-y-suelo-para-el-cultivo-de-la-papa

2.Braulio La Torre Martines. (2012). “Asistencia Técnica Dirigida En Fertilización En El Cultivo De Papa” [Guia Tecnica]. 

UNALM Octubre 4, 2021, from

https://www.agrobanco.com.pe/data/uploads/ctecnica/032-h-papa.pdf

#Crops #Farm #Sun #Earth #Farming #Vegetables #Harvest #Climates #Statistics

This project has been submitted for consideration during the Judging process.