The Kanda Weather Group is seeking participants to develop a simple User Interface (UI) dashboard that shows our forecasts in an easy-to-understand way for local farmers and stakeholders.
The company is refining a weather balloon (also known as radiosonde) IoT technology product that collects data and uses Machine Learning to make a simple 12-hour rain forecast. They are 80% cheaper than traditional radiosondes and can be set up anywhere on earth.
We see Africa as being one of the biggest potential users of our technology, and we are looking to work with local groups to make localized forecasts for small-holder farmers. An accurate 24-hour flood forecast and warning system may be enough time to allow them to gather their crop yields on 1 hectare of land early before dire flooding occurs. Additionally, we believe that the data from the radiosonde balloons can also be used to make short-term air quality forecasts over polluted regions like the Niger Delta or fast-growing metro cities.
We are working with decentralized climate company dClimate to provide near real-time access to other variables such as soil moisture or rainfall data for our two forecast regions Accra, Ghana and Uyo, Nigeria. We invite participants to be creative in their efforts to build a display dashboard, and are awarding $1,000 USD to the 1st place project team and $500 USD to the 2nd place finishers.
Our company sees an opportunity in the miniaturization of computing and low cost of IoT sensors to dramatically improve weather data collection of the upper atmosphere. We originated as an idea in the Telos community through the Worker Proposal System and have been able to develop our product independently thanks to Goodblock.io . We are working with universities in Nigeria, Ghana, and the U.S. to collaborate on research.
We are passionate about eosio blockchain, and see low power, long range open networks as holding the potential to bringing many people out of poverty with low cost access to information.
On July 1st, the Kanda Weather Group will host a live virtual weather radiosonde launch to kickoff the hackathon.
Also on that day, a series of "Hindcasts" will be provided that participants can use as input to their forecasting dashboard. For the purposes of the hackathon, the only difference between a Hindcast and a forecast is essentially the date. It is essential that a dashboard include at least one of these Hindcasts into the display.
You will receive an email from the hackathon when the Hindcasts are posted to Taikai. Additionally, you can view them in the Updates tab, when they are made available.
The submission must include the following by July 31, 2021 at 23:59 GMT :
1. In English, please provide either ONE of the following describing the technologies you used and what makes your dashboard unique:
2. At least 2 different screenshots of the dashboard you created
3. Link to code on github with README.md file for how to build and run the software. If the dashboard can handle multiple locations and forecasts, please include how to adjust the backend parameters to achieve this functionality.
1. The "Simple" dashboard
- Handles only one location/date/forecast.
- For example: Uyo, 5/20/21, No rain
2. The Adaptable dashboard
- Handles many locations, dates, and forecasts
- Forecast adjustable via some backend (csv input file, raw input)
- For example: Uyo, 5/20/21, No rain or Accra, 5/22/21, Heavy rain
3. The Exceptional dashboard
- Handles many locations, dates, and forecasts
- Forecast adjustable via some backend (csv input file, raw input)
- Reads in soil moisture for the given location/date from dClimate's API
and shows flood risk based on that information
(HINT: high 10cm soil moisture values or water runoff values indicate higher flood risk)
- For example:
Uyo, 5/20/21, No rain, Low flood risk or Accra, 5/22/21, Heavy rain, High flood risk
Figure 1. Example UI weather dashboards.
Forecast is clearly illustrated and dashboard designed nicely (40%)
Ability to handle more than one location and/or date/time (25%)
Ability to handle wide variety of forecast types (rain, heavy rain, flood risk, air quality) (25%)
Interactivity (for example selecting different language like French and/or Yoruba, dark/light themed) (10%)
Of course, the first steps are to create a profile here on Taikai and find other participants that are interested in your approach to developing this product. Once you've done that, create a project under this competition and go through the necessary steps.
We recommend using one (or more) of the following javascript frameworks when developing a desktop application. But these are just suggestions to get you started! There are many more tools you can choose from.
Examples of weather dashboards using Vue.js in particular can be found here.
If you find yourself on a team without any coding experience, try out Google Data Studio to practice building a general-use dashboard.
Please review the resources section for guides on how to use the dClimate REST API. Happy coding!
We recommend you copy the forecasts.txt file from the "Resources" section of the hackathon into a backend location of your dashboard app. You may also create your own .json version of the file, if it makes it easier for your app to ingest the forecasts.
If you cannot find the file, here is the content of forecasts.txt :
### BEGIN FORECASTS ###
Uyo, NG: January 18, 2021
Pressure: 1000.7 mb
Temperature: 29.5 C
Humidity: 77%
Condition: Cloudy
Wind: WSW at 5 m/s
Chance of rain: 80%
Uyo, NG: February 7, 2021
Pressure: 999.3 mb
Temperature: 34.7 C
Humidity: 57%
Condition: Cloudy
Wind: Unknown
Chance of rain: 20%
Uyo, NG: March 9, 2021
Pressure: 998.2 mb
Temperature: 34.9 C
Humidity: 60%
Condition: Sunny
Wind: NE at 15 m/s
Chance of rain: 20%
Accra, GH: June 9, 2021
Pressure: 1002.0 mb
Temperature: 32.7 C
Humidity: 68%
Condition: Partly Cloudy
Wind: Unknown
Chance of rain: 30%