Kenya Power(KPLC) is the main power distributor and retails electricity to customers throughout Kenya.
KPLC posts daily planned outages on their official care account KenyaPowerCare.
The planned interruption schedules are posted in image format and include :
- The Region
- The Area
- Date & Time
- Locations within the area
The main inspirations for this project is:
- To be able to visualize and understand which parts of the country get more power interruptions than others.
- To be able to understand trends and patterns which KPLC use for their interruption schedules.
- To possibly automate the process of notifying citizens (via SMS/Email) about planned outages in there areas as soon as they are posted on the KenyaPowerCare Twitter.
The project is going to be a series and will go from scraping the planned interruption images from Twitter to analyzing and visualizing this data.
The steps I am going to take to achieve all this include;
- Scraping the images from KenyaPowerCare using this Twitter Image Downloader I built Twitter Image Downloader
- Extract Text from the images and converting them to txt file using Tesseract.js
- Cleaning, manipulating and analysing the extracted data using Pandas.
- Visualizing the data on a map.
- Automating the process.
In the next article I am going to take you through the process of building my Twitter Image Downloader.