The inspiration is that intelligence is needed to combat wildlife trafficking, the basis of which is information. The internet provides a rich vein of open-source information which is a starting point for understanding the patterns, trends, and dynamics of the billion-dollar transnational illegal wildlife trade.

However, as all NGOs operate with resource constraints, short time frames, and stretched budgets, the challenge is to identify, extract and collate pertinent data from specific sources in a timely manner, an ability we’re currently missing because they're reliant purely on slower manual extract and replication methods.

WICS is a solution to essentially scan news reports on crime events to extract relevant information and then populate the Postgres database for future analysis.

Please refer to Global Problem Statement 10 of the 2019 Zoohackathon in Uganda. You can visit this link for more details

What it does

It allows a user to provide specific settings for periodic scanning of respective online applications. The user can as well manually insert links to websites they would like to scrape.

Nonetheless, automatic scanning from the user's preferred settings can still be performed. In this case, the user would find reports of the scans and they could optionally download the reports in different formats for archiving.

How I built it

We built WICS using Python, Postgres, Beautiful soup, Javascript, ReactJs, and Adobe illustrator. Please find a link to the application here.

Challenges I ran into

We faced issues designing clean, consistent, and easy to understand data model that can represent all expected data over time and reflects the real-world structure of the scraped sites.

Accomplishments that I'm proud of

I'm proud that my team was able to structure a working database and strong backend logic to effectively scrape a website and render the data in a graphical format for quick analysis.

What I learned

We learned about how to scrape a website for unique keyword arguments, use natural language processing and then parse that data in the right formats and populate a database with it.

We also learned how to generate relevant wildlife analytics from the data scrapped. We have learned that this will help to provide deeper insights into the wildlife conservation society when planning and allocating wildlife resources.

What's next for WICS - Wildlife Intelligent Crime Scanner

We plan to fully deploy WICS so that it can be used globally for targeted scanning of media to enrich counter wildlife trade intelligence efforts. We believe by doing this, we'll have broadened the net.

Going forward, we plan to add more artificial intelligence to the application by making the scrapping algorithm smarter.

We also plan to build for different platforms to address the issues of mobility.

Nonetheless, we are certain that more clear requirements will be realized as we get to build the application and work with the wildlife conservation society.

View the presentation.

The presentation was built using Focusky, which is free animated presentation software for delivering interactive presentations.

Please find attached a copy of the presentation and you can go right ahead to open them using Focusky. Follow this link below to set up Focusky on your respective device. You can also download the slides here (

This is the link to install Focusky;

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