Combating wildlife trafficking
What it does
Our approach is to use a combined flow of experts and machines to detect offending groups and track down influential individuals in that group. After that, information about the group association and tracing will be sent to the authorities for processing.
How I built it
- Front-end: Vuejs framework, nuxtjs
- Back-end: python flask
- AI: python
- Chatbot: Ramas framework
- Cloud computing platform: Digital Ocean We using cloud computing to connect independent component.
Challenges I ran into
In terms of project challenges, perhaps the biggest issue we faced was with privacy on social media. The second thing is that the receiving organization still has many problems in handling the results. implementation and handling of violations. In addition, because the duration is quite short, only the basic ideas of the Penguin team can be implemented.
Accomplishments that I'm proud of
What we are most proud of is that we have applied quite powerful technologies such as AI, Cloud, web, Rasa to this project. Also, in terms of the idea of implementation is very good and the impact of the solution is immeasurable.
What I learned
We upgrade our coding skill. Using new technology. Have more knowledge about wild trafficker.
What's next for Penguins sytems
In the future, we want to deploy into an automated system and network. From collecting data from social networks as well as receiving information from others, the creation of chatbots also helps especially in providing and finding information. Our core goal is to improve the accuracy of the system to the highest level possible. Thereby reducing the crime of animal trafficking on social networks. Although the scope is quite narrow, it is undeniable that its influence is very large and the ability to perform is completely possible within the technological capabilities of the penguins team.
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