Drug Detection Using AI And ML On The Dark Web [Explained]

    Artificial Intelligence (AI), as a field, has grown immensely over the past few years. The rapid growth of technology has automated tasks, making our lives easier. By automating redundant tasks, AI, and ML (Machine Learning) helps us focus on innovation and advancement.

    Drug Detection Using Artificial Intelligence

    A person who would have to be a clerk may now be academia, as we would no longer need humans for monotonous tasks. Such is the boon of AI in the present world. An excellent use that AI is to put it in detecting illegal drug trafficking. Drug trafficking is being carried out on an enormous scale. Social media and the dark web are two prominent sources for the sale of narcotic drugs.

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    The dark web is a popular hub where most of the drug smugglers and human traffickers dwell. Now that AI is playing a critical role in our lives, can it help put an end to drug abuse? Let’s find out.

    Drug Detection Using AI And ML

    Drug Detection On Social Media

    When Facebook, Twitter, and LinkedIn were gaining popularity, they did not regard the laws for criminal activities. Now that they account for billions of users, the enormous responsibility of protecting their users from illegal activities has become crucial for the safety of their communities.

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    To fight back against crime, social media firms are now using Artificial Intelligence and Machine Learning. Companies can use AI to embed real-time monitoring of threats while intercepting the dangers that criminal elements pose.

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    Now, Facebook doesn’t depend on users to report drug-related images. Instead, it uses AI to detect and reject inappropriate content. Other social platforms benefiting from AI are Twitter, Instagram, LinkedIn, and Reddit.

    Drug Detection Using Artificial Intelligence

    They use AI, which follows “Inspect, Report, and Ban” methods to remove potential bot accounts that tweet obscene images. Twitter uses one of its mainstream features, “Hashtags” to detect fake accounts and ban them instantly.

    While Facebook, Google, and Twitter are different companies with different work ethics, they still appreciate fighting against trafficking together, which is excellent.

    Drug Detection In Real Life

    Identifying drug dealers on the internet is easy compared to finding them in real life. Methods of detection which come into the picture either have a lower accuracy / higher failure rate or don’t get enough recognition in the ocean of endless ideas.

    Drug Detection Using Artificial Intelligence

    Image Processing plays a vital role in drug detection. It can detect if people are carrying weapons, are traveling with oversized backpacks that contain drug bundles, or even if there are dangerous animals or endangered species. With these ML and AI capabilities, we can now scan thousands of baggage and get details of suspicious behavior and much more.

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    By using the Geographic Information System, we can map and analyze the IoT sensor information to determine travel patterns, smuggling patterns, and examples of narcotic traffic. One of the most critical places where image processing is being used is the airports.

    Drug Detection Using Artificial Intelligence

    Despite all this effort, the way these dealers are spread across the world makes it harder to carry out the methods mentioned in this article on a large scale. The count of drug dealers is usually high in places where the economy of the country is declining.

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    The financial inability makes it difficult for the government to afford new technologies, which increase the number of smugglers. Even though AI is efficient, it takes a lot of time to improve the existing ML algorithms and to train models to detect every drug from the plethora pertaining to the world.

    code - "Drug detection using AI and ML"

    We can only hope for the best until faster ways to this are fabricated. So, as a conclusion to our original question, yes, AI can help us abrogate drug trafficking, but only when implemented efficiently, on a large scale.


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