How can artificial intelligence, computer vision techniques, and machine learning model help to take care of the environmental conditions, and why newspapers will disappear in a few years?

Our guest’s team has created a true game changer – a scalable solution using AI technologies that analyzes the visual data e.g. individual characteristics of the cut tree, such as the grain pattern, for classification, and thus identifying their physical characteristics. Such real-time technology and algorithms make it possible to catalog and localize every tree felled. Briefly speaking, computer vision and deep learning, help to reduce illegal logging and reduce environmental impacts. How else can IT companies support the fight for climate balance using computer vision and machine learning, and what is the forecast in this area? 

Meet Swapan Chaudhuri, CEO of Deeplai in episode 7 of the podcast by Applover.

Swapan Chaudhuri is the co-founder of a tech start-up, that focuses on fighting the degradation of forests in the world, in particular the problem of illegal logging, using e.g. deep learning, computer vision, and AI. Deeplai uses huge datasets, machine learning algorithms, and artificial intelligence, to identify and track felled trees. Environmental sustainability and efficiency are the overarching value that guides the development and implementation of its products.

His team has developed an AI and machine learning technology called Product Fingerprint that analyzes the individual characteristics of the cut tree, such as the grain pattern. These analytics, and AI, can be used to boost the catalog and track every tree felled, which helps in the fight against illegal logging. Product Fingerprint may prove useful in the context of new EU regulations regarding the ban on the export and import of products resulting from forest degradation. 

Chaudhuri emphasizes that the destruction of thousands of acres of forests yearly has a high impact globally, and is not only an economic problem but above all an ecological one. World Economic Forum draws attention to the fact that forests are home to 2/3 of all species on Earth and store large amounts of carbon dioxide, which is crucial in the fight against global warming. AI can help forests to be cared for, and new trees planted to ensure their survival for the predictive future. Our guest is also focused on combating illegal industrial practices such as counterfeiting and illegal sourcing. He pays particular attention to the wood industry in the context of environmental conditions and the impact on the lives of the next generations.

The “Product Fingerprint” technology can play an important role and be applied to other products, not only to wood. In the case of tires, the imprint is created based on the tread pattern, markings applied by the manufacturer, as well as information contained in the DOT code on the tire sidewall. This is just one example, but this one is becoming increasingly important, because the use of AI, allows verifying the originality of products at every stage of distribution. Manufacturers must enter all their products into the database at the end of production, and prevent placing counterfeit products on the market thanks to machine learning and artificial intelligence. Computer vision technologies, AI, bring enormous opportunities and capabilities to achieve the unknown by implementing workflow automation processing as well. The potential of computer vision models in the food industry is difficult to assess – how the technology can help confirm the authenticity and origin of food and eliminate waste.

What else you can hear about in this episode:

  • How to use computer vision in the fight against illegal industrial practices and environmental protection?
  • How can tech companies support pro-ecological attitudes and fight for climate balance daily? 
  • Which areas of the fight against climate change must be considered by founders in the first place? 
  • How does Product Fingerprint technology work, and what are its possibilities?
  • What challenges or obstacles have encountered our guest while implementing AI and deep learning solutions, and how he overcame them?
  • How does he envision the future of AI and ML solutions in the context of climate and environmental protection?
  • What are the development plans for Deeplai, especially in the context of the new EU regulations on forest protection?
  • What are the biggest challenges for sustainable forest management in the world, and how can Deeplai contribute to overcoming them?
  • What are the chances of extending machine learning technology to other forms of environmental protection?

Have we boosted your appetite for more?

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