The implications of the waste we produce
The three Rs of waste management are commonly referred to as the solution to our waste crisis. The principles of the first two, namely ‘reduce’ and ‘recycle’ are easy to understand, however, the processes and the inefficiency of ‘recycle’ are many times poorly understood by consumers and even businesses. Many still believe that recycling is an effective method to get rid of our waste, despite the fact that only around 9% of our plastic waste is recycled. Our systems have large gaps and the methods supporting the circular economy are missing even though we now have a clear understanding of what would be proper actions for its implementation and what their benefits are. Sooner or later, we will understand that the implications of our actions if we stick to the linear economy model are of socio-environmental nature and will threaten our well-being, health, and homes.
Where trash ends up largely depends on the customers and this is the first part of the problem. They may or may not collect trash selectively, and they may even discard their trash in illegal ways. However, the second part of the problem is how trash is handled by municipalities. A large share of the trash gets to landfills, which is responsible for methane emissions. Another significant part of the trash is incinerated, causing carbon dioxide emissions, a greenhouse gas heating up our planet. Some part of the trash, however, even ends up in our freshwaters, threatening marine life and waterways.
How will AI transform waste management processes?
Traditionally, waste management has been a manual process. Today, however, we are on the threshold of a technology-driven world in which artificial intelligence (AI), machine learning, computer vision, robotics are helping municipalities to eliminate the need for manual labor and increase efficiency.
The spillover effect
The above-mentioned technologies not only transform the way we normally manage waste but will also provide a range of solutions that will shape the way we manage and collect waste and at the same time will provide us with innovations for the recovery of raw materials from waste.
We will never look at waste in the same way. Moreover, we are living in a transforming society in which there is an increasing focus on waste minimization, the use of new materials, and the removal of inefficient materials from the system.
On top of this, there are also innovative solutions that offer the possibility of previously unimaginable processes that aim at getting rid of our existing waste, as we wrote in an earlier article regarding Beworm. Basically, the sky is the limit in how we use AI and modern technology: StartRocket plans on removing space debris using space-grade polymeric foam. Another company, Winnow Solutions, uses AI to weigh food waste in commercial kitchens.
Solving improper waste sorting
One particular area of opportunity for AI-driven solutions is the complex problem of improper sorting. Due to the variety of waste-material types and regulations, consumers find it difficult to identify the composition of waste items, which often results in a mix of recyclable and non-recyclable waste. One potential AI application is the use of image classification to identify and help consumers recognize the material composition and consequent recyclability of their waste items.
TeknTrash – AI incentivizing recycling
Manufacturers often do not have information about what happens to their product once it leaves the shelves of stores, although it would be useful information for understanding the lifecycle of a product. Al Costa, professor of big data and AI, founded the AI start-up TeknTrash with high ambitions to radically change the amount of information that is accessible to companies after the sale of their products.
TeknTrash relies on AI to locate products at recycling centers and match them to the shops they were sold. The technology allows the instant recognition of the discarded products and their geolocation. The innovation also obtains valuable consumer data by this process.
Companies need to register their products in order for TeknTrash to monitor them. TeknTrash also aims to encourage recycling because when customers take pictures of the product before it is discarded (whether it is theirs or others’) they can collect points for good recycling and even enter a competition. Then these points could be exchanged for money, perhaps even creating a source of income for vulnerable people. They will also get kudos from their community for their recycling efforts. The main idea is awarding people for good habits and implementing a solution to bring about a massive transformation via making people more aware of the products they are using as well as their end-life.
The AI behind the start-up identifies registered products as they pass on the belt of recycling centers and matches them with the shop. Machine learning basically makes it possible to recognize and categorize any product. All the data collected with the identification results in the so-called big data and allows companies to better understand their consumers’ purchasing and even usage habits. They, therefore, are able to avoid stockpiling, may change the product or its packaging, and can incentivize people to properly follow the third R of waste management: recycling. Blockchain technology ensures the credibility of the whole supply chain. Big data itself is only useful if there is an effort to efficiently interpret and use that data. And in the whole lifecycle of a product, millions of information pieces are ignored, even though they have the potential to not only standardize recycling and the use of alternative materials but also incentivizing people to be aware of their own decisions and the implications of those decisions.
Opportunities and obstacles
The idea behind TeknTrash is revolutionary because AI will definitely be able to help us handle our waste and understand more about our behaviors and also help us follow a better path. The idea may be even further refined and used for alternative purposes.
The major obstacle standing in the way of TeknTrash success at this point is going large-scale and overcoming the typical start-up problem of fundraising. However, TeknTrash switched the steps and first would like companies to register their products, so they can then take the next step in order to fundraise.
If the assumption holds true that data equals money for companies and TeknTrash is able to provide extremely useful information about the lifecycle of the product and consumer behavior, then the idea behind TeknTrash will be definitely valued by companies. The collected data is definitely beyond the traditionally obtained sales data. And this data can shape company decisions just like sales data.
TeknTrash is looking forward to the future with a major focus on growth. They already feel that they have significantly evolved from the original idea they started building upon and also hope that they will always incorporate new technologies and ideas.
The major transformation can only come when people are incentivized to act differently because they understand their impact on natural resources as well as the pollution resulting from their individual actions. Sanctions may only go so far, but the real change has to be one in which human behavior is also significantly shifted as a result of genuine understanding.
