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The world produces an average of 2.12 billion tons of waste every year. This enormous number is expected to increase by 70% by 2050. The problem is big enough to warrant revolutionary advancements in recycling management systems.
Beyond just addressing a pressing issue, proper waste management also contributes to the livability of a city. Poorly managed waste services can turn any place into a breeding ground for diseases and urban violence. That’s not to mention the negative impact on the environment and the exacerbation of climate change.
For all their best intentions, governments and businesses are spending enormous amounts of money on waste management that’s inherently wasteful. They’re throwing away precious time and resources with collection routes that are poorly planned. These governmental and commercial bodies need efficient and sustainable systems to improve their processes.
That’s where smart waste management systems come in. Innovative technologies like artificial intelligence, machine learning, and robotics maximize the efficiency of waste collection and recycling. Particular attention is now being placed on computer vision, which has made strides in training systems to interpret the visual world.
Computer vision allows systems to recognize visual inputs and use the information to take appropriate responses or actions. Much like we use our human vision to make sense of the visual world around us, machines can derive meaningful information from digital images and videos.
Artificial intelligence (AI) is what allows the machine to think, while computer vision is what enables it to see. Smart recycling systems combine computer vision, machine learning (ML), and robotics to speed up the sorting process and increase its accuracy. The system may use a spectroscopic camera to capture images of the trash, after which ML identifies the waste materials and sends feedback to the robot, which then takes appropriate action based on the information.
Systems use large numbers of images and videos of waste items to train models to recognize the recyclables. Recycleye’s WasteNet, for one, has 2.5 million training images in its dataset.
In addition to sorting the recyclable materials, computer vision can also be used to gather data about the waste items that are commonly collected. This provides government organizations and recycling facilities with insights into the types and amounts of waste materials being generated each month. They can then use the information to come up with effective waste reduction strategies and public awareness campaigns.
A handful of AI-driven tools are now being used for smart waste management. Here are some of the noteworthy ones.
A smart waste bin is equipped with an intelligent system that detects its fill level and communicates the data to those responsible for waste collection. It’s designed to provide insights that help improve waste management.
Because sanitation workers know which bins are filling up, they can route the garbage trucks efficiently. This allows them to reduce costs and emissions by avoiding trips to unfilled bins. It also enables them to prevent dumpsters from overflowing and becoming a health hazard.
Smart bins use artificial intelligence, sensors, and image recognition to determine fill levels. Postindustria’s own research puts a spotlight on computer vision with an algorithm that relies on photos from cameras. To estimate fill levels, the researchers used semantic segmentation, which categorizes pixels into scrap, container, or background. It then computes the ratio of the image area occupied by scrap to that of the empty container.
Smart waste bins are not complete without a compactor to optimize waste storage, a solar panel to provide energy, and a closed design to keep pests out and slow down decomposition.
Waste level sensors measure fill levels and related data points. They work with many different types of containers, from mobile bins in commercial buildings to semi-underground waste receptacles in urban locations.
To date, these sensors have been relying on ultrasound technology, which is a cheaper but less optimal solution. But optical time-of-flight (ToF) technology, and even more affordable and high-performance alternative, is starting to take the spotlight.
Smart bin sensors are often packaged in a compact format, allowing them to easily integrate into bins of varying shapes and sizes. They require minimal energy, improve collection routes, cut down costs, and reduce carbon footprint.
The world fails to recover more than $200 billion worth of recyclable materials every year. AI recycling and sorting robots offer a solution.
Recycling robots use computer vision and machine learning to recognize waste management recycling items and send them to the right sorting bin. This AI-driven automation increases the recycling rates, minimizes health risks for human workers, and reduces emissions.
To optimize recycling management and potential, these robots tap into the same computer vision technology used by self-driving cars. They look at the incoming trash, analyze the material using machine learning, then make a decision accordingly. The waste products are either scooped up or left to keep moving along the conveyor belt.
On-board weighing systems accurately measure the net weight of a trash container as its content is being emptied into the vehicle. The data is electronically transmitted to an on-board computer or the head office. Advanced systems use solid-state image sensors to report the lift arm’s position and ensure accuracy.
Accurate measurement of each bin allows waste management collection companies to charge their clients correctly — larger customers no longer have to subsidize the services rendered to small-scale ones. Precise weighing also allows trucks to keep their collection at a legal capacity, which helps them avoid overload fines and minimize maintenance costs.
Real-time reporting of the trucks’ payload helps optimize collection routes. This equips drivers with the data they need to determine the best time to head to the transfer station or landfill without underutilizing the truck or overloading it.
From finance and healthcare to manufacturing and advertising, various industries are reaping the benefits of AI-powered tools. It’s time for waste management systems to catch up.
Here’s a rundown of the benefits of AI-driven waste management systems.
Smart waste management systems deliver insights in real-time. This means you no longer have to rely on assumptions to allocate resources. You’ll know just where to route your waste collection vehicles at any given time.
AI-driven systems also optimize the management of recycling and reuse of waste composites. Not only does this increase recycling rates, but it also improves the quality of recycled products you produce.
China used to absorb around 40% of the scrap materials from the United States. But this has changed after the former set a stricter contamination rate. China has mostly banned the import of contaminated recyclables. Now more than ever, the US needs to set stricter standards when it comes to sorting its recyclables.
With AI-driven tools automating waste management, you can expect cleaner streets. Overflowing bins will be a thing of the past. It’s hard to establish consistency when an area that’s prone to trash build-up today can be empty the following day. The insights provided by a smart system will help you handle the unpredictability of waste generation patterns. Garbage collectors can make it to the scene just before the bins are filled to overflowing.
Smart waste management systems cultivate environments that improve the working conditions for sanitation workers, increase productivity, and boost employee satisfaction. Drivers no longer have to make unnecessary trips to bins that are barely full, and trash collectors and sorters reduce their exposure to health hazards.
Smart waste management systems deliver data that give governments and businesses a glimpse of the unnecessary expenses they have in terms of time and resources. Organizations that struggle with tight budgets will know just where to trim the fat. They can optimize waste collection routes, reduce the contamination rates of the recyclables, and improve employee productivity.
Beyond just reducing expenses, waste management companies can also increase the revenue they gain from recycled products.
Oftentimes, municipalities prevent bins from overflowing by increasing the frequency of the collection rounds. This means that cleaner streets come at a cost. Not only does this increase fuel consumption, it also brings a greater toll on the environment.
With smart systems informing sanitation workers of the best time to collect waste at specific locations, drivers no longer have to make too many stops. They’ll be guzzling less gas and greatly reducing their carbon footprint.
Moreover, increasing the recycling rates can cut a huge chunk out of the piles reaching the landfill or polluting our seas.
Proper waste management stands to improve the standard of living and sustainability of any given location, particularly congested urban areas. With global warming and population growth threatening the livability of cities and municipalities all over the world, the powerful hands of technology need to play a bigger role. And you can count on AI-driven waste management tools to do just that. Effective recycling management systems are now within reach.
Ready to step up to the challenge? Postindustria offers a full range of services that will bring your vision to life. Our teams have the expertise to create solutions based on machine learning algorithms. They’ve highlighted waste management in research that explores the role computer vision can play in a smart system. Leave your information in the form above, and we’ll contact you to discuss your project.
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