Governments should consider implementing smart recycling using computer vision and machine learning to address major issues in waste management.
Some developing countries face major challenges in managing and disposing of increasing amounts of garbage. These countries have garbage piles that are more than 200 feet tall and require aircraft warning lights. The impact of rising volumes of garbage can be witnessed across the globe as reports have shown the increasing amount of waste on Mount Everest. Additionally, the volume of generated waste will be increasing by 70% by 2050. Hence, managing and disposing of such large volumes of waste can become even more challenging.
Governments must implement alternative methods of waste management and disposal such as smart recycling to address their challenges. However, government organizations must carefully analyze the existing challenges in waste disposal and management to find effective solutions.
Challenges with conventional recycling
Globally, governments are taking the necessary measures and urging citizens to practice recycling. However, these measures haven’t proven to be reliable as citizens may be negligent at times and garbage collectors and recycling facilities may make errors while sorting waste. Hence, an alternative would be using sorters for separating and recycling waste. Sorters have remarkably improved the process of recycling. Sorters use infrared cameras to identify the material composition of different objects. After identifying the material composition, mechanical sorters can organize waste with the help of blowers. After sorting recyclable waste, recycling facilities can sell the materials to manufacturing plants or brokers.
However, brokers and manufacturing plants have specific requirements regarding the type of recycled materials they will purchase. For instance, a plastic water bottle and a plastic salad container may have the same material of plastic, but a broker may not purchase the salad container due to food contamination. However, an infrared camera would sort these products together as they are made from the same material. In such conditions, conventional sorters can prove to be inaccurate. Hence, recycling facilities need to look for a more reliable alternative.
Smart recycling using computer vision and machine learning
Computer vision has shown its potential in identifying human faces accurately. Similar abilities of computer vision can be used to identify different types of waste. By combining computer vision with machine learning and robotics, recycling facilities can build robots that can perform automated smart recycling.
Smart recycling systems can consist of different sensors to detect metals and 3D laser and spectroscopic cameras to capture images. These images can be sent to a centralized cloud for analysis. Machine learning models can accurately identify various waste materials and send feedback to smart recycling systems. Such machine learning models are trained using large volumes of images and videos of waste items to help the system identify recyclable waste. Also, smart recycling systems can weigh waste items with the help of robotic arms to determine whether waste boxes or cans are filled with food.
In addition to waste sorting, smart recycling systems can gather data about different types of waste items that are collected. With such data, government organizations and recycling facilities can determine which types of recyclable waste are generated and how much garbage is generated on a monthly basis. Using this detailed data, government organizations can create waste reduction strategies and use the accumulated numbers to create public awareness about waste generation.
Along with smart recycling, governments can use IoT and AI for waste management. By combining smart recycling and AI-powered waste management, governments can streamline the entire process from garbage collection to disposal. With such modern technologies, governments can speed up waste management procedures and keep up with the increasing rate of waste generation. However, the problem of waste generation and management cannot be solved with technology only. Governments and people have to proactively reduce the generation of waste, use recyclable products, and spread awareness about the rising volume of garbage to address the issue of waste generation and management.
