The Role of Big Data in the Waste Management and Recycling Industry

When it comes to waste management and recycling, the introduction of big data is causing a positive revolution. Big data refers to vast sets of information that can be analyzed via a computer. The computer uses this information to identify patterns, trends, links, and other factors that help humans determine the best course of action.

How is big data relevant to the US in terms of recycling and waste management? Well, the US is known to be a country bound to overconsumption of resources. The byproduct of this overconsumption is colossal waste generation; over 230 million tons of waste material is produced annually. Although 70% of such wastes are recyclable, less than 25% are actually recycled.

But what if we use the massive analytical and computational capabilities of modern computers to pinpoint problems so we can find precise solutions? That’s what incorporating big data aims to address. With such information, we can create solutions to improve waste management protocols, increase recycling statistics, identify risks, discover opportunities to minimize waste, enact better policies, and so on.

AI for safer and more efficient work

Researchers and scientists aim to use big data and artificial intelligence (AI) to make workplaces safer and more efficient. The recycling industry could definitely use these technologies to their advantage. You see, recycling is labor-intensive and has a relatively high risk of injury. But if the human factor is partially or fully replaced with intelligent machines, recycling becomes cheaper, safer, faster, and more efficient.

Good thing that this is already in the works. Two Denver-based companies have developed Clarke, an ordinary industrial robot modified to do recycling duty. The unique thing about Clarke is that the robot utilizes artificial intelligence to determine different kinds of food and beverage containers. It uses programs and algorithms to preemptively segregate them from the rest of recycling waste.

Fresh new data is constantly fed to the computer that controls Clarke, vastly improving the robot’s recycling capabilities. In fact, recent news shows that Clarke is now able to separate 60 boxes of recyclable items per minute with almost-perfect accuracy. It can identify new patterns and recognize new images, then applies this new knowledge during the next sorting round.

Clarke is just the first step. Pretty soon, with big data, we will be able to incorporate systems, technologies, and intelligent machines that make recycling safe, super-fast, and incredibly efficient. With fewer materials heading out to the landfill, this will be a huge relief for those in charge of waste management.

Improved inventories

According to an updated medical waste disposal guide, 5.9 million tons of medical waste from hospitals are generated in the US every year. These medical wastes include expired drugs, vaccines, chemicals, and similar substances. By inference, these are excess, unused stock. But because any number of people needs these substances at any given time, a medical facility’s procurement department finds it difficult to determine the exact amount of substances.

However, through big data gathered via new data-gathering technologies, such a facility can determine the optimal amount of inventory to minimize waste. Such information can be cross-referenced to other databases such as patient health records, local or national health statistics, pharmaceutical product distribution data, waste disposal schedules, and other sources. This allows health facilities to analyze their present procurement processes and adapt more cost-effective, less waste-generating ones.

Improved inventories aren’t just relegated to the health industry. All businesses that use inventories can take advantage of big data.

Satellite data for a bird’s eye view

We’ve been using satellites to look at our planet from the heavens. And it’s not looking good. Through satellite images, we can see that the Amazon forest is diminishing, the Great Pacific Garbage Patch is increasing, the Polar Ozone holes are getting larger, and vast swatches of corals of the Great Barrier Reef are bleaching.

Using satellite data from their cameras and sensors can give us a general view of the global environmental impact of human activities. For instance, by scanning ocean temperatures, scientists identified warming waters caused by global warming as the primary cause of coral bleaching. Major river systems such as the Ganges River in India and the Yangtze River in China are sending carelessly thrown garbage into the ocean, which joins the garbage gyre in the pacific. And through satellite information, we now know that there are ships that illegally dump bilge or sewage water once they leave a country’s jurisdiction.

Satellite data is crucial in gathering information that we can’t see at the ground or micro level. In addition to what it can give to science and research, such data can provide regulatory agencies with tools for environmental enforcement actions.

Better GIS analytics

A geographic Information system (GIS) is a framework for studying spatial and geographical data. Cities such as Stockholm are using GIS data to help alleviate their municipal waste problems. Specifically, Stockholm’s local government uses GIS to collect data such as the city’s waste weights, generation, collection locations, and collection frequencies.

Using this big data, the city was able to study the inefficiencies of many collection routes and schedules. These inefficiencies have been overlooked for quite some time due to the city’s past incapability to decipher the data. But with the aid of computational big-data analysis, the revelations enabled the city to find practical solutions, including the formation of a shared-waste collection vehicle fleet.

Stockholm serves as an example of how big data can be used in identifying still-existing patterns, procedures, and processes that are no longer practical or efficient in a rapidly growing city.

More accurate projections

If we continue cutting down the Amazon forest, what will happen 50 to 100 years from now? Given the existing recycling practices, what will it take to increase recycling statistics from 7% to 15%? If we reduce global plastic consumption even by 10%, how much landfill space will be able to conserve?

Using big data allows companies, organizations, and governments to identify patterns and predict outcomes in the long-term.

It’s with no doubt that big data is a game-changer when it comes to ecological preservation. The above points are just the start. As computing technology evolves, we’ll be able to draft better environmental policies, lessen waste production, implement more efficient recycling processes, and more. Big data will bring us closer to that green and healthy world that we’ve always dreamed of.