How AI Helps Prevent Littering and Improve Waste Management

Littering has long been a matter of concern for governments across the world but, unfortunately, not for individuals themselves, who actually are the cause of this problem. The belief that there’s no consequence for improper disposal of trash makes people stick to their littering behavior. Meanwhile, the problem is growing. So is the negative impact on the environment and people’s health. Litter in public places and recreational areas not only affects their aesthetic value but is very costly for authorities to remove. What can be done to stop littering? Obviously, strict laws and penalties like those in Singapore work well. But without proper monitoring and reporting, you can’t make sure that offenders will not get away with littering. This is when AI-powered video analytics can come in. In this article, let’s have a closer look at advanced AI technologies which can help tackle this problem by automatically detecting discarded litter items and immediately notifying assigned endpoints.

The problem overview

A litter problem is quite common in modern society. Why do people intentionally fling rubbish, plastic packaging, food wrapping or cigarette butts? The reasons are different. Psychologists say that the decision to litter is often based on what people see around them. If the place is already littered, they are more likely to throw their waste just on the ground. Another important justification is the lack of trash receptacles nearby. Some people are just too lazy to walk to the bin. Others drop rubbish as they don’t feel responsible and hardly realize that leaving or throwing litter in a public place is an offence. Such an attitude develops into a habit and causes a number of serious consequences.

First and foremost, litter poses a significant threat to nature. It spoils urban environments and destroys the natural beauty of cities. It also contributes to visual pollution and decreases the quality of life of people living nearby. Beyond environmental and social considerations, littering does harm to people’s health. It facilitates the spread of infections and poses detrimental health effects. Besides, cleaning litter up from roadways, parks and streets is quite costly. The U.S. alone spends about $11.5 billion every year cleaning up litter, according to Keep America Beautiful.

What is the solution?

The ideal way to handle the problem of littering is to encourage each member of society to take responsibility and dispose of waste properly. Both individuals and businesses are more likely to do so if there are serious legal or financial consequences. All states have some type of litter law, with different penalties which vary according to the amount, type, and location of litter. Offenders are typically subjected to a fine, which ranges from $25 to $30,000 in different states. The court may also suspend a violator’s driver’s license or order litter cleanup and community service. In more serious cases, offenders may be imprisoned for sentences ranging from 10 days to six years.

Local authorities are responsible for keeping public places under their control, clearing litter and imposing penalties on people who break or ignore the law. Local authority litter wardens can issue on-the-spot fines for litter offences.

Why are litter laws ineffective?

Enforcing strict litter laws and other enforcement measures against littering in private and public places can’t be effective enough unless disposal of rubbish is controlled and fined in an appropriate manner. In fact, it is impossible to control every street and corner of the park, mostly because of the lack of people engaged. Furthermore, authorities cannot fine someone unless they see them littering.

How can AI help?

What AI can offer is to help implement 24/7 monitoring of public places and private facilities for litter left behind, thus helping authorities and facility owners to keep the area clean and safe.

● reduce littering in public areas

Given that public places are typically equipped with cameras, AI video analytics appears to be a viable solution for addressing littering in these locations. By deploying software that is trained to detect various types of rubbish, for example, food packaging, bottles, cans, plastic bags, paper and cigarette butts, among others, litter wardens can receive real-time information about the littering event, identify who leaves litter and where, and respond appropriately: catch a lawbreaker and issue a fine, or just remove discarded litter. AI models can process live streams from cameras or can be used to review video footage forensically.

Security drones used for video surveillance can become valuable help in the fight against litterbugs. Advanced AI-powered algorithms process footage from drones and automatically and rapidly detect discarded litter items, quantify them by type and brand, and create litter heatmaps. These are sent to waste managers to help them better understand and prevent littering in areas of their responsibility.

● tackle fly-tipping

Another unlawful practice that needs better control is fly-tipping. In comparison with littering, it means disposal of large waste and bulky items, such as old furniture, electrical items and big bags full of rubbish, in places which are not designated for that. By doing so, fly-tippers want either to dodge disposal fees or not to bother themselves with the attempt to find a local recycling center. Similarly, lots of people leave waste next to a public communal bin, which is also illegal.

Smart video analytics can immediately identify such events. Utilizing an abandoned object detection algorithm, the system detects left-over waste, spots the offender nearby, and automatically sends notifications to assigned personnel who can check the case and ticket the offender. Thus, technology will not only help make cities cleaner but also improve people’s behavior and encourage them to act more responsibly.

● prevent waste fires

Waste piles may contain combustible items and therefore present a fire hazard. When fires occur, they pose a great danger to the environment and human health due to the toxic nature of smoke and contaminants released into the environment by the fire. Regarding this issue, particular attention is now placed on computer vision-based solutions that can detect smoke and fire at a greater distance based on the images from thermal cameras, thus ensuring early detection of the danger. AI-powered temperature monitoring solutions integrated with thermal imaging cameras are utilized to enable continuous, real-time thermal scanning for overheating and a quick extinguishing reaction.

● prevent littering on highways and roads

Litter thrown from cars continues to cause problems for drivers and the environment. According to Keep America Beautiful, over 51 billion pieces of litter appear on U.S. roadways each year, most of which (roughly 38%) are tobacco products. Paper (22%) and plastic (19%) are the next largest types of materials.

AI and computer vision are being utilized to remotely detect vehicle-based littering offenses. Integrated into existing CCTV cameras, the system detects the most common litter types, including cigarette butts, cups, and fast-food packaging, thrown from vehicles, and registers the act of littering. Robust object detection algorithms can easily detect even small litter items such as cigarette butts at a distance, and effectively work with a moving background. An instant alert is sent to human operators for validation. They can review the footage, see detailed information about the occurrence and issue a penalty charge notice to the offender.

● provide insights for better waste management

To investigate and tackle problems, decision-makers require reliable data. Waste management is no exception. AI technology is increasingly used by different industries for this purpose. When it comes to littering, AI analytics can give a helping hand in better understanding and preventing littering and illegal dumping. AI analyses all the collected data and provides actionable statistics in the form of heatmaps and graphs. This can help assess the problems and make decisions on the necessary changes to provide better conditions for litter disposal.

Statistics gathered by AI solutions can be used to understand whether there are enough trash receptacles installed in certain areas and whether they are properly placed for effective garbage disposal. Heatmaps can give an idea of where foot traffic is higher and spot areas where bins tend to be overfilled. As a result, waste managers will make decisions on how often they need to be emptied and where to reposition bins that are being underused.

AI analytics can also play an important role in highway and road maintenance. With litter heatmaps, road clearance teams will always be well-informed on the situation on the side of the road so that litter can be cleaned more quickly.

The bigger the area of monitoring, the more difficult it is to keep an eye on it. AI video analytics embedded in surveillance cameras can facilitate this process by implementing real-time monitoring of the whole area through all the numerous cameras, detecting all the cases of breaking the law and providing information in a centralized way.