AI is transforming ways of cleaning cities, managing waste

AI is gradually revolutionizing the way cities manage their waste, monitor cleanliness, assess the health of machinery in operation, and automate the cleaning of streets and beaches. Indian cities can learn from peer cities and deploy the power of Artificial Intelligence (AI) and machine learning to make waste management operations efficient, safe, and cost-effective

Imagine a city or town where waste is no longer a problem. Where garbage is sorted and recycled automatically, and landfills are empty. Where we can all breathe clean air and drink clean water; this is the world that AI and machine learning can help us to create.

Technology has profoundly impacted our lives, making things easier, more efficient, and more connected. We are witnessing innovations and use of existing technology tools to improve the world around us. The new and reformed use of artificial intelligence and machine learning is increasingly becoming popular worldwide. Waste management is one of the areas that is of interest to cities. However, the use of technology in waste management has been limited in India. We keep hearing sad stories from various parts of the country about sanitation workers killed by inhaling toxic gases while cleaning manholes. Artificial Intelligence offers significant potential to enhance efficiency, ensure the safety of workers, reduce costs, and improve overall cleanliness. Many case studies demonstrate successful applications of AI, robotics and machine learning in various cities, inspiring others to adopt similar approaches. By leveraging AI technologies such as computer vision, machine learning, and robotics, municipalities can optimize waste management processes, automate cleaning tasks, and enhance the overall cleanliness of public spaces.

In the vast realm of the Indian urban landscape, an embryonic potential awaits. Our cities and towns are fertile ground for imbibing the wisdom of modern metropolises. Adapting new technology can bestow seamless efficiency upon the tapestry of waste management operations.

AI and machine learning are being used to address simple waste management challenges. For example, Smart Bins are becoming popular everywhere. These are of different kinds. And then there is Trashbot. It provides real-time, adaptable feedback and engaging custom content reflecting what is being thrown away. When a person throws a waste item in the bin, it sorts the waste in the corresponding bin inside, and the user will get a helpful tip based on the thing he or she just threw away, acknowledging the completion of the process and educating the user through instant gratification. It informs users about waste and pollution issues, driving better recycling behaviours and ensuring the ROI of recycling programs.

Some other intelligent waste bins use technology to tell collectors about their fill levels. AI-powered sensors are integrated into waste bins to monitor their real-time fill levels. This data can be used to optimize waste collection routes, saving time and resources. Such bins are being used in Barcelona, Spain. The city implemented an AI-powered waste management system. Sensors in waste bins collect real-time data, enabling optimized collection routes—this reduced waste collection costs by 30 per cent and improved overall cleanliness. Using the technology, municipal corporations can also predict equipment failures or maintenance needs in waste management systems, enabling proactive maintenance and reducing downtime.

AI algorithms can analyse images of waste items and classify them into different categories for efficient sorting and recycling. Such sensors are also used in robotic waste collectors. In a video shared by the World Economic Forum on its social media channels recently, robots were seen cleaning beaches. In addition to picking up waste, they were also sorting it using machine learning and AI. They could also identify natural objects like shells and stones, leaving them undisturbed. These robotic sanitation workers with cameras and sensors could navigate beaches and identify and collect trash.

Robots, drones, AI & cleaning

Robotic cleaning systems are becoming specifically helpful in cleaning manholes. They are also applicable elsewhere, but such mechanisation of cleaning ‘’dangerous’’ spaces must be immediately considered in a country like India. Some cities are using mechanised cleaning, but it should be deployed everywhere. AI-enabled robotic cleaners with sensors and computer vision capabilities can autonomously clean streets, sidewalks, and public spaces, reducing manual labour and ensuring consistent cleaning.

Drone-based surveillance and cleaning can also come in handy in reaching difficult places or even ordinary places during difficult times. Drones with AI algorithms can monitor and clean hard-to-reach areas such as rooftops or areas with limited accessibility. Cleaning cities and streets after any natural disaster becomes challenging for municipal employees; drones can clean up debris after a natural disaster such as a hurricane or flood. They can also be used to clean solar panels, which can be difficult to reach by hand and demands human resources.

The City of New York used drones to clean solar panels on city buildings. The drones could reach the panels that were difficult to reach by hand, and they could clean them more efficiently than manual cleaning crews. Similarly, Singapore’s National Environment Agency has deployed autonomous cleaning robots that can navigate complex urban environments. These robots have improved cleaning efficiency and reduced the workload on human cleaners.

Intelligent Monitoring and Reporting

AI-based surveillance systems also assist the city sanitation team in ensuring cleanliness. Computer vision technology monitors public spaces and identifies littering or illegal dumping incidents. This enables prompt action and helps maintain cleanliness. Using data analytics for decision-making, cities using artificial intelligence can analyse data from various sources such as sensors, social media, and citizen reports, to identify patterns, trends, and areas requiring attention. This information can guide decision-making in waste management and cleaning strategies. New York City implemented the “Clean NYC” initiative, which uses AI-powered cameras to monitor public areas for cleanliness violations. This resulted in increased compliance with cleanliness regulations. AI-powered mobile applications can allow citizens to report cleanliness issues, such as overflowing bins or littered areas, providing real-time feedback to municipal authorities. Many of the cities in India have launched their version of such applications. People can report littering and any sanitation-related issues using GPS-based location sharing. Seoul in South Korea has a “Zero Waste Challenge” app which allows citizens to register waste-related problems and earn points for their participation. The app has increased citizen engagement and improved cleanliness. India too has made progress in this space and has deployed several innovative initiatives in waste management.

Some cities also have apps which enable citizens to sell their discarded items to junk dealers using mobile phones. Yet others have collaborated with tech giants like Google to inform residents about e-waste collection facilities, toilets, etc. Use of AI and machine learning in waste management is still in its infancy, but the potential benefits are vast. Indian cities must employ technology to build cleaner, safer and healthier cities.

Drone-based surveillance and cleaning can also come in handy in reaching difficult places or even ordinary places during difficult times. Drones with AI algorithms can monitor and clean hard-to-reach areas such as rooftops or areas with limited accessibility. Cleaning cities and streets after any natural disaster becomes challenging for municipal employees; drones can clean up debris after a natural disaster, such as a hurricane or flood