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How trash object detection from a drone can halve the overall detection and collection cost

Technology CV
Industry Government
Potential industries Real Estate, Logistics, and Transportation, Construction
Client Semi-government real estate organization


For a large semi-government organization, our team developed a system that detected litter objects from images captured by drones and helped to manage trash collection activities. We designed and developed a GIS-based application that allowed convenient interaction with detected litter objects and facilitated trash collection activities via optimal route planning and tracking of the collection progress.

This resulted in significant cost savings, halving the overall detection and collection costs. Furthermore, the collection time decreased by a factor of 4 while the automated computer vision solution allowed a 7% higher detection accuracy compared to a human expert. Additionally, this system decreased carbon footprint by a factor of 19.



Municipalities are frequently grappling with the issue of graffiti that appears overnight on their city walls. Locating these graffiti spots and organising their removal can be quite challenging and time-consuming. Manual methods of detection are often inefficient and can lead to delays in the graffiti removal process. Hence, there was a strong need for an automated, precise, and efficient solution to quickly detect and localise graffiti around the city.

Solution by AI Superior

To address this challenge, AI Superior developed an advanced model that enables rapid, real-time detection and localisation of graffiti. Using a vehicle equipped with a 360-degree camera to patrol the city streets, our solution applies deep learning algorithms to detect graffiti with high accuracy and capture photographs of it in real time. Each detected graffiti spot is accompanied by the GPS location of the vehicle at the time of detection.

This information is then transferred to an interactive map with markers. Each marker identifies a graffiti location on the map, enabling users to see the exact location and 360-degree image of the graffiti. Relevant metrics, such as the total number of graffiti spots, graffiti density map, and average size of graffiti, can also be extracted from this platform. Furthermore, this solution is versatile and can be adapted for detecting other objects like trees, garbage, traffic signs and more.

Outcome and Implications

AI Superior’s graffiti detection platform has revolutionised the way municipalities manage their graffiti removal operations. By automating the detection and localisation of graffiti, the platform saves substantial time and resources. City cleaning teams can now swiftly identify and prioritise graffiti removal, optimising resource allocation and enhancing urban aesthetics.

In addition, this platform’s adaptability to detect other types of objects opens up myriad opportunities for city management. Municipalities can leverage this technology to manage various other aspects like tree maintenance, waste management, and traffic sign monitoring. Overall, this innovative platform ensures efficient city management, enhancing both safety and aesthetics

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