LitterCam Featured in Fast Company for AI-Powered Approach to Tackling Litter
Vehicle-Based Littering
LitterCam, a UK-based technology startup, has been featured in Fast Company for its innovative use of artificial intelligence to combat littering from vehicles, an issue that costs England an estimated £850 million each year to clean up.
Founded in 2019, LitterCam has developed an AI and computer-vision system capable of detecting littering incidents in real time and linking them to vehicle license plates. The technology can be installed on lampposts or integrated into existing CCTV infrastructure, enabling cities to monitor known littering hotspots such as roundabouts and intersections. The system is already being trialled across multiple locations, including Kent, Central London, Essex, Scotland, and parts of the Netherlands.
LitterCam’s software is trained to identify the 10 most common types of litter, including cigarette butts, cups, and fast-food packaging. When an offense is detected, the system captures evidence of the act and the vehicle’s license plate. Importantly, the platform does not use facial recognition, and all data access is restricted to authorised law enforcement personnel. Each case is reviewed by an enforcement agent before a penalty notice is issued, ensuring human oversight remains part of the process.
In its coverage, Fast Company explores both the promise and the complexity of automated enforcement. While AI-driven systems like LitterCam could reduce direct interactions between police and the public, potentially helping to address certain enforcement biases, they may also increase the volume of fines, which historically can disproportionately impact low-income communities. The article situates LitterCam within a broader global debate about automation, fairness, and accountability in public enforcement.
LitterCam founder Andrew Kemp emphasises that the company’s core mission is behaviour change and environmental protection. Beyond enforcement, the technology can also be deployed on assessment vehicles to detect and geo-tag roadside litter, enabling faster and more efficient clean-up operations. This application could significantly improve road maintenance while reducing environmental harm to wildlife and waterways.
As Fast Company notes, it is still early days for the technology, and its long-term impact on littering behaviour and social equity remains to be seen. However, LitterCam’s feature highlights growing interest in how AI can be applied to environmental challenges and how thoughtful design and oversight will be critical as these tools scale.