Cleaning – the right way! AI computers improve cleanliness in cities

Cleanliness as a calling card. Cities want to be seen as an attractive place to live and work. Cleanliness has a major impact on the appearance of a location – and thus on urban development. Not surprisingly, considerable resources are invested in keeping cities from Paris to Tokyo clean. But when it comes to cleaning, there is a lot of room for improvement, as startup Cortexia from Western Switzerland discovered. Andréas von Kaenel, who co-founded Cortexia with André Droux, says: "Cleaning is often done where it’s already clean and not where it’s necessary." His partner, von Kaenel, adds that cleaning is mostly based on experience and habit, and not on actual pollution.

Cortexia gained this insight from a survey carried out by the company in ten European cities. It also revealed that some cities spend an above-average amount on cleaning, but the general public is still dissatisfied with the cleanliness.

Cortexia decided to take on this problem. The company wants to improve the cleanliness of cities and simultaneously reduce costs and environmental pollution. They are doing it with Machine Vision (MV) and Artificial Intelligence (AI). The Cortexia solution is already being successfully used in numerous European cities. It consists of a camera, an AI-enabled embedded computer from Syslogic, AI algorithms, and a web-based customer interface.

AI Computer on the Edge detects pollution

The hardware, consisting of a camera and an AI computer, is installed on vehicles that regularly travel in cities. That includes municipal vehicles, courier bicycles, postal tricycles or buses. The camera captures the surroundings. The images are not stored, but processed directly by the Cortexia Box. The level and type of pollution are determined in real time. Andréas von Kaenel says: "Right from the start it was clear to us that we wanted to carry out the image analysis on the Edge." According to von Kaenel it has two key advantages over the downstream evaluation. The data volume would be kept small and data protection would be ensured, as no images from the public space would be stored.

This is due to the fact that the collected images are processed and evaluated in real time in the vehicle. The vehicles can travel at up to 50 km/h (30 mph). All pollution types are assigned to categories. Depending on the category, measures for removal are suggested. Cities can also define pollution categories, be it syringes, broken glass or excrement, which they want to have removed immediately. If such contamination is detected by the system, an alert is triggered. Immediate removal can be ordered, so that a cleaning team can be sent to the appropriate location.

Cortexia shows how cleanliness is achieved

This example shows that Cortexia does not only assess the cleanliness of a city. Rather, the company provides significant support to cities in improving cleanliness and thus increase satisfaction of the local residents. Results from surveys also flow into the Cortexia solution. Pollution types that are perceived as particularly disturbing by the population can be prioritized for removal.

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