SPOTLOG and citcom.ai projects possible connections

On 12 April, the city of Mechelen, one of the SPOTLOG partners, organised a workshop, in Antwerp, focusing on urban logistics, within the European project citcom.ai, of which is a partner too.

Citcom.ai, European AI Testing and Experimentation Facility for Smart and Sustainable Cities and Communities, is delivering a European Artificial Intelligence Testing and Experimentation Facility (AI TEF) for Smart and Sustainable Cities and Communities (SSCC). The CitCom.ai consortium brings together world-leading TEF capabilities around the three themes of POWER, MOVE and CONNECT.

The main scope of the workshop was discussing possible topics for use cases around urban logistics, also defining synergies with SPOTLOG, by using data and Artificial Intelligence towards a more sustainable and efficient urban logistics.

The starting point for the discussion was that to aid in cycling policy-making, various sensor technologies can be effectively utilized. These technologies gather critical data, enabling cities to make informed decisions and create a more cycle-friendly environment. By leveraging these sensor technologies, cities can gain a comprehensive understanding of cycling patterns, safety concerns, and infrastructure needs. This data-driven approach allows for the development of targeted policies and infrastructure improvements, making cycling a safer, more accessible, and more enjoyable mode of transportation.

The following technologies were discussed:

•    Traffic Counters and Sensors
Installed on roads and bike paths, these sensors count bicycles, distinguishing them from vehicles. This data helps in understanding cycling traffic patterns and peak usage times, crucial for planning and improving cycling infrastructure.

•    GPS and Mobile App Data
GPS tracking in smartphones and cycling apps provides valuable information on popular cycling routes, average speeds, and trip durations. This data is essential for identifying areas that need better cycling infrastructure and for planning new bike routes.

•    Mobile mapping data
This data is collected by a mobile mapping sensor mounted on a moving vehicle.

•    Smart Bike Racks
Equipped with sensors, these racks monitor usage patterns, helping cities understand where more bike parking is needed and how often existing racks are used.

•    Wearable Devices
Cyclists' wearable devices can collect health and performance data, offering insights into the impact of cycling infrastructure on physical activity levels.

•    Environmental Sensors
These sensors measure air quality and noise levels, providing data on the environmental benefits of cycling and areas where improving cycling infrastructure could have the greatest impact.

And, in the end, 4 possible uses cases were proposed: 

• Reroute logistics transport based on sensor data in the city
• Change access rules of vehicle based on detected type and load
• Reservation system for loading spot on construction site
• Dynamic waste management