Alba Challenge: Waste Trucks as Sensor Platforms
How can waste trucks provide high-resolution information on the state of urban systems?
ALBA Group, a leading global recycling and environmental services company with headquarters in Berlin is seeking qualified applications by startups to co-develop and deploy solutions that turn recycling vehicles into smart sensor platforms. This work will initially focus on street-quality (potholes & weather-condition) and can extend to the sensing of other urban systems.
We are looking for a startup with an existing proof of concept of a sensor and an analysis-platform in an industrial context. Resources will be dedicated for the implementation of the product over a 2-3 months experimentation phase.
The team will have to travel to Berlin to participate in up to two sprints (2-3 days) between October and December 2018.
English-language proficiency is required, Spoken competence in German would be a plus.
Partners on this project will have direct access to ALBA decision markers and will work closely with the dedicated innovation manager from both ALBA and BIA (formerly NUMA Germany)-side to accelerate the development. The support-package will include:
- 10.000 € to cover the expenses and enable the prototype-development (no equity taken);
- business and pitch-coaching by experienced mentors to develop a scalable business-model;
- on-demand support in user research and UX-design;
- greater visibility through inclusion in public events involving local startup ecosystem, city administration and other corporate partners in Berlin;
- access to global innovation-network to scale solutions.
Finally, the deployment and test of prototype will be organized in an experimental setup in Berlin with opportunities to build a commercial partnership.
// BUSINESS OPPORTUNITIES
- For startups, this challenge is the ideal platform to test a solution with a large fleet of vehicles & potential for scaling.
- For ALBA, this challenge expands the exploration of the usage of waste-trucks as sensor platforms.