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Description
As we transition to a low carbon, zero-emission future, the decisions we make around transport will play a critical role. Re:Hatch is an innovative R&D project that aims to use artificial intelligence and machine learning to help develop a digital solution to optimise transport.
People and businesses require better, more relevant information to help them cut through industry noise, automotive rhetoric and public misconceptions. Appropriate and engaging tools will be necessary to help people respond promptly and responsibly to the climate emergency. Behavioural change is traditionally a slow and challenging task. Through utilising technology in an innovative way, Rerwt aims to bridge the knowledge gap and speed up the time it takes for people to move away from damaging and unhealthy transport choices. Organisations will benefit from a data-drive consultancy service encapsulating statutory emission reporting, sustainable planning and organisational mobility support.
As Rerwt scales, local, regional and national learnings will support broader, longer-term policy, energy and infrastructure planning.
| Julia Chesney-Roberts | PM_PER |
Subjects by relevance
- Innovations
- Sustainable development
- Machine learning
- Decision making
- Traffic
- Emissions
- Enterprises
- Optimisation
- Energy policy
Extracted key phrases
- Innovative r&d project
- Unhealthy transport choice
- Hatch
- Critical role
- Low carbon
- Statutory emission reporting
- Emission future
- Innovative way
- Organisational mobility support
- Rerwt scale
- Drive consultancy service
- Artificial intelligence
- Digital solution
- Sustainable planning
- Challenging task