In a recent interview the director of the QROWD project, Professor Elena Simperl, states that the goal of the project is ultimately to make transport in its various forms smarter. She goes on to explain that by making transport “smarter” she means improving the quality of available services that different transport operators offer to citizens, but also having better tools and IT service providers to support these processes, and helping those who define and implement policy to have a more informed view on what is needed.
“The approach that QROWD are taking to solve this challenge is unique in the sense that while we acknowledge the data and technology to realise the goals of the project, we are equally aware of the human factors that are part of the problem, but also a part of the solution. The platform that we’re building has a mix of human social and data components to realise these goals.”
The Qrowd project will run for three years, and the first year has just drawn to a close. During this time the first steps have been to consolidate the vision of the project. Fellow Southampton teammate Dr Luis Ibanez Gonzalez explains that the first stage of the project sought to understand how data from municipalities, from map providers and other areas can interplay together to create better services for the citizens.
The second stage, he further explains, was understanding the right place of humans in how to analyse this data: citizens that need to be engaged in the process to create better services; and also in the sense of human crowd workers to improve various stages of the data analysis process. Finally, the third stage was ensuring that what the project wants to achieve is still aligned with the partners’ agendas in particular, as well as authorities involved in the project.
Dr Gonzalez reflects on the first year of the project, especially on working with the project partners. “I think we have definitely learnt a lot from the interactions with the different partners. The problems that stem from the transportation and ability use cases have been very good – I’m very happy that we have found a lot of things that can help to realise those scenarios.”
“We in Southampton have been involved in projects with big data and data innovation focus for quite some time now, and for me personally we view this as an opportunity to work with partners like ATOS and the University of Trento, but also the chance to explore some business cases we had less experience in, which focus on transport and mobility.”
Over the past year you can really see people come together and start to work as a team, which is more difficult to achieve than some people would imagine. Projects take a long time to put together, but then when you actually get the funding and put together the team of people that will deliver that project you still have this learning phase where the teams on the ground need to understand and get used to each other, and then ultimately work together. That’s a huge achievement that everyone has brought so far.
Entering the second year we see a completely different vibe in the sense of a common purpose, which we think is very important in order to be successful. We have partners who are bringing technology expertise from industry as well as from academia, we also have business and domain experts both from the public and the private sector. Similarly we have companies that have a long track record of innovation management and are trying to develop together with us a sense of commercial and impact strategy for the project. It’s quite a range of activities and skills.
Both Professor Simperl and Dr Gonzalez speculate that the main contribution from the Southampton team is to bring in the “human factors” angle. This ranges from developing a more user-centric approach on how to design business cases, to expertise in social computing and crowdsourcing from projects such as SOCIAM.
In the next year, the QROWD project will advance in the development of the Qrowd platform, which will allow various data analysis processes. The team in Southampton give us a breakdown on the three core use-cases that have already been identified as valuable for citizens, municipalities and industry. These are:
- Completing mobility infrastructure
This aim of this is to gain deeper knowledge about existing infrastructure (type and position) based on crowdsourced data from citizens (app-based sensors and manual feedback). Crowdsourced data will extend to the analysis of availability/occupancy of mobility infrastructure.
- Better data for computing and estimating the modal split of the use cases to inform transport policies.
This type of transport service is very challenging and most service providers that are working in this space, including the likes of Google maps, are not very accurate in doing the modal split. It’s an understanding of what transportation services citizens are using in their daily routines. This is important to authorities to understand, for example, where to build the next bus station, or which new bus routes should be introduced based on demand, etc.
“Because we have this advanced platform that uses both the best of technology and crowdsourcing we can create labelled datasets that are used to train machine learning classifiers to provide the modal splits.”
- Decision support through the creation of the dashboard to allows citizens and municipalities to be more informed about transport in the city.
This is about analysing different aspects of transport and presenting them visually so that they are useful for individuals and communities. In order for smart transport to really be of value to cities it must be easy for citizens to actually see the value in it quickly and easily.
Both team Southampton and the wider QROWD project are looking forward to the next year of development. To keep up to date with the project developments you can check our website, follow us on Twitter @QROWDproject, or sign up for our newsletter below.