Here at LUCA, we were very excited to see the news as we are also passionate about making cities smarter and more efficient by using Big Data – something which we started to do 4 years ago when we launched our Smart Steps product, providing groundbreaking transport insights to bodies such as Highways England, the DGT and a wide range of city councils across Europe and Latin America. We also recently expanded our technology to China, working alongside China Unicom to roll out our insights platform outside of Telefónica’s footprint.
Our Smart Steps product lead, Timothy McHugh said: “We’re particularly curious to see how the Uber Movement product works. As experts in population movement understanding and overcoming challenges such as bias and spatial accuracy have been key to delivering world class output, something we’ve always been eager to be transparent about with our partners and clients.”
We also think it will interesting to see how they take on the sample bias, given that, for example, almost three quarters of their user base in the US is between the age of 16 and 34. Equally, many countries aren’t just facing an urban traffic problem, and therefore need to understand the way people move between different cities to plan infrastructure and public transport more efficiently at higher level.
Overall, it’s clear that Big Data, and indeed Open Data, are going to disrupt the way cities are managed and therefore optimized in the future. We strongly believe that combining multiple data sources and validating new innovative data sources is crucial in enabling the public sector to make meaningful progress on the Sustainable Development Goals 11 and 13 (Sustainable Cities and Communities and Climate Action).
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As private sector companies, it’s important that we work closely with the public sector (in a sustainable way) to give back the value of data to society. We’re keen to see how Uber Movement insights could compliment our Smart Steps data in the future – “finding smarter ways forwards” together as their slogan suggests.
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