Infrastructure has become another hot word in post-industrial economies that are busy figuring out how they can renew all the physical plant that was constructed during their industrial past. The UK has established a National Infrastructure Commission amidst a flurry of proposed new initiatives involving high speed rail, and other new rail lines, a focus on new housing, as well as a continuing concern for ever faster broadband, specifically based on G5 technologies. American too, notwithstanding the President’s pronouncements, is also initiating new approach’s to established and renewing infrastructure from roads to bridges to airports.
Infrastructure, however, no longer relates to simply physical things, information infrastructure is hot on the agenda while social infrastructure pertains to all our organisational and indeed socially responsible administration that emerged during the 20th century and badly needs renewing. In the current editorial in Environment and Planning B, I summarise some of the key points about renewing our infrastructure. Many new kinds of models are being fashioned to deal with such problems which are now spatially extensive in a way their precursors were not, and integrating different sectors is now one of the key issues so that the wider impacts of new infrastructure can be assessed, as for example in the MISTRAL models being developed by a consortium of research groups in the UK.
You can get my editorial here.
Visited the Urban Dynamics Institute (UDI) headed up Budhendra Bhaduri (Budhu) which is a rapidly growing effort in data-driven technologies applicable to cities. This group which is based at Oakridge National Labs which began life in the war years as part of the Manhattan Project, focusses on research that is geared to understanding, predicting and resolving key urban problems using large data sets which are spatially extensive. It is one of the few groups around the world doing serious research into the science of cities, albeit data-driven in that the focus is on extracting urban patterns and processes from very large data sets. Traditionally these data sets have been based on imaging from remotely sensed data but are now being extended to social media and all kinds of real-time sensed data dealing with location, mobility, transportation and climate. Many of these projects utilise the powerful computer technologies established at Oak Ridge by the Department of Energy that runs the National Labs. At Oak Ridge, the UDI used the TITAN supercomputer for processing remotely sensed images that require various forms of deep learning in the extraction of pattern. TITAN is the fourth largest supercomputer worldwide (measured by petaflops – floating point operations per second which is greater than 10pb) but it is being replaced by SUMMIT and the lab could well take the top spot, overtaking China again – who knows.
The UDI’s most visible project is Landscan. This is a world-wide data set at very high resolutions – at various grains down to approximately 1 km resolution (30″ X 30″). let me quote from the web page: ” LandScan is the finest resolution global population distribution data available and represents an ambient population (average over 24 hours). The LandScan algorithm, an R&D 100 Award Winner, uses spatial data and imagery analysis technologies and a multi-variable dasymetric modeling approach to disaggregate census counts within an administrative boundary. Since no single population distribution model can account for the differences in spatial data availability, quality, scale, and accuracy as well as the differences in cultural settlement practices, LandScan population distribution models are tailored to match the data conditions and geographical nature of each individual country and region.”
I am a member of the Scientific Advisory Board [myself, Mike Goodchild (UCSB), John Harbor (Purdue), Nigel Davis (Willis), Karen Seto (Yale), and Luc Vincent (Lyft) were in attendance] and we visited Oak Ridge last week March 27-29 and I gave a talk to the Institute. Bhudu asked me to talk on Cities and AI and although I complained mildly that I didnt know much about AI, I have explored how neural nets can be used in models of design so I decided to talk about this. You can access and read my talk by clicking on this link that will give you the PDF
However the icing on the cake was a visit to see TITAN and the photographs above show a panorama of me along the bank of boxes which are thence arrayed in parallel in 8 rows, a truly massive machine. Also saw one like this at Harwell (Rutherford-Appleton) the other week at STFC !
I should not say this but I don’t remember much about writing the attached piece which is entitled ‘Technology and the Democratic Management of Urban Complexity’ but here it is: click here. Published by Acciona and from a book entitled S.M.A.R.T, it deals with a subject that I have not written much on as yet and maybe that is because it is so important that it is not easy to articulate and remember: this is the question of how we are to manage our new technologies that are increasingly underpinning how cities function in the short term – which doubtless after the smart city has been around for a bit – will turn into the long term.
The essence of the argument is that it is not technology that is significant – but it is I how we manage and how we organise ourselves to do this. I suspect in the next 25 years, there will be a massive push to regulate such technologies in terms of privacy, access to information, and the unfettered use of technologies that are disruptive and invasive. It could be, however, that we will all be run by the Gods at Google, whatever, but such a pessimistic view of the human condition and the future seems to be under ever greater scrutiny and thus may not be the outcome of current development in AI, machine learning, and all this hype. Democratic management of technologies is what I write about a little in the attached piece and this will increasingly, in my view, be where the focus will and should be in terms of our future cities.