THE VIEW Positive Thinking ???? Bob McQueen

Bricks and mortar for a Smart City

Y ❝

The deeper understanding of prevailing traffic conditions that could be provided by analyzing the data repository could also be used to improve transit

operations ❞

ou have all these advanced transportation technol- ogy products and services that can be deployed to create a Smart City: how do you make sure that

these are all deployed in a coherent manner that pro- vides the best stewardship for public funding, leverages private sector motivation and moves forward incremen- tally in the right direction? One way to approach this is to consider the products and services as the basic building blocks or bricks that you will use to build your Smart City initiative. This analogy immediately raises the question of sticking the building blocks together-where do you get the mortar? Based on my exposure to big data and analytics over

the past couple of years, I would suggest to you that a data repository and an analytics capability can combine to pro- vide some excellent glue for the projects. Now, it seems that data is not a particularly attractive subject and it is difficult to convince most people that data is compelling, attractive and valuable. However, the results of collecting the data and subjecting it to analysis can be particularly fascinating especially to Smart Cities. These results can be enhanced considerably if data is drawn from multiple projects, brought together into a common repository, or “Data Lake” and then subjected to detailed analysis. The capability to establish, operate and maintain a

Bob McQueen is associate editor of Thinking Highways North America


“Data Lake” and apply advanced analytics has progressed in leaps and bounds over the past couple of years. In the past, we have tended to fragment and partition data to be able to manage it effectively. New developments in data science and data storage have made this fragmentation unnecessary and allow us to create “globs” of data (note my superb use of data science terminology!). What’s the advantage of a “glob” of data? The benefit lies in being able to address the data as one seamless data horizon, enabling pieces of data to combine and support the devel- opment of understanding and insight based on patterns and trends. Since the data is being sourced from multiple projects and multiple departments, the resulting data and analytics can also be shared, facilitating an enterprise wide view of all data and all analytics. This is the glue that can hold multiple, disparate Smart City projects together. For example, if probe vehicle data from Connected

Vehicles was assembled for an entire Smart City and combined in a “Data Lake” with road geometry and infra-

structure-based sensor data from public sources, it could form the basis for analysis work that would be interest- ing to multiple Smart City departments. Vehicle origin and destination information could be provided as input to land use and transportation planning. Detailed speed profiles along corridors could provide valuable input into advanced traffic management and traffic signal timing. The deeper understanding of prevailing traffic condi-

tions that could be provided by analyzing the data reposi- tory could also be used to improve transit operations. In this latter case, decisions regarding bus acquisition could also be better informed by having a better understanding of prevailing transportation conditions. Several Smart City initiatives have already identified

the need for integrated data exchange and the devel- opment of a data catalog that provides everyone in the Smart City with a clear view of the data available. I would put it to you that the Smart City “glue” could be made even stronger if analytics are shared on the same basis as data. Making data visible and accessible is an extremely valuable approach within a smart city, but it should be borne in mind that accessibility to data does not necessarily mean utilization of data. To encourage Smart City practitioners to use new data sources, it is extremely valuable to be able to communicate analyt- ics, use cases and ways in which others have used the data, to spur innovation. Ideally a Smart City community can be centered around the use of big data and analytics techniques to improve the full spectrum of transporta- tion service delivery from planning through design and deployment, to operations and maintenance. It is my belief that the smartest of cities will be able to

sense challenges and opportunities both within the city boundaries and beyond. These cities will also be able to apply intelligence to understanding the sensed data and develop appropriate response strategies. It has become clear that a focus on just data and information is not enough. It is necessary to manage a chain of activities including data collection and acquisition, information pro- cessing, the development of insight and understanding and the definition of appropriate actions, responses, and strategies. Regarding private sector organizations, my friends at Teradata refer to this as the “Sentient Enterprise”. Perhaps the smartest of cities will be “Sentient Cities”?

Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44  |  Page 45  |  Page 46  |  Page 47  |  Page 48  |  Page 49  |  Page 50  |  Page 51  |  Page 52  |  Page 53  |  Page 54  |  Page 55  |  Page 56  |  Page 57  |  Page 58  |  Page 59  |  Page 60  |  Page 61  |  Page 62  |  Page 63  |  Page 64  |  Page 65  |  Page 66  |  Page 67  |  Page 68