Eight trends that will shape the big data driven future of urban planning

Urban planning is being rewritten by big data tools

Big data will change the way we know our cities to be

It would be unfair to urban planners to suggest that data analysis is only now gaining grounds in the domain. Whatever tools planners had, they have been analyzing extensive data sets in designing the urban landscape. But undeniably, recent advancements in sensor and mobility technologies have truly converged the concept of smart cities into reality. And now, when we talk about big data application in urban planning, we emphasize on real-time data, connected devices and smart systems. A lot of it has to do with the fact that urban population is becoming increasingly mobile and planning dynamics are altering faster than ever expected.

Noticeably, some urban hubs are emerging as the hotspot of technology development and implementation. For example, Singapore has been in news recently for its LIVE Singapore! Initiative, a part of the Singapore-MIT alliance for Research and Technology (SMART), that uses smartphone data and sensors real-time to track and manage city planning in issues ranging from traffic congestion to predicting rainfall. Analyzing it and several other activities across the globe, I have presented some of the trends we are going to witness in big data based urban planning in the next few years.

Sensors, and more sensors, will flood the environment sparking data ownership and ethics debate
With Internet of Things (IoT) tech making rapid advancements, the types of sensors and their data type coverage will expand to never before levels. Most private enterprises, be it retailers, building owners, etc. will install sensors to gather and analyze consumer data for optimizing their operational expenses, energy usage needs, etc. With data ownership strongly linked to data monetization potential, we will also see battles between premise owner vs data owner vs device owner – as to who has the right to monetize the data. With many city areas falling under public places, ethics debate on what should be tracked and what shouldn’t will also get stronger.

Sensors, cloud based systems and public Wi-Fi will help city administration with better predictions
A recent report in Fortune highlighted how the City of Chicago is using public Wi-Fi and network of sensors, overlaid with historical data, to build better crime prevention mechanism and addressing legacy issues such as controlling rodent population. Cities are also giving free public Wi-Fi in select spots. Almost unthinkable a decade ago, geo-localized tweets can be a very useful in city planning esp. given the fact that conventional city planning paid little significance to factors of noise pollution and nightlife habits.

Building Information Modelling (BIM) will expand its horizons of activities
Conventionally used by building developers and planners, we are witnessing some really interesting and diverse examples in this field. The City of Vancouver is using Autodesk products to understand how the newly emerging high-risers will alter population movements, congestion and transit landscape. This power of information modelling, coupled with sensor data, can even make waste collection and disposal smart. Another example is that of Enlighted, a company that installs sensors into the lighting fixtures of commercial buildings, for better energy efficiency management. We’ll see many such new businesses evolve from the BIM platform.

Mobile apps will continue innovating to help consumers face less issues in city
For example, let us look at the Placemeter app. It gathers mobile app data to predict the extent of crowdedness in a location. Then you have apps such as Waze (acquired by Google) and Hubspot that share real-time traffic data on the roads. Innovators will keep on improving algorithms and technology to optimize data collection and analysis. In a way, such real-time and extensive data collection exercise conducted by mobile apps and devices will soon make a lot of open data redundant and obsolete – making the governments of the day dependent on private information owners for conducting its own activities (highlighted in the next point).

Local public sector will increasingly collaborate with private data owners
Let us first concede that data privatization will increase further as consumer adoption and usage of mobile apps increases. And most apps are privately owned and better focused on consumer data gathering as their monetization models demand that. Local governments are likely to forge partnerships with private data and technology owners in improving their urban planning efficiency. We’ve already started seeing this happening. During the 2014 Soccer World Cup, the city of Rio forged partnerships with travel apps Waze and Moovit to help with traffic management. In another example, AirSage analyses wireless carriers data, exclusively from two US carriers, to show population and market segment locations and movement patterns for specific geographic areas over time. Private data intermediaries buy this service from AirSage and then sell it to local governments for urban planning. We’ll see a lot more such collaborations and intermediary business models in the near future.

Private players will innovate business models around Open Data and in turn, improve urban planning outcomes
Real estate portal Trulia is a good example. It has a crime stats data for each property listing, pulling in open data from other sites as spot crime and crime reports. There are a number of other private players that are analyzing air quality and other data sets and turning them into useful health related dataset. We might also see local administration taking renewed interest in exploring and visualizing the trends in their own data sets. Overall, a lot of statistics lying unused from the past will find some use in the near future.

Data philanthropy will become private sector’s initiative to earn goodwill from local governments and consumers
Uber recently announced that it would share trips data with the City of Boston to help urban planners manage traffic congestion. We’ve also seen how Google comes forward to collaborate with local governments in tracking missing persons during a natural disaster or predicting Flu Trends. We might even see a push from technology companies to classify data donation as CSR. Notwithstanding that, this is a great trend. And large tech companies, facing the wrath every other day for being a hawk on consumer data, might always be interested in earning some goodwill.

Visualizations segment will see continuous innovations and improvements
Players such as Cityzenith and Synthicity (acquired by Autodesk) are some of noted upcoming players that will keep on designing newer ways to visualize urban data and expand their offerings to include platform IoT and big data services. I also think the maps application hasn’t seen its zenith yet. My view is that visualization potential of urban data still has a long way to go in terms of possibilities and we’ll continue to see improvements.

Despite all this, we have to be careful with connected technologies. If big data in urban planning isn’t managed in a secured way, it could fall into the hands of hackers, etc. And with automation of response signals gaining foothold in urban management, data security issues will not only remain confined to data alone – and could potentially create havoc in the urban habitats.

Anubhav, a data scientist, writes about new developments and future trends in the machine learning and data analytics domain.
He can be reached at anubhav@thinkbigdata.in
Follow him on Twitter at: https://twitter.com/think_bigdata

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