Guide to Building Data-Driven Organizations in the Public Sector

Remote Sensors

Team 2: Annie Ackroyd, Victoria Adair, Bret Petersen

Overview

This week’s readings for chapter 7 address how data is collected remotely and routinely from people in a city, and how it can be used to improve cities. The authors also consider privacy concerns related to large-scale data collection. In Social Physics, Pentland discusses the potential for data collection to inform a city’s approach to transportation improvements and public health efforts. In Reality Mining, Eagle discusses data collection and application with regard to transportation and crime prevention. Both authors argue that there are countless benefits to large-scale data collection for a city. However, the benefits must be weighed against individual privacy concerns, and steps must be taken to protect individual privacy. To this end, citizen involvement, disbursement of power, and effective policies are critical.

There are countless avenues for data collection in a city. Smartphones provide an endless supply of data on individual behavior, which can be analyzed at the city level to identify trends in where people eat, what they buy, when they drive to work, etc. Pentland calls this a city’s “rhythm” (Ch. 8). Cities also collect data using GPS information from cell phones and car navigation systems, traffic cameras, vehicle sensors, police reports, and street cameras.

Among the many potential applications of data for a city are the following:

Pentland goes so far as to argue that data collection has the potential to save hundreds of millions of lives by preventing (or containing) the next flu pandemic (Ch. 8).

However, dystopian novels have long predicted the consequences of the dissolution of individual privacy. Without effective regulation, legislation, and citizen engagement, it’s easy to imagine how the sensory system Pentland proposes could bring about a dystopian future. For example, according to Pentland, using data from smartphones, we can track the spread of diseases at the individual level. In Pentland’s words, “…we could take steps to reach infected people before they spread the disease further” (Ch. 8). But what might these steps entail? How far would we go to prevent a global pandemic? Would we compromise individual rights in the interest of the greater good? Should we?

Chapter Summaries

CH5 urban analytics: traffic data, crime stats, and closed-circuit cameras

The amount of data available for municipalities is vast and plentiful for analyzing metrics related to CRIME and TRAFFIC.

CRIME

Regionally specific data from local law enforcement, such as police reports, can be mapped in a way that helps identify patterns or trends in specific areas that lead to accurate predictions of what, where when and how officers need to prepare and respond. Data on TIME, LOCATION, DATE and INCIDENT TYPE are easily depicted in maps and can be utilized daily. Most cities have an internal Geographic Information System that can easily incorporate a “law enforcement” layer to be viewed as either a deterrent or a tool to prevent criminal activity or apprehend violators.

TRAFFIC

INRIX is a data analytics firm, the largest recognized in the text published in 2014, that provides data for numerous industries including the Public Sector, Automotive Mobility, Insurance, Advertising, Real Estate and Site Selection to name a few. I’d highly recommend you visit their website at INRIX.com for more investigation of the industry areas you may be interested in. I found it intriguing that things like Bluetooth sensors are installed along major roadways to accurately collect and calculate “real-time” vehicular speeds along interstates, and that the information can be instantaneously uploaded to GPS navigation systems found in many vehicles today. This allows drivers to better predict desired routes and avoid areas under construction or restricted due to an accident.

The author concluded that chapter by stating that “data is underutilized” and if used for good, could lead to better functioning and safer communities.

CH8 sensing cities

Pentland (2015) lays out arguments that cities can be more efficient and healthy if big data were able to be harnessed and used by the citizens to better manage public services.

First, Pentland discusses how big data is already being used to map activity patterns within cities. He argues that these observable behavioral demographics (largely collected by smartphones) are “more than four times as accurate as standard geographic demographics based on zip codes” (p. 142). By studying the behavioral patterns of the city, cities can be better planned and managed. He then uses transportation and health as case studies for how big data and social physics can improve public services, laying out short term (could soon be actualized) and long term applications of this information.

TRANSPORTATION (p.144-145)

HEALTH and DISEASE (p. 145-149)

He then proposes that social mobilization, tuning of social networks and leveraging social engagement are effective strategies to ensure that the systems are actually used by the people.

Key Take-aways:

References: