Exploiting Big Data from Mobile Device Sensor-Based Apps: Challenges and Benefits

MIS QUarterly Executive Exploiting Big Data from Mobile Device Sensor-Based Apps: Challenges and Benefits

Sensor data gathered from mobile devices generates big data, which can help organizations continuously monitor a wide range of processes in ways that prompt actions and generate value. However, generating reliable data from such devices is not straightforward and presents a variety of challenges. This article describes the challenges and provides guidelines based on a case study of “Street Bump,” a mobile device app that the City of Boston uses to facilitate road infrastructure management.1,2

Daniel E. O’Leary University of Southern California (U.S.)

Sensor Data from Mobile

Devices Provides New Opportunities1,2 In the world of big data, organizations are increasingly turning to mobile devices as new sources of data derived from continuously monitoring a wide range of processes and situations. Mobile devices can facilitate the gathering of data from a diverse set of internal and external3 stakeholders, including employees, customers and citizens willing to “donate” their data. Moreover, this data can be used in myriad ways. For example, sensor data on how

agencies to insurers.4,5 an Facilitatedautomobile by is thedriven “Internet is providing of Things big benefits(IOT),” donatedfor organizations sensor data ranging generated from governmentfrom users’ mobile devices provides important new opportunities. As originally conceived, the IOT includes all kinds of devices connected to the Internet and to each other, generating sensor-based signals independent of human intervention. As noted by Ashton,6 “We need to empower computers with 1 Cynthia Beath, Jeanne Ross and Barbara Wixom are the accepting senior editors for this article. 2 An earlier version of this article was presented at the pre-ICIS SIM/MISQE workshop in Orlando, Florida, in December 2012. In addition to the workshop participants, the author would like to thank anonymous referees and special issue editors, as well as Chris Osgood and James Solomon from the City of Boston. 3 Piccoli, G. and Pigni, F. “Harvesting External Data: The Potential of Digital Data Streams,” MIS Quarterly Executive (12:1), 2013, pp. 53-64. 4 Vaia, G., Carmel, E., DeLone, W., Trautsch, H. and Menichetti, F. “Vehicle Telematics at an Italian Insurer: New Auto Insurance Products and a New Industry Ecosystem,” MIS Quarterly Executive (11:3), 2012, pp. 113-125. 5 Mann, T. “Data Driven: New Program to Fix New York City Streets,” The Wall Street Journal, August 30, 2013. 6 For a summary of the history of the Internet of Things, see Ashton, K. “That ‘Internet of Things’ Thing,” RFID Journal, June 22, 2009 (http://www.rfidjournal.com/articles/view?4986).

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their own means of gathering information, so they to identify potholes.”9 In 2012, the City of Boston can see, hear and smell the world for themselves, developed an app called “Street Bump” (see in all its random glory … sensor technology [that] Figure 1) to allow virtually anyone to capture and enable[s] computers to observe, identify and report pothole data using their iPhone. understand the world—without the limitations of human-entered data.” With this concept of the Figure 1: The Street Bump iPhone App IOT, humans play a relatively passive role, simply ensuring that their mobile devices are switched on and generating data. As further noted by Ashton:7 “people have limited time, attention and accuracy—all of which means they are not very good at capturing data about things in the real world.” In addition, with activities such as driving, it is dangerous or illegal for people to simultaneously perform the activity and provide

to capture that data and relieve humans of the responsibility.associated data. Mobile devices can be configured Although sensor data from mobile devices can help generate deep insights and create value, gathering this kind of data does have its challenges. Using sensor data is not simply a matter of connecting devices together. Instead, companies need to identify and address the Source: http://www.newurbanmechanics.org/ technical, behavioral, organizational and privacy projects/streetscapes/bump/ issues arising from mobile device sensor initiatives. In theory, drivers simply need to download Based on a case study of the City of Boston’s and activate the app, put their phone on the “Street Bump” app available for iPhones, this dashboard or in a cup holder and drive. Using article describes the emerging challenges and this approach, an army of mobile phone users proposes approaches to overcoming them. With driving the streets of Boston can replicate the Street Bump, users place their iPhone in their work of city employees traveling block to block, cars, turn the app on and drive. The app captures surveying streets and looking for potholes. data about the location of potential potholes that When a driver runs over a pothole, the phone are encountered, which can then be uploaded to captures the location of the pothole and then a central server. City of Boston managers actively sends that location to a cloud-based computer, mitigate the challenges arising from the app so which records the reported pothole information with the location of other potholes so that they to the city and to app users. can be scheduled for repair in a timely manner. that the data can be used to provide benefits both The Street Bump App of Boston, “[Street Bump] provides a new way for Specifically, as noted by Nigel Jacob from the City The City of Boston has over 800 miles of roads people to donate their data in solving public good 10 and repairs over 19,000 potholes every year.8 problems.” Street Bump is being recognized as an important emerging innovation. For example, City workers. As noted by Mathew Mayrl from the City ofHistorically, Boston, “We potholes probably have have been 30 identified to 40 staff by cityout there each day, and one of their responsibilities is of Boston Co-Chairs of the Mayor’s Office of New

7 Ibid. 9Urban Bump MechanicsApp Detects Potholes, (Nigel Alerts Jacob City and Officials, Chris Osgood), 8 Ngowi, R. “App detects potholes, alerts Boston city officials,” Associated Press, July 20, 2012 (http://www.youtube.com/ USA Today, July 20, 2012 (http://usatoday30.usatoday.com/tech/ watch?v=yxAYLA405pU). news/story/2012-07-20/pothole-app/56367586/1). 10 Ngowi, R., op. cit., 2012.

whose responsibilities include the Street Bump To improve the effectiveness, the city captured app, were awarded the 2013 Tribeca Disruptive the location of known objects, which were bumps Innovation Award.11 but not potholes. The app also uses different

Street Bump Technology movement and bumps, such as joints in bridges, The Street Bump app12 uses the mobile speedalgorithms bumps, to filterutility out damage alternative to streets sources and of phone’s accelerometer to detect potential damaged street hardware (e.g., manhole covers). potholes, and the phone’s global positioning These changes improved the pothole system (GPS) capabilities to gather location detection accuracy rate to between 30% and information of that pothole. As users of the app 40%. But even with this higher level of accuracy, drive around Boston, a constant stream of data managers still needed to have a person physically is captured by the iPhones and analyzed for identify the existence of a pothole before it “bumps.” Street Bump currently provides users with feedback in the form of a summary of the number of bumps and the length of the trip ofcould the beexistence confirmed of potholes as one is that a costly needed process; to be (see Figure 1). The user then decides whether therefore,repaired. the Unfortunately, city continuously physical works confirmation to improve to submit the bump data to the City Works the accuracy rate over time. Department, which is responsible for repairing potholes. If so, the data is uploaded to a server, available to the public to facilitate testing by and likely road problems are submitted to the individuals,City officials which has also resulted made in the useful app feedback. widely city via open311,13 For example, users discovered that the location of the phone in the car and the type of car could obstacles such as speed where bumps. they are classified result in different data being generated for the as GPS potholes software that maps need tothe be location fixed or of aspotential known same road anomaly. potholes with an accuracy of within 18 feet. If an adjacent bump is encountered, the two become Potential Benefits of a cluster, and the center is calculated as the Generating Data from Mobile midpoint between the two. The cloud servers to which the app sends data Devices are hosted by Connected Bits, Boston’s partner on Mobile device apps like Street Bump offer the the project, with the data stored in a MongoDB opportunity to provide continuous monitoring database. City users can generate queries to and thus generate big data. For example, mobile analyze the data collected in that database. phones constantly monitor location and other variables, such as heart beats, noise levels and Filtering Out Bumps that are not movement. These capabilities can generate Potholes Although Street Bump was designed for use provide direct, indirect and emerging future by citizens, the initial implementation has been significant quantities of data and ultimately restricted to data gathered by city employees. In late summer and fall of 2012, 25 employees benefits.Direct Planned Benefits used the app to gather data on bumps in the Mobile apps can continuously monitor highway. By the end of the year, the city realized situations and conditions from many different that Street Bump was only about 10% effective in sources or locations and from a wide range of determining the existence of a genuine pothole, users. The cost of gathering this data generated in rather than a speed bump or a raised or damaged real time is potentially low. In addition, it can be casting. Street Bump did not discriminate well analyzed and integrated with business processes between those different types of road anomalies. to solve problems.

11 http://www.tribecadisruptiveinnovationawards.com/?p=209. 12 The app can be downloaded at https://itunes.apple.com/us/app/ the United States is substantial. For example, in street-bump/id528964742?mt=8. The cost of finding and fixing potholes in 13 Open311 is a collaborative model and open standard for civic 40 crews working 24 hours a day, seven days a issue tracking. the winter and spring time, New York City has

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14 In the Potential Future Benefits case of Street Bump, rather than having crews In the case of Street Bump, the plan is to week, simply finding and filling potholes. mobile phone owners, thus reducing personnel, other systems that can facilitate the pothole equipmentfind the potholes, and other that costs task for can the be city. carried out by repairintegrate process. pothole For identification example, Street capabilities Bump could into There are many individual stories of how be integrated with a system that allows rapid potholes have “destroyed” everything from school response and resource allocation in the form of buses to Ferraris. Reportedly, deaths have even a pothole management system. Such a system resulted from potholes.15 Street Bump allows both could provide an improved capability to facilitate major anomalies in the road infrastructure and management of city resources and help guide resource allocation decisions and infrastructure investment. hazard,“emerging” thus potholes reducing to bethe identified costs of sopotholes that they to Street Bump has additional potential future can be fixed before they become a major traffic may indicate other highway management increasethe public. exponentially Speed of identification as the quality is particularlyof the road problems,benefits. For such example, as bridge the existence joint disrepair of potholes or deteriorates.important because the cost of fixing potholes can manhole cover disrepair or of the need for more extensive road repairs. Pothole data may also Indirect Benefits support the analysis of other city services. For As data is gathered using mobile apps, example, to what extent are potholes predictive of managers gain real-time insights into the processes being monitored. Continuous extent do potholes limit the speed of response monitoring generates data about the process, problems leading to police and fire calls? To what facilitating transparency and eliminating quality pothole databases to other databases information asymmetries.16 As data is gathered enablesof the police these and and fire other services? related Linking problems real-time to be using mobile apps, managers can align their investigated. actions, strategies, processes and organization with the information and knowledge generated Challenges of Sensor-Based from the processes being monitored. Organizations can use the insights into the Mobile Device Apps information asymmetries to generate competitive Although sensor-based mobile device apps or political advantages over competitors so they win the support of customers, voters, etc. challenges. We illustrate some of the challenges bycan describing provide significantthe experiences benefits, with thereStreet areBump. also to change processes and organizational relationships.New data When also it provides implemented the Street opportunity Bump, Information Systems Management the City of Boston found that it had over 300,000 Issues castings on the city streets and sidewalks. Sensor-based mobile device apps present Although some belong to the city, the majority challenges that require management decisions. belong to other organizations such as the water Managers need to consider what types of devices company. This has led to monthly meetings to an app will be available for and the scalability of keep both sides informed and allows tracking and the supporting infrastructure. They also need management of the condition of those castings. quality to meet business requirements. to ensureDevice thatStandardization. the data collected Sensor is ofsignals sufficient can vary according to the particular type of mobile 14 “City Grapples with Thousands of Potholes,” NY1 News, February 9, 2011 (http://www.ny1.com/content/top_stories/133598/ device, and various device characteristics, such as city-grapples-with-thousands-of-potholes). the hardware and operating system, can impact 15 Reeves, J. “Death by pothole,” The Post and Courier, December the signal. For example, the accelerometers 22, 2010 (http://www.postandcourier.com/article/20101222/ PC1602/312229952). used in different mobile phones vary. Thus, 16 Information asymmetries occur when two people have given the same input, the movement and shocks different information about the same thing. If one has additional captured by different types of mobile phones inside information, he or she can leverage or take advantage of that can be different. Accordingly, to generate a information.

consistent sensor signal, it may be necessary to Data Donation Management Issues standardize on a single type of device, at least Controls need to be considered when mobile initially. Alternatively, additional measures must devices are used to collect data donations from be put in place to make the signals and their the public. Organizations must also plan how interpretations similar. they will respond to the donations. Accordingly, In the case of Street Bump, the iPhone managers must consider the context of the accelerometer, the Android accelerometer and device use, user behavior and user incentives and other phone accelerometers and their operating expectations. systems generated different signals from the Context of Device Use. Although gathering same bump in the road. Further, different sensor data from mobile devices may seem Android phones had different accelerometers. relatively mechanistic, such data can be As a result, in order to ensure signal reliability and data consistency, the City of Boston decided context in which it is used. For example, Street that, initially, data would only be gathered from Bumpinfluenced users by found the use that of the the location device, ofincluding the mobile the iPhones. phone in the car, the type of car and which phone Infrastructure Scalability. Scalability of the is used make a difference to whether or not a supporting IT infrastructure can be a key concern when collecting data from mobile devices. As use of an app moves from a few users to many users, car,pothole a four is identified.wheel drive One vehicle, user noted found that 50 hedifferent drove facilities can be overwhelmed by increasing data the same route with two different cars. The first volumes. one over the same 3.5 mile journey. That same In the case of Street Bump, the City of userpotholes, noted whereas that the the location second, of a Jaguar,the phone found in only the Boston mitigated some of the scalability issues car also made a difference on whether potholes by initially capturing Street Bump pothole would be detected. information only from City employees. This User Behavior. User behavior can also

could begin to understand some of the key data in the case of Street Bump, a driver might managementprototyping approach concerns was associated taken so thatwith officials data consciouslyinfluence what slow thedown device or drive finds. around For example,potholes volumes before having to process and store the to better preserve his or her car, which clearly data from a larger number of users. Data Quality. The quality of technology potholes. Alternatively, although unlikely, drivers, in mobile devices can limit the quality of intentlimits theon providingpotential the success city withof the detailed app in pothole finding the information gathered from the devices, information could speed-up as they drive through compromising the precision and limiting the potholes. Each behavior would result in different use of the data for its intended purposes. The sensitivity of components such as accelerometers User Incentives and Expectations or GPS capabilities differs according to the device. Management.findings from the A keyexact challenge same environment. in using a mobile With Street Bump, location information from app to facilitate data collection is to ensure the iPhones is accurate to within 18 feet; therefore, app is used. If the app is too costly or there are multiple sources of the same anomaly can be no incentives for using it, there are not likely to be many data donations. In the case of Street Bump, the app was available as a free download, anused anomaly to triangulate at the to same get a betteror a similar fix on the location, actual minimizing the direct costs to iPhone users. thelocation. redundancy For example, in the whendata generated multiple users provides find Further, users likely anticipated that by driving better evidence for the existence and location of a with the app on in their car, potholes would be potential pothole or cluster of potholes.17

identified and the city would use that information to fix the potholes. There would be a direct user 17 “Boston releases Street Bump app that automatically detects Inbenefit addition, because users potholes may have on “felt the good” roads about they potholes while driving,” MailOnline, July 20, 2012 (http://www. beingused wouldpart of more a network likely that be identified provided andsignals fixed. to dailymail.co.uk/news/article-2176783/City-releases-motion- detecting-Street-Bump-app-automatically-detects-reports-potholes- driving.html).

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monitor road quality. All in all, there would be (or competition) that invited interested parties to propose solutions.19 When users donate data, they likely have Inherent Biases. Using mobile devices for expectationsdefinite incentives for how to using that Streetdata will Bump. be used. To data collection can result in various inherent accommodate those expectations, organizations biases. To participate, a user must have access to need to provide feedback in different situations. the device and app, and the context. If users do However, once the signal is received by the not have access to any of those three, they will organization, what kind of feedback should occur, not be involved in generating data, and resource and what events should drive the feedback to allocation decisions may be made to their detriment. As a result, using sensor-generated issue, since mobile devices work passively while data can result in a bias—a kind of “digital usersthe information are performing provider? other Toactivities, complicate it may the divide”20 between participants who can afford be that users do not notice that the devices are the app, device and context, and non-participants who cannot afford them. Street Bump does not capture information about To capture road infrastructure information users,generating which usable means data. there As is currently no mechanism configured, for with Street Bump, the user needs to have the app, providing feedback on whether a pothole was an iPhone and a car. Although the app is free, not everyone has access to an iPhone and car. This and incentives. may result in disproportionate amounts of data fixed,The thus sensor limiting data the generated ability to linkby Streetexpectations Bump being generated about some roads, which can result in greater attention being given to road a bump, citizen expectations are that the city infrastructure in some locations. To date, the City can influence expectations. If Street Bump finds of Boston has circumvented this issue because only city personnel are used for data capture. potholes,should be but able most to fix of it. those However, castings Street are Bump not ownedidentifies or maintained many more by casting the city. bumps18 As a than result, actual the Privacy Management Issues Mobile apps provide the ability to capture Street Bump. substantial broad-based sensor information city cannot fix many of the bumps identified by generated by individuals based on their behavior. Application Management Issues Although users can limit which information Application management is concerned with they will share by turning the app on or off, delivering the expertise, skills and solutions necessary to successfully build, run and evolve shared inadvertently, or life-style information applications. Applications provide the interface couldpotentially be embedded confidential in the information donated data. could As bea between the IT infrastructure and the user. result, data donation or data sharing can result Designing user-friendly interfaces requires in both the perception of and actual invasion the appropriate domain expertise. In addition, of privacy. Privacy concerns may also cause organizations need to understand the issues the user to be selective about when the app is associated with the inherent biases of using switched on. In addition, organizations may have mobile devices. to forego the advantages of personalization and Domain Expertise. Organizations may or contextualization because of privacy concerns. may not have the necessary expertise to develop Perceived Privacy Invasion. The perception of an invasion of privacy is illustrated by expertise must consider alternative options such accounts of how cities’ use of other technologies asthe outsourcing. specific app. The Those City of without Boston the outsourced appropriate the has compromised privacy. For example, there development of Street Bump, removing the need to acquire internal expertise about the app. The captured cheating spouses running red lights; outsourcer was chosen as a result of a “challenge” whenhave beenthe pictures reports onwere how sent traffic to their cameras home have as evidence, their spouse saw them with someone

18 Moskowitz, E. “App shows jarring role of cast- 19 Osgood, C. “Challenge: Build an App to Detect Potholes,” metal covers in Boston,” The Boston Globe, December (http://www.newurbanmechanics.org/2011/02/09/challenge-build-an- 16, 2012 (http://www.bostonglobe.com/metro/2012/12/16/ app-to-detect-potholes/). pothole/2iNCJ05M15vmr4aGHACNgP/story.html). 20 Norris, P. Digital Divide, Cambridge University Press, 2001.

184 MIS Quarterly Executive | December 2013 (12:4) misqe.org | © 2013 University of Minnesota Exploiting Big Data from Mobile Device Sensor-Based Apps: Challenges and Benefits else. Thus, an important question to address is gathered from users to personalize their usage. to what extent users will perceive sensor-based Unfortunately, the more personalization built mobile apps that can track their every move as an into the mobile device and app, the greater the potential loss of privacy. For this reason, the City Actual Invasion of Privacy. There can be of Boston has chosen to exclude all personal privacyinvasion issues of their associated privacy? with knowledge about information from Street Bump’s use to provide the user’s life style that can be discovered from maximum privacy. the donated data.21 Since sensor data from mobile Similarly, organizations can choose the extent devices is gathered unobtrusively, and potentially to which device capabilities are “optimized” for continuously, data could be gathered that would be intrusive to the data provider’s life. For determine the extent to which they will account example, the sequence of potholes provided by the specific context. In particular, organizations Street Bump could result in information about a sensor signals. In the case of Street Bump, the route to a hospital or doctor. If that information potentialfor context context variables information that influence includes mobile the typedevice of were made available to others, it might be used device (iPhone), relevant technology within the against the data provider in situations such as device (GPS, accelerometer), the location of the insurance policies. device (e.g., car type and location of device within The City of Boston aimed to build a “strong the car) and other factors. relationship of trust” as part of its citizen-centric The more fully the context information is approach. As a result, when capturing bump considered and used, the “better” the potential location, any user information is stripped from performance of the app at capturing sensor data the data. By stripping out user information, it is to accomplish the task at hand. Unfortunately, in some cases, providing context information can or investigate particular user behavior, thus result in loss of privacy. For example, if the user assuringimpossible data-provider to generate privacy. “user profiles” to analyze employs a unique context or the context includes Addressing privacy concerns can result in user characteristics, then the context can point substantial costs. If data is cleansed of many of its directly to a particular user. Thus, in the case identifying features, the ability of the organization of Street Bump, there currently are no plans to to generate knowledge from data can be limited. gather context information from citizens since the In the case of Street Bump, eliminating user and city wants to preserve privacy. pothole sequence information can severely limit additional knowledge that might be mined from Recent and Future Street the data. Bump Developments Selective Use to Preserve Privacy. As a result of privacy concerns, users are likely to be Street Bump is still evolving. Recent selective about the information that they disclose developments over the last year, some of which to the system. In particular, privacy issues may have been mentioned above, include: ●● At the time of writing, the donated data based app and how long it is turned on for. In the is generated only by city employees. caseinfluence of Street the timeBump, when users a usermay turnsbe selective on a sensor- about However, the City of Boston expects that the routes for which they allow the system to as the accuracy of pothole detection capture data. For example, the user might turn the increases, it will begin using data donated app on for day-to-day activities, such as driving to by citizens. work, but not turn it on for after-work activities ●● To date, the city has not actively tried to or trips for medical purposes. This behavior can engage citizens in data collection since it lead to potential biases in the information that is is still piloting Street Bump. As a result, generated. less than 5,000 users worldwide have Personalization and Contextualization downloaded the app. Although data from Different users have different Privacy Issues. users in other cities and countries is preferences. As a result, information is often captured, it is neither mapped nor used. 21 O’Leary, D. “Knowledge discovery as a threat to database security,” Knowledge Discovery in Databases, AAAI Press/MIT Press, 1991, pp. 507-516.

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●● Because of recent national and disconnect, managers may need to reengineer international concerns with privacy,22 processes within the organization—for example, Boston has discussed the potential by leveraging automation or alerts—so that the development of a “nutritional label” that organization can process and act on sensor data would indicate the key privacy protection appropriately. built into the app. 3. Design Personalization and ● The city is considering developing an ● Contextualization to Match Privacy app that is similar to Street Bump but Requirements is only used by city employees. The Organizations should determine the extent revised version would allow capture of to which users can personalize apps and design them accordingly. Whereas personalization more detailed data capture than would enables users to better meet their needs, the bespecific possible trip with information, data donated thus allowingfrom the greater the level of personalization, the greater public. ●● The city expects that, in the future, Street Bump will become an open source app, understandthe potential the loss unique of privacy.risks of the These initiative. conflicting thus facilitating collaboration with other influences must be balanced by managers who cities and developers. 4. Plan for Growth Organizations should anticipate the potential Guidelines for Avoiding growth of sensor data and leverage advanced technologies, such as cloud computing and the Pitfalls of Sensor Data MapReduce,23 to facilitate scalability. Sensor data Generation can be divided into multiple pieces—either at the Based on the City of Boston’s experience with device level or event level—so that the data can Street Bump, the following seven guidelines will be processed in parallel, which further facilitates help organizations avoid the pitfalls of sensor scalable solutions. data generation. 5. Set a Narrow Band of Device 1. Make Data Actionable Standards and Expand over Time For management to depend on and use the Organizations should initially choose to data generated from mobile device sensors, standardize on a particular device to facilitate it must be timely and reliable—i.e., it must sensor signal standardization from mobile be actionable. In general, such data is timely devices. Over time, the device options can be but may not be reliable. In the early stages of a extended to include related devices (e.g., iPads in project, it is important to assess the reliability of the case of the iPhone) or emerging new devices the data being captured, and then work over time that gain in popularity (e.g., in a recent poll, USA to improve reliability to achieve an acceptable Today readers felt that Android users would 24 level for the data’s ultimate intended use. outnumber iPhone users in three years. )

2. Prepare for Likely Organization and 6. Pilot Test with Employees Process Changes When possible, organizations should pilot The rate at which mobile devices and test mobile device sensor apps internally to apps collect sensor data may outstrip the more fully understand their use and effects— organization’s ability to react to the insights and to mitigate risks associated with unexpected generated from that data. For example, issues from engaging with customers or external stakeholders. Pilot testing will show how user

StreetBump can find potential potholes faster behavior with the mobile devices can influence than22 Satran, the R. city“NSA canData Fight fix Could them. Signal To Privacy reconcile War,” US this 23 Dean, J. and Ghemawat, S. “MapReduce: Simplified Data News and World Report, July 30, 2013 (http://money.usnews.com/ Processing on Large Clusters,” Communications of the ACM (51:1), money/personal-finance/mutual-funds/articles/2013/07/30/nsa-data- January 2008, pp. 107-113. fight-could-signal-privacy-war). 24 USA Today, June 26, 2013, p. 1.

results. For example, in the case of Street Bump, ●● Google Group: There is a Google Group snow and ice will likely cause drivers to slow devoted to Street Bump. As part of down and be more cautious, which will affect the the research, the author monitored sensor data recorded for potholes. contributions to that group. ●● Phone interviews with City of Boston 7. Offer Incentives and Feedback while personnel: Managing Expectations Solomon (Street Bump Manager, Mayor’s A mobile sensor app ultimately needs The author interviewed James to make a difference in the life of the data provider, so organizations need to ensure UrbanOffice ofMechanics), New Urban both Mechanics) from the and Public Chris that users can identify the value proposition WorksOsgood Department. (Co-Chair, Mayor’s Without Office their of help, New associated with donating data from their this article would not have been possible. mobile apps. Organizations should continually gather information about user costs and About the Author conducting periodic surveys. benefits, possibly by running experiments or by Concluding Comments Daniel E. O’Leary The huge amount of data generated from the Marshall School of Business at the University the sensors in mobile devices can offer unique ofDaniel Southern O’Leary California. ([email protected]) He is a former is a professor editor inof opportunities to provide continuous monitoring IEEE Intelligent Systems and the current editor of a range of processes, in real time, potentially Intelligent Systems in Accounting, mitigating information asymmetries. But Finance and Management. capturing and making use of the sensor data authorof John ofWiley’s Enterprise Resource Planning Systems, is not as simple as just adding a new data published by Cambridge University O’Leary Press, is which the source. This article has described the challenges has been translated into Chinese and Russian. His organizations face with sensor-based mobile current research focuses on technology-based device apps and provided guidelines for avoiding crowdsourcing and other emerging technologies. the pitfalls.

Appendix: Research Methodology

This study is based on data collected between gathered from multiple sources, including: June 2012 and July 2013. Information was ●● Social media: Street Bump and Connected Bits have Twitter accounts that provide insights. ●● News media: Several videos (for example, by the Associated Press) about Street

videos include interviews with City of BostonBump are personnel. available In on addition, YouTube. news These media, ranging from USA Today to The Boston Globe, have published articles about Street Bump.

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