Challenges of Mobile Phone-Based, GPS-Dependent Gaming for Citizen Science

Abstract Citizen Science (CS) projects involve the public in data collection for a range of goals, from scientific to social health. Context aware gaming, where location-based information is used to inform gaming elements, can be leveraged to engage players in CS activities, attract new players, and act as quality assurance for data collected. Here we describe the challenges faced during development of the mobile phone-based CS game of Floracaching that uses the GPS sensor to grant players access to gaining points based on their physical location. Problems with the accuracy of GPS have been demonstrated to reduce player confidence in the functionality of the game and have led to abandonment of further play and data collection. We introduce a method for manually overcoming the GPS-based location inaccuracy in urban environments and evaluated its effectiveness on a university campus.

Author Keywords Participatory Sensing; climate change; plant phenology

ACM Classification Keywords J.3 LIFE AND MEDICAL SCIENCES; D.m MISCELLANEOUS; H.5.4 Hypertext/Hypermedia; H.5.2 User Interfaces

Copyright is held by the author/owner(s).

CSCW’12, February 11–15, 2012, Seattle, Washington, USA.

ACM 978-1-4503-1051-2/12/02.

Eric A. Graham, Dylan Vassallo, Sophie Gerrick,

Kyungsik Han, Jinha Kang, Nancy Hsieh

Center for Embedded Networked Sensing

University of California, Los Angeles

Los Angeles, California

egraham@ucla.edu, dylanv@ucla.edu, slgerrick@gmail.com,

zenithhan@gmail.com, jinhakang@ucla.edu,

nancyhsieh@ucla.edu

Figure 1. The home screen for BudBurst Mobile with access to the Floracaching game.

General Terms Human Factors; Design; Measurement; Reliability; Verification

Introduction Citizen Science and Project BudBurst Citizen Science (CS) and Participatory Sensing projects are research collaborations that enable non-scientist members of the public to assist with scientific provide substantial and unique datasets that have the potential for greatly increasing the volume of observational data for research, and include, for example, projects that ask participants to classify photographs of galaxies [1], report bird sighting data for ornithological research [2], or plant sunflowers and observe bee pollination [3]. Public engagement in scientific and technological issues has exploded in popularity in recent years [4].

Project BudBurst1 is a national CS program that involves non-scientists dedicated to recording the timing of life stages (phenology) of plants (e.g., the date when a plant first leafs out) and how this relates to environmental conditions. Data from phenological studies are increasingly relevant for addressing applied environmental and sustainability issues [5].

BudBurst Mobile (Figure 1) is the mobile phone-based extension to Project BudBurst. Although BudBurst Mobile was developed primarily as a record-keeping tool for Project BudBurst, it is also an example of a technology that supports civic engagement in issues that are of social concern [6, 7], and is thus an ideal platform for testing methods of engagement to participate [8]. Additionally, BudBurst Mobile is a

1 http://budburst.org

context-aware application, in that it leverages the location-based services available on the Android platform (GPS, WiFi location) in order to automatically send data collection parameters to the server.

Games and Floracaching Games have been used in CS projects to increase participation and the amount of data collected or processed [e.g., 1]. Indeed, games are natural extension for CS projects because often participation is based on enjoyment, with secondary motivations involving identification with the goals of the project [9].

Floracaching2 is a game within BudBurst Mobile that is similar to geocaching3, in that locations have been identified using GPS coordinates that players must find. In Floracaching, a plant occurs at the published location that players search for. Finding a Floracache (the plant) consists of being within 10 m, as determined by the GPS sensor on the mobile phone, and then subsequently using BudBurst Mobile to capture a photo and record the plant phenophase (e.g., first leaf, first flower, etc.).

It is desirable to allow volunteers to start contributing to CS projects through even low-level tasks [9]. Thus, finding one type of Floracache can be accomplished relatively easily, through a live map interface (Figure 2). Two other types of Floracaches are more challenging to find: a medium- difficulty level, with a compass direction and distance indication, and hard level, with only a description of the location of the plant that offers the most points per capture. Ranks or levels

2 http://floracaching.org

3 http://www.geocaching.com

Figure 2. The Map level for locating Floracaches. Note the messages indicating that the player is not within range after trying to capture the Floracache.

are obtained after accumulating sufficient points in the game and badges are assigned as a reward.

Challenges of Using GPS in Floracaching Problems with the accuracy of GPS in urban environments are not uncommon [10] and can be due to both temporary blockage of signals by buildings and terrain and also reflections off the sides of buildings, resulting in multi-path fading. The effect has been termed the GPS signal “near far” effect [11]. Forested areas with an appreciable canopy can also significantly block satellite signals [12].

The Floracaching game has been previously evaluated for performance and user experience using groups of volunteers [13]. During a more recent test of the game, 64% of the 22 volunteers indicated that while trying to find a Floracache their phone’s GPS sensor located them incorrectly. Erroneous GPS-based location data was common enough to delay or prevent the capturing of Floracaches for most of the players, even though they indicated that they had physically found the Floracache. Anecdotal information gathered from volunteers indicated that if a GPS error was encountered during their initial attempts to find a Floracache, the player was more likely to abandon the game than to continue.

Solutions for Reducing Location Errors Many hardware [e.g., 14] and software [e.g.,15] solutions to reducing GPS errors on mobile phones have been investigated. Using the reported GPS error has also been used to trigger feedback to a user. In one study, a mean error of about 15 m forced a context aware mobile application to use other information to remove positioning uncertainty [16].

We found that on the ULCA campus we could not rely on the system-reported GPS “accuracy” value from the mobile phone, which is calculated in part using the number of visible satellites and may be incorrect due to multipath errors [17]. Additionally, a backwardly compatible solution that is available to all smartphones that can run the Budburst Mobile application was desired.

Thus, we implemented a manual solution for players to adjust their locations using a pop-up map if they feel that they have found the Floracache but their GPS-based location indicates that they are outside the 10 m range (Figure 3). If the player is within 30 m of the Floracache, he or she is presented with a notice that they can adjust their location via a map (with no visible Floracaches) with the center being the current GPS-based location. The latitude and longitude are then calculated from the map and those coordinates are used for determining if the player is within range.

In most urban and suburban situations, there are sufficient landmarks (buildings and roads) for a player to be able to accurately indicate on a map where they are currently positioned. Problems may occur in parks or in more rural areas where landmarks may not be nearby.

Players may easily “game” the system using the pop-up map during the capture of the mapped Floracaches because the location will be easily remembered when the pop-up map is triggered. Gaming the system is more difficult in the two harder levels. Photo verification is required during any floracache capture, which may also reduce cheating.

Figure 3. Pop-ups used for refining GPS location: (top) indication that a player is close and (bottom) touchable map that allows a radius of possible adjustment, indicated by a blue circle. The revised location is indicated as a flag.

During a test of this manual solution for adjusting the GPS-based location for finding a Floracache, 6 volunteers each attempted to capture 25 Floracaches on the UCLA campus. Volunteers were instructed to stand within 3 m of the plant and attempt to capture the Floracache. Data on GPS-based location performance is presented as successful or failed captures (Table 1). Every volunteer needed to use the manual adjustment at least once during the trial.

Results varied considerably depending upon the device used. For example, one volunteer using a Motorola Droid successfully captured all Floracaches and required the manual location adjustment for 2 of the 25 attempted Floracache captures. However, a second volunteer using a Samsung Vibrant, which is known to have GPS sensor issues4, required the manual adjustment 36% of the time and completely failed to capture 4 Floracaches due to inaccurate GPS-based location beyond the 30 m limit for manual adjustment.

For all failed Floracache captures, the average GPS-reported distance away the volunteer was located from the Floracache was 43.8 ± 3.9 m, even though the player was always within 3 m.

Conclusion Games using on mobile phone GPS-based location may be confounded in areas near buildings because of inaccurately reported location. In order to not discourage players in Citizen Science-related activities, who may abandon the game if they initially encounter such errors, manual adjustment of location may provide a solution.

4 http://www.samsungvibrantforum.com

Acknowledgements We thank all the volunteers who participated in testing the Floracaching game and BudBurst Mobile application and Sandra Henderson from Project BudBurst for continued collaboration. We also thank the growing list of people who have contributed to the BudBurst Mobile Android and server code. Work was supported by NSF grant #CNS-0627084.

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Location Adjustment

None After

Captured 75.2 ±

22.7%

18.2 ±

15.3%

Failed 6.5 ±

8.8%

0.5 ±

1.2%

Table 1. Average percentage of Floracaches that were captured (± S.D.; n=25 Floracaches, 6 attempts each).

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