List of Figures

Chapter 1. Location-based services: an overview

Figure 1.1. Makeup of a location-based service illustrating the four key components required to deliver a fully functional service to the user of the service

Figure 1.2. This iPad is running the Yellow Pages LBS application, currently one of the most downloaded iPad applications in the United States.

Figure 1.3. RFID chips come in all shapes and sizes, including implantable chips that can be used in the healthcare industry to diagnose disease, for example.

Figure 1.4. Global map of popular location-based mobile social networks across the globe, which have been increasing in popularity and count more than 60 million estimated members in total

Figure 1.5. Google’s Nexus One smartphone, launched in January 2010 and featuring the latest version of the Android operating system, marked Google’s attempt to gain greater control of the mobile ecosystem.

Figure 1.6. Elements of the contextual Holy Grail in the case of a skier

Figure 1.7. Nokia’s Eco Sensor handset prototype with heart rate sensor was also designed to detect pollen levels in the atmosphere and alert allergy sufferers to this environmental hazard.

Figure 1.8. Twitter’s release of its Geolocation API in November 2009 allows third-party applications to pull geotagged content directly from Twitter users, making a whole new set of location-aware mashups possible.

Figure 1.9. Square allows anyone with a smartphone and its proprietary add-on device (or dongle) to accept credit card transactions in the same way as a traditional merchant account. The screenshot shows how this electronic payment would appear on the customer’s iPhone.

Chapter 2. Positioning technologies

Figure 2.1. Cell tower triangulation works by detecting distance of a cell phone from the radii of three separate cell towers. The cell phone’s location is where the three radii overlap (figure courtesy of Chris “Silver” Smith at mng.bz/OQf3).

Figure 2.2. Planned orbit ellipse of GPS BIIA-28 satellite around the earth (courtesy of NASA) as of June 7, 2009, at 11:10 a.m. GMT

Figure 2.3. Triangulating from three different satellites allows a cell phone’s position to be narrowed down to one of two points, point A or point B, where the three spheres representing three separate satellite fixes intersect.

Figure 2.4. A Belkin Bluetooth GPS device that can be connected to a mobile phone to provide additional GPS functionality

Figure 2.5. Comparison of the accuracy of cell tower detection used by Google Mobile Maps in an urban and a rural environment. Although the location picked up in downtown New York City is accurate to within a few hundred meters, in a rural town like Slater, the accuracy is reduced to several kilometers.

Figure 2.6. Skyhook Wireless’s Wi-Fi point coverage map derived from its database for North America

Figure 2.7. Schematic description of how P-Cell technology is designed to capture a mobile device’s location (courtesy of CELIZION Inc., Korea)

Figure 2.8. Picture of an STMicroelectronics LIS2L02AS two-axis accelerometer unit. On the left we have the standard view. On the right we see an X-ray image of the unit with micro-components, showing the MEMS (MicroElectroMechanicalSystems) and ASIC (application-specific integrated circuit) wire-bonded together and mounted side by side in the package. A three-axis version of this is incorporated in the iPhone and other smartphone devices to allow it to detect rotational attributes like pitch, roll, and yaw movements (source: mng.bz/kG2q).

Chapter 3. Mapping

Figure 3.1. Two different maps of Salerno, Italy, from two different sourceshttp://compete.com

Figure 3.2. Map, satellite, and terrain views of Spirit Lake, Iowa

Figure 3.3. Result of geocoding “1 Times Square, New York, NY”

Figure 3.4. Traffic of major map destination websiteshttp://compete.com

Figure 3.5. CloudMade Style Editor

Figure 3.6. NAVTEQ’s own Java applet showing Central Park, New York, with a 45-degree tilt at http://navteq.com

Figure 3.7. Tele Atlas map data of Central Park, New York, seen through Google Maps

Figure 3.8. Tele Atlas global coverage map (from Tele Atlas website)

Figure 3.9. OpenStreetMap data of Central Park, New York, at http://openstreetmap.org

Figure 3.10. Fire Eagle overview (from Fire Eagle website)

Chapter 4. Content options

Figure 4.1. Centrl.com application with restaurant and discount layers. Green icons (with knife and fork) represent the discount layer, and blue icons represent the restaurant reviews layer.

Figure 4.2. OpenLayers GeoJSON tool showing the GeoJSON encoding of shapes drawn on the map

Figure 4.3. MapQuest map displaying restaurants, hotels, and gas stations in New York City

Figure 4.4. User-generated content for seafood restaurants in London on Google Maps

Figure 4.5. The architecture of a typical mashup application. The mashup pulls data from various different sources, such as the web, RSS feeds, and databases, and puts it together (source: mng.bz/88yF).

Figure 4.6. Intel Mash Maker in action mashing Facebook and Google Maps

Figure 4.7. Chicago Crime Map

Figure 4.8. Yahoo! Pipes in action

Figure 4.9. Yelp business listings on a Google Map

Chapter 5. Consumer applications

Figure 5.1. Telmap’s mobile solution

Figure 5.2. High-resolution 3D views of the Tower Bridge in London and the Eiffel Tower in Paris as depicted by Ovi Maps’ City Explorer service on mobile screens

Figure 5.3. An example screenshot of Ovi Maps’ Drive in-car routing on a mobile phone screen providing real time, turn-by-turn navigation using GPS

Figure 5.4. The WHERE widget library, where developers could publish the mobile widgets they built using uLocate’s mobile location platform.

Figure 5.5. Screenshot of uLocate’s Traffic application for the iPhone showing traffic hotspots on a typical road route to a user destination in Boston, Massachusetts

Figure 5.6. Screenshots from Google’s Android-based Maps Navigation application, currently free in the United States on a limited number of handsets, including the Motorola Droid

Figure 5.7. Comparison of a selection of popular location-based mobile social networks available on iPhone (Source: TechCrunch, 2008)

Figure 5.8. Google Latitude screenshot showing the location of three different connected members of the service within the midtown area of Manhattan in New York City

Figure 5.9. Whrrl screenshots of its iPhone application depicting public events happening in the neighborhood and an individual photo story provided by a member of the service

Figure 5.10. Whrrl’s home screen on its website allows all users to browse through public stories made up of geotagged photos taken by members of the Whrrl community and also to link up with other members who are close to the location of the story.

Figure 5.11. Loopt screenshots of its mobile application showing where users are located on a map, which friends are online, and what messages the Loopt community has been leaving recently in the area of the user

Figure 5.12. GyPSii latest iPhone home screen showing downtown Amsterdam (Netherlands) and its Places screen showing POIs according to distance from the user and date of last update

Figure 5.13. Sniff’s integration with Facebook has been core to its service since launch, pointing the way for subsequent players in the market.

Figure 5.14. Friendticker allows members of its community to check in at precise locations and thus place themselves with less than a 1-meter error anywhere in the city. Friendticker defines this new concept as hyperlocalization.

Figure 5.15. Friendticker’s stickers are NFC-enabled but also incorporate QR (Quick Response) codes that can be scanned by the handset’s video camera to register the user’s position. In addition, users can send an SMS with a unique numerical identifier for each sticker that tags the user to that location.

Figure 5.16. Google adopted a similar strategy to that of Friendticker in 2010 by distributing over 100,000 QR stickers to local businesses across the United States in an attempt to bridge the virtual world and the real world.

Figure 5.17. Groupon’s iPhone application (of which two screenshots are she figure) allows users to find special offers, or Groupons, near their location as detected by the mobile device.

Figure 5.18. Screenshots of GPS Mission iPhone application illustrating available missions according to the location of the player

Figure 5.19. Geocaching iPhone application screenshots, allowing players to navigate within their neighborhood and identify hidden geocaches

Figure 5.20. Foursquare screenshots showing the Check-in button for users, special offers locally available, and the badges that can be won by earning points

Figure 5.21. MyTown iPhone application screenshots showing the Quiznos location, its location statistics, and user rewards available for checking in at a venue

Figure 5.22. Gowalla screenshots showing the user profile (with the number of check-in stamps and pins gained), an example of an item available at a location, and a list of trips available at certain locations

Figure 5.23. Wikitude was one of the early pioneers in the AR space and launched its AR browser for Android devices in mid-2009 (shown in a real-use scenario). The browser lays Wikipedia and other user-generated content over the camera view of the phone. (Source: mng.bz/qKp5)

Figure 5.24. Screenshot of Layar’s application for Android that allows users to combine a video camera view of the world with useful information shown as a digital layer on top of the screen view

Figure 5.25. A second screenshot of Layar’s Android application, showing Wikipedia information overlaid on the video camera’s image of downtown New York

Figure 5.26. Acrossair’s subway finder AR application released in summer 2009 for the iPhone 3GS, one of the first AR apps made available on the iPhone platform

Chapter 6. Mobile platforms

Figure 6.1. Major new mobile platforms: iPhone, Android, HP webOS, BlackBerry Storm, and the iPad, which are disrupting the old mobile ecosystem

Figure 6.2. The Java ME platform is a subset of the whole Java platform, targeted for mobile devices. (Source: mng.bz/8aLR)

Figure 6.3. Symbian as part of the Nokia S60 platform architecture (source: mng.bz/LSKH)

Figure 6.4. Nokia Ovi Store

Figure 6.5. iOS technology layers (source: mng.bz/d3j3)

Figure 6.6. Cocoa Touch in the architecture of the iOS (source: mng.bz/ZGY5)

Figure 6.7. aApple App Store

Figure 6.8. Major components of the Android operating system

Figure 6.9. Android Market

Figure 6.10. WebOS architecture (source: mng.bz/E16W)

Figure 6.11. HP App Catalog

Figure 6.12. BlackBerry architecture (source: mng.bz/1hue)

Figure 6.13. BlackBerry App World

Figure 6.14. Windows Marketplace for Mobile

Figure 6.15. LiMo architecture (source: mng.bz/t946)

Figure 6.16. Moblin architecture (source: mng.bz/XRT6)

Figure 6.17. BREW architecture (source: mng.bz/S0aX)

Chapter 7. Connectivity issues

Figure 7.1. LBS app displaying the accuracy of the location fix to the user in real time

Figure 7.2. An iPhone LBS application asking for permission to access the user’s current location

Figure 7.3. Settings for updating the user’s location in the Centrl LBS application

Chapter 8. Server-side integration

Figure 8.1. Various different types of POIs seen in an LBS application

Figure 8.2. Results of a routing request displaying turn-by-turn directions

Figure 8.3. Applications and servers exchange data using REST. The application makes REST requests from the server, and the server sends the application REST responses and notifications (source: mng.bx/272K).

Figure 8.4. Common spatial data types

Figure 8.5. The basic operation of Memcached (source: mng.bz/001q)

Figure 8.6. MapServer client view

Figure 8.7. GeoMedia client view

Figure 8.8. Microsoft MapPoint client view

Chapter 9. Monetization of location-based services

Figure 9.1. Impact of introducing charging (on November 9) on the number of downloads of the Galaxy Impact iPhone application (source: see footnote 2)

Figure 9.2. Application value/market decision matrix showing alternative charging strategies according to the perceived value and potential market size of new applications

Figure 9.3. LinkedIn has developed a successful freemium model by offering three types of premium memberships at different rates, on top of its basic, free membership.

Figure 9.4. Farmville’s virtual world allows users to network with members of the community, create their own unique online identity, and personalize their virtual farm with farming implements available in the online store.

Figure 9.5. Mobile screenshots showing a typical Flirtomatic profile page and a range of actions and virtual gifts that can be purchased, ranging from a flirtogram to various accessories

Figure 9.6. Screenshots of the AP Mobile iPhone app using push notification. This is one of the new features that can be charged to the consumer within Apple’s micro-payments platform.

Figure 9.7. Apple’s Store Kit is the go-between from an iPhone application to the App Store, allowing users to purchase approved items by showing premium content available and authorizing individual micro-payments. (Source: mng.bz/qbJg)

Figure 9.8. Global LBS subscription revenues (USD millions) from 2008 (actual) to 2009–2013 (forecast)

Figure 9.9. Different elements of real estate property offering application developers the chance to monetize their application (in order from the left): an application download page, a sponsored splash screen, and a main application page containing an advertising banner

Figure 9.10. Example screenshots from Nokia’s Ovi Maps service, showing how location-based ads can be embedded within a local weather forecast. Clicking on the ad banner takes the user to details of a store and a map of its exact location.

Figure 9.11. Screenshot of Otetsudai Network’s innovative mobile solution. Otetsudai connects local labor requests (visible through colored icons on the map) with local labor supply by using GPS on mobile phones.

Figure 9.12. Sense Networks’ BlackBerry application showing heat maps based on where users of mobile social networks cluster together. This allows ads to be served to tribes of consumers based on their patterns of behavior.

Figure 9.13. Screenshots from Lonely Planet’s range of iPhone City Guide applications, which currently are available in 20 different versions for cities around the world

Chapter 10. The privacy debate

Figure 10.1. The four pillars of privacy concerns (adapted from the CFIP Instrument by Smith et al.), which include data collection, data usage, data accuracy, and data access, summarize the current fears surrounding privacy within the general public.

Figure 10.2. Probability - Impact Matrix of Privacy Incidents shows the likelihood of different privacy breaches occurring and the negative consequences (from minor to serious impacts, such as identity theft). (Source: David Riphagen; reproduced with permission)

Figure 10.3. Screenshot of Google Street View (part of Google Maps) shows snapshots of street scenes in several countries across the world (from Japan, the United States, and Europe) but the service stirred controversy for infringing personal privacy because real people were depicted at specific locations.

Figure 10.4. iPhone screenshots of the Starbucks and AccuWeather applications’ opt-in screens

Figure 10.5. Screenshots from the Dopplr iPhone application, showing how users can opt in to use their current location to view local services or people but opt out from granting access to their private location data or footprint for use within anonymized statistics

Chapter 11. Distributing your application

Figure 11.1. Decision tree modeler for selecting the ideal distribution platform based on the four key app criteria (price, geographical target market, desired time-to-market, and platform)

Figure 11.2. GetJar is the leading independent, global app store with over 50,000 applications available for all mobile OSs (except LiMo) but currently offers only free apps.

Figure 11.3. BlackBerry’s App World has more than 3,000 applications and is available in more than 20 countries worldwide, with only 20% commission on app sales retained by the manufacturer.

Figure 11.4. Mobile operator stores, such as Vodafone’s Betavine and O2’s Litmus, have been mainly experimental and point toward future mass-market app store rollouts, such as Telefonica’s mstore.

Figure 11.5. The Android Market OS store offers a relatively small but rapidly growing app base of 20,000 and includes trial periods for testing new apps.

Figure 11.6. Positioning of key app stores illustrating the dominance by single-platform global stores (iTunes above all) and multiple-platform global stores (typically independent). The size of each circle is representative of the number of applications available in the store (350,000+ in the case of iTunes).

Figure 11.7. Apple’s iPhone Developer Program offers a wide range of developer tools, including Xcode and Apple Instruments, with step-by-step guidance on Apple’s application development best practice.

Figure 11.8. Within Xcode, you’ll need to start creating your project build by choosing a project name for your development project.

Figure 11.9. Once you’ve named your development project, you’ll need to select the target before selecting the base SDK for your application.

Figure 11.10. You can select an active configuration for your application by accessing the Debug workspace and selecting Distribution as the Active Configuration.

Figure 11.11. Selecting Add New Application from the main menu within the iTunes developer area takes you to a series of screens with mandatory input of information for your application, including a full description and the app categories it fits into.

Figure 11.12. Once you’ve created the name and a description of your application within the iTunes developer area, you’ll be requested to add your application, a logo, and up to five screenshots.

Figure 11.13. App Gems screenshot from the iPhone application that allows users to monitor global rankings of other iPhone applications

Figure 11.14. TripIt for iPhone charting of its app store rank and the number of downloads of the application, showing the strong correlation between these two variables. The lower line shows the iTunes App Store rank of the TripIt iPhone application for a three-month period from November 1 through January 31. The upper line shows the number of downloads of the TripIt iPhone application over the same period. As rankings drop, such as on the week of November 22, so does the number of app downloads. As rankings increase, such as on the week of January 17, so does the number of app downloads.Developer Secrets: Increasing App Store Sales; San Francisco, February 8, 2010 presentation, Will Aldrich, TripIt, mng.bz/q144

Figure 11.15. Effect of a short mobile advertising burst on the rankings for the Mixology iPhone app, showing a sharp spike in rankings within two days of launching the campaign (source: AdMob)

Figure 11.16. Flurry Media offers a dashboard-style free analytics tool, allowing developers to track users’ sessions and the duration of these sessions to assess how successful the app is in achieving its targets.

Figure 11.17. Yappler is one of several app social recommendation sites allowing users to recommend their favorite apps to their friends, as well as check out some useful aggregate statistics on app prices over time.

Figure 11.18. Flixster developed an effective partnership with Rotten Tomatoes that gave its iPhone app extra exposure for a fraction of the cost of an advertising campaign.

Chapter 12. Securing your business idea

Figure 12.1. Strategic choices available to a start-up include product leadership, operational excellence, and customer intimacy, and derive from the core values of the company.Source: White paper by Mark A. Zawacki, “Startup Candy Vol. 1,” The Milestone Group, November 2009.

Figure 12.2. Ecorio launched its green Android LBS application in August 2008 and established an early product leadership after receiving the Android Developer Challenge prize. The application helps users reduce their CO2 emissions.

Figure 12.3. Zappos is a well-known example of a company that started out with a clear “Customer is king” strategy, aiming to wow its online clients.

Figure 12.4. A company will need different amounts and types of funding according to which one of the five stages of development it’s in: concept, seed, start-up, growing, or mature.

Figure 12.5. Map of venture capital investments made in the United States ($ billions, by state) between 1970 and 2008, showing a heavy concentration in California’s Silicon Valley that dwarfs that of second-place New EnglandSource: mng.bz/bn45.

Figure 12.6. How the venture capital model works: Entrepreneurs need money to build their businesses. Institutional investors want high returns. Investment bankers need companies to sell to public markets. Venture capitalists make the market for the other three.

Figure 12.7. One of the schematics from Apple’s patent for the iGroups software in March 2010. iGroups uses the iPhone’s positioning technology to broadcast and receive position tokens, which are timestamped and so create “clumps” of people who share a location at a given time.