Location aware apps: patterns and solutions - Ben Butchart - Jisc Digital Festival 2014

Location Aware
Apps: Patterns &
Solutions
Ben Butchart
Team Leader: Software Engineering, EDINA
JiscDigifest2014:LocationAware
AppsDesignPatternsandSolutions

Ben Butchart b.butchart@ed.ac.uk
Users of smartphones, tablets,
and other devices expect position
with the highest level of accuracy,
always available, with the least
amount of power consumed.
GPS World
http://gpsworld.com/putting-the-ultra-low-power-in-geofence/
Location Awareness awareness

Pins on Maps
Characteristics:
• Periodic location update to
track user (blue dot).
• Pins /markers display Points
of Interest (POIs).
• Armchair accessible.
Examples:
• Google Maps, Apple Maps, Bing Maps
Power Management:
• Good. (foreground only).
http://datenform.de/map-kassel-1.jpg
Constraints:
• Foreground only
• User manually pans map.
• Network access
Options:
• Augmented Reality View
• 3d View
Related Patterns:
• POIs Near Me
• GPS

POIS Near Me
Characteristics:
• Periodic location update to
track user (blue dot).
• Pins /markers display Points
of Interest (POIs) in vicinity
Examples:
• Google Maps, Apple Maps,
Bing Maps
• AR: Wikitude, Layar, Junaio
Power Management:
• Good. (usually by
request, foreground
only).
Constraints:
• Foreground only.
• User requests POI update.
• Network Access
Options:
• Routing
• Augmented Reality View
• 3d View
Related Patterns:
• Pins On Maps

Geofence Notify
Characteristics:
• User proximity to POI triggers
a notification or other
background activity (audio)
• Can work in background
(with device in pocket)
• Always checking location.
Examples:
• Google Keep
• iReminders
• Family Locator
• IfThisThenThat
Power Management:
• Can be expensive
Constraints:
• Hard for developer to control
OS driven behaviour.
Options:
• Wakeful
• Start on boot
• widgets
Related Patterns:
• Geofence Soundscape
• Scavenger Hunt
• Activity Detection

Geofence Notification Anti-patterns
• Start activity directly (without notification)
• Geofence DIY
http://lists.w3.org/Archives/Public/public-sysapps/2013Apr/att-
0104/Geolocation_API_Modifications_for_Web_Applications_April_2013.pdf

Geofence Soundscape
Characteristics:
• Sounds/ acoustic /video tracks
provide ongoing immersive
background.
• Different sounds layered /
altered according to location.
• Location updates always on in
geofence.
• Media always playing (while in
geofence)
Examples:
• Inception The App
• Forgotten Futures
Power Management:
• Expensive (near geofence)
• Medium (away from geofence)
Constraints:
Options:
• Wakeful
• Start on boot
• Transition events only
• Activity detection
Related Patterns:
• Geofence Notify
• Activity Detection

Data capture / Geo-tagging
Characteristics:
• User can use device to
capture images, text, audio,
GPS tracks and other sensor
observations
• Captured assets are geo
referenced (e.g. have lon, lat,
altitude)
Examples:
• Fieldtrip GB
• iSpot
• LeafWatch
• Fulcrum
• Evernote
Power Management:
• Good (foreground only)
• Medium (GPS track capture)
Constraints:
• Sync’ing complex
• GPS not always accurate
enough.
Options:
• Sync to cloud to share.
• Create active geofences.
• Display on map.
Related Patterns:
• Pins on Maps
• POIs Near Me
• Geofence Notify
• Scavenger Hunt

Scavenger Hunt
Characteristics:
• One POI provides clue /
directions to discover next
POI.
• User collects POIs / assets to
gain points or arrive at final
destination to collect prize.
Examples:
• Ingres
Power Management:
• Medium (geofence modem)
• Low (geofence native)
Constraints:
• GPS
• game engine.
Options:
• Use geo-fences.
• Augmented Reality visualisation.
• Computer vision capture .
• Create clues/content for other users to
discover (geo/ computer -caching).
• Mix with real world clues / prizes (geo
caching)
• Display on map.
Related Patterns:
• Pins on Maps.
• POIs Near Me.
• Geofence Notify.
• Data capture.

Activity Detection
Characteristics:
• System detect user activity
modes such as walking, in
car, resting.
• Uses sensor fusion
(gyroscope, accelerometer)
as well as GPS / WIFI.
Examples:
• Where’s My Car
• Dude, Where’s My Car
Power Management:
• Good (built in sensor fusion)
• Low (developer implementation)
Constraints:
• Requires data connection
Options:
• Use with geo-fences.
• Use with data capture.
Related Patterns:
• Pins on Maps.
• POIs Near Me.
• Data Capture

Marauders Map
Characteristics:
• Event triggered by a virtual
character rather than device
location.
• Virtual character follows pre-
defined route
• Geo-fence triggered by user’s
proximity to virtual character
as user “follows/accompanies”
virtual character.
• http://dlib-brown.edina.ac.uk/openstacktestlink3.html
• Work in progress!
Power Management:
• Medium (geofence modem)
• Low (geofence native)
Options:
• Armchair mode.
Related Patterns:
• Pins on Maps.
• POIs Near Me.
• Data capture.

Bomb Sites
Project Zero: Disease Infection Modelling
Womens Walks
Spatial Memories
Example Location Aware Use Cases
Featured Concepts:
Other Suggested Concepts / Thoughts:
Campus tour
Library reminder
3D- Geology
Building Anatomy
Student Society / Club App

Possible exention to Jisc funded Bomb site project (
http://www.bombsight.org/) Disclaimer: this was idea I mooted about 2
years ago with project manager (Dr. Kate Jones) but not currently part of
project or planned as far as I know. So only using idea as an example for
design exercise.
Bomb Site – The night the bombs fell
We want to recreate some sense of the experience
of Londoners during a single night during the
London Blitz in 1941, using data from the National
Archives that details the location, type and time
that bombs fell during one of the heaviest nights of
bombing during the Blitz. User will step back in
time and be able to hear the Air Raid warnings at
same time people heard the 50 years ago, they will
hear bombs falling and explosions in the distance
or nearby and be able see where their nearest
shelter would have been as bombs start falling
closer to their location.

Patient Zero
Patient Zero project at Threshold Festival: http://sciencegrrl.co.uk/patient-zero-
project/
One of the oldest and most common techniques in disease ecology is
mathematical modelling. At its most basic level, it uses a set of equations
that predict how the numbers of people infected by a disease in a population
will change through time. The aim of the Patient Zero project is to explain
infectious disease modelling by simulating an epidemic with people attending
a local festival playing the part of the population experiencing the
infection.
We are Manda Minter, Beth Levick and Cassie Raby, and all three of us are
PhD students in the Department of Ecology, Evolution and Behaviour at the
University of Liverpool. We have developed the project together with the
Liverpool ScienceGrrl Chapter and the Forgotten Futures app.
We are each researching how disease moves through populations: leptospirosis
in urban slums in Brazil; wildlife plague in Kazahstan; and baboons in
Namibia. We are all interested in how we can describe the spread of disease
and try to make predictions about how it might move in the future.
(Use R programming language)

In a short project in partnership with the London School of Economics (LSE),
EDINA have produced a smartphone app for showcasing content from the LSE's
recently acquired Women's Library.
The Women's Library @ LSE collections document all aspects of women's lives,
with a particular emphasis on the lives of women in the UK and the great
political, economic and social changes of the past 150 years.
The print collections include over 60,000 books and pamphlets and 3,000
periodical titles. The archive and museum collections include over 500 archives
and 5,000 museum objects, including photographs, posters, badges, banners,
textiles and ceramics.
This short project concentrated on a sample of these resources, geolocating
them and providing a smartphone interface with which to interact and discover
key content – showcasing in particular content related to the suffragette
movement. Using a smartphone, users can undertake guided walks around a
number of London based walks and at key points discover more detail about
some of the LSE Womens Library Collection relevant to that specific location.
Womens Walks

Spatial Memories
An App enabling people with disabilities to become more
independent and less reliant on others in making spatially
aware reminders, hints and checklists using a personalised
interface. The goal of the project is to develop a proof of
concept smartphone App that will allow individual learners to
record oral instructions, make text and audio notes, capture
images, and associate these with locations, routes and
activities. The aim is to improve the user’s confidence in
different working and learning environments and assist them to
live more independently.
The project has been funded through the ‘Good to go’ strand of
the Small Business Research Initiative (SBRI) programme. ‘Good
to Go’ is about increasing independence in unfamiliar or
challenging environments by giving people easy access to the
information they need when they need it.

Location aware apps: patterns and solutions - Ben Butchart - Jisc Digital Festival 2014

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Location aware apps: patterns and solutions - Ben Butchart - Jisc Digital Festival 2014