SMART CITIES FOR HEALTH PREVENTION

Nicola Bryant, Birmingham City Council & Phil Crooks, Etive Technologies

Softcom 17 IoT and Smart City Services to Support Independence and Wellbeing of Older People 22/09/2017

BIRMINGHAM

AIM OF SESSION: IoT and Smart City Services to support independence of older people

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Aim

◘ Context and background

◘ Role of IoT and smart city services - ambition for City4Age

◘ Overview of technical design and system architecture for Birmingham

◘ Technical challenges for data collection and detection

◘ Next steps

INTRODUCTION – The Challenge

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INTRODUCTION - Ambition for City4Age

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◘ Use and sharing of citizen data

◘ Interpretation of data (locality & contextual)

◘ Increase digital skills

◘ Accessibility, adoption and use of technology

◘ Stimulate private sector innovation

◘ Deliver new sustainable and cost-effectivce services for the future

New prevention services to promote healthy & active lives

INTRODUCTION - Pilot set-up for data collection and detection

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◘ 2 phased pilot studies in contrasting neighbourhoods of Birmingham

◘ User centric iterative design

◘ Focus on outdoor environment

◘ Detect changes in daily living patterns

◘ Data collected in unobtrusive way

• Locality ; Motility data

• Other supporting data

◘ User feedback & validation of technology and non-technical aspects

SYSTEM ARCHITECTURE: Overview

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SYSTEM ARCHITECTURE: Digital Log Book

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SYSTEM ARCHITECTURE: Estimote Proximity Beacons

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◘ Designed to attach to fixed points (walls, tables, shelves) to provide apps with location context.

◘ Bluetooth® SoC

◘ ARM® Cortex®-M4 32-bit, 64 MHz

◘ Bluetooth® 4.2 LE standard

◘ iBeacon and Eddystone protocols

◘ Power: -20 to +4 dBm in 4 dB steps

◘ Range: up to 70 meters

◘ 1 x CR2477, 3.0V Lithium cell

◘ Over three years of battery life on default settings (advertising every 300ms at -12dBm).

SYSTEM ARCHITECTURE: Deployed Beacons

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Ley Hill Surgery, Sutton Coldfield, Birmingham

◘ Beacon Instance: c4a000002760

◘ Advertising interval: 300ms

◘ Transmit Power: -20dBm (range of approx. 3.5m)

SYSTEM ARCHITECTURE: City4Age Birmingham Locator App

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◘ Very simple – smarts in Local Repository

◘ Runs on Android and iPhone (etc.)

• Cordova/Evothings JavaScript App

• Runs in the WebView

◘ Uses battery saving geolocation to decide when to scan for Eddystone Beacons

• Scanning paused when Beacons out of range or device stationary

◘ User registers using email address

◘ App sends:

• Hourly heartbeat

• Beacon Found and Lost events

◘ Usually runs in background without a UI

SYSTEM ARCHITECTURE: Nokia/Withings Watches

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Data collected via the Healthmate app and collected on the Nokia server

◘ Activity

• Steps and distance

• Calories

• Rate of Activity Soft, Moderate or Intense

◘ Sleep

• Time to fall asleep

• Time asleep Deep or light sleep

• Times woken

• Time awake in bed

SYSTEM ARCHITECTURE: Local Repository (1)

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◘ Grails 3 server (Groovy, Java, Spring, Hibernate)

◘ No User Interface needed

◘ Receives heartbeat messages from phones

◘ Receives Beacon Proximity events (Found and Lost events) from phones

◘ Holds information about

• Care Receivers

• Points of Interest and

• Beacon locations

◘ Runs nightly jobs:

• Translate the previous day’s Proximity events into POI events

• Fetch the previous day’s Activity and Sleep data from the Nokia server

• Upload POI events and Activity/Sleep data to the Central Repository

SYSTEM ARCHITECTURE: Local Repository (2)

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TECHNICAL CHALLENGES: Detecting Beacons Reliably

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◘ Beacon range set to 3.5m to increase accuracy of location

• Coverage 7m diameter

◘ Assume fast walking Care Receiver covers 4.5km/h or 1.25m/s

• Walk across the diameter in 5.6 seconds

• 9 km/h is fast ”power walking” and would need only 2.8 seconds

• Detection in 1.4 seconds should never miss an important beacon

◘ Beacon advertising

• Every 700ms to guarantee one advert in 1.4 seconds

• Default is every 300ms or four adverts in 1.4 seconds – use this

◘ Beacon detection

• Only detect strong signals: -90dB

• Beacon “found” if still detected 1.4 seconds after first detection

• Take 6x longer (8.4 seconds) to lose a ”found” beacon (trial and error)

TECHNICAL CHALLENGES: Battery Life

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◘ Bluetooth scanning is power hungry

• 13mA (approx) per scan

• Need to scan constantly when near beacons

◘ Use location to turn on scanning when needed

• GPS is power hungry

• “Battery Saving” mode is not

◘ City4Age needs Lat & Lng for POI location

• Turn on BT scanning when close by

• Can create multi-location “regions”

◘ Turn off BT scanning when phone is stationary

◘ Efficiency could be improved further

• Native App

• Optimise use of location and Bluetooth

TECHNICAL CHALLENGES: Creating POI Events

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◘ Beacon Proximity Event List is organised into Beacon Event Pairs (BEPs)

• A BEP is a Found event and its corresponding Lost event

• A Lost event followed quickly by a Found event is a Drop-out Drop-outs are ignored

• BEPs are categorised as Walk-by (events <= 60 seconds apart) or

Visit (events > 60 seconds apart)

◘ The BEP list is reversed making the first BEP a POI exit

• A working assumption, the Care Receiver may have walked past

◘ POI exit events (BEPs) are “stacked” to allow POI Locations to be nested

◘ Iterate through the list looking for adjacent BEPs from same location

• If BEP has same location as a stacked exit event generate POI events

• If not, empty stack and add the new BEP

• Visit BEPs can generate POI entry and exit if no other match

TECHNICAL CHALLENGES: iPhones

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◘ The Birmingham City4Age App runs on iOS

• But only in the foreground!

• Unfortunately the App runs 24x7 and mostly in the background

◘ iOS limits use of system resources in the background to conserve power

• Many common, core Bluetooth tasks are disabled

• App may be terminated to free up resources

◘ Core Bluetooth Background Execution Mode

• Bluetooth-central mode allows device discovery but…

• Can only discover a device once (no way to detect entry and exit)

• The scanning interval increases so will not detect all Beacons

◘ Geolocation has similar limitations

◘ Great battery life but Apple’s rules are too restrictive for research

• Need to be able to take control to explore possibilities

NEXT STEPS

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◘ User testing and validation

◘ Learning and iterative design to inform development of 2nd pilot study starting October 2017

◘ Implementation of the intervention phase

◘ Refinement and resolution of manageable data detection apsects

◘ Addressing limitations in device capabilities

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