This document describes a proposed pedestrian safety system called SmartPath that uses Bluetooth beacons and a smartphone app to alert distracted pedestrians approaching intersections. The system was designed to address the growing problem of pedestrian deaths in the US. It involves placing Bluetooth beacons at intersections that can be detected by a smartphone app running in the background. When a pedestrian enters the beacon range near a crossing, the app provides an audible, visual or tactile alert. The document outlines the implementation of a prototype app that monitors, ranges and notifies users of nearby beacons. It discusses challenges, assumptions, and ideas for future improvements to functionality and accuracy. The goal is to develop a reliable system that alerts all pedestrians using their

1. SmartPath
A pedestrian safety system
December 5, 2017
By: Kamlakant Tripathi, Pratik Navale
Instructor: Dr. Shubham Jain
Old Dominion University

2. Problem
2
● Between 2005 and 2014, a total of 46,149 people
were struck and killed by cars while walking in the
United States.
(Source:https://smartgrowthamerica.org/dangerous-by-design/)
● Nationwide, 22 percent more pedestrians killed last
year than two years earlier, according to the
Governors Highway Safety Association.
(Source:https://www.deseretnews.com/article/865676927/Pedestrian-deaths-on-roads-
up-cellphones-partly-to-blame.html)

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8. Traffic lights can only do so much!!
Even if they are put on ground.
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9. Related work
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▪ LookUp!
The shoe sensors relay inertial sensor
measurements to a smartphone, which
extracts the step pattern and the inclination of
the ground a pedestrian is walking on.
Prototype:
1. Shoe-mounted sensor
2. Two android applications for data
collection with LookUp safety feature
LIMITATION:
GPS accuracy can quickly degrade to tens of
meters in urban canyons.
Not viable for every individual/expensive
setup.
▪ LookUp!
shoe mounted inertial sensor
for alerting pedestrians
(Source:
winlab.rutgers.edu/~shubhamj/papers/m
obi251f.pdf)
▪ Drowsy Detector
facial recognition technology to
detect whether drivers are getting
drowsy
(Source:
https://www.ncbi.nlm.nih.gov/pmc/articles/PM
C3571819/)
▪ Rider Alert
uses Bluetooth to alert drivers
with an audio / visual alert
(Source: http://rideralert.org/)

10. Idea
Alert distracted pedestrians on their phones
▪ Beacons at intersections
▪ Smartphone application
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Our solution

11. Beacons at intersections
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▪ Bluetooth Low Energy (BLE)
▪ Altbeacon, Eddystone, iBeacon
protocol / standard
▪ Placed at pedestrian signals
Beacon
Traffic Light
Bluetooth

12. Smartphone application
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▪ Runs in background
▪ Alerts user when in beacon
range

13. Methodology (Communication flow for a single cycle)
1310
Beacon
Is hazard
situation
created?
Walker’s
cellphone
No alert /
keep
monitoring
Preventive
action
Send data
Beacon’s
signal
Walker’s
smartphone
Post
Analysis
Alert &
visualization
Audible alert
/ vibration /
Text
Yes
No

14. Our implementation
▪ Basic Android app - functional
▪ Monitoring, ranging and alert notification
▪ Monitoring: monitors nearby beacons
▪ Ranging: logs distance, Tx, rssi, UUID/Major/Minor
▪ Notification: alerts pedestrians when they’re close to intersection
▪ Android beacon library by Altbeacon
https://altbeacon.github.io/android-beacon-library/
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15. Our implementation
▪ Monitoring - working
▪ Ranging - working
▪ Notification - working* (*better calibration needed)
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Log excerpt:
Logging information from nearby beacons:
distance, Tx, rssi, id
Alerts when
near a road

16. Evaluation
▪ Functionality over accuracy
▪ Number of positive detections over total trials
▪ Accuracy in mind
▪ Measured ‘distance’ values over time and compared to ground truth
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17. Field experiments
Data: Exported Logcat data from Android Studio
Data format: Text, converted to CSV
Data description: Timestamp, Distance, Tx, RSSI, UUID
Data collection: Real time, over various distances
Data collection frequency: Observations for 60 sec for each distance
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18. Evaluation
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Tx: -53 dBm
Mean RSSI : More deviation at longer distance.

19. Evaluation
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More variation as distance increases.
Acceptable for our application.

20. Challenges
▪ Walking speed of pedestrians
▪ High volume of pedestrians (peak time): signal reflection and obstruction
▪ Accuracy (App detecting beacon from a min. safe distance)
▪ Beacons usually used for locating objects
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21. Challenges
▪ Beacon placement:
▪ Avoid unnecessary detections
▪ Can change alert distance by
configuring beacon
▪ Alert distance,
x : Distance at which alert triggers;
y : Beacon range
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x
y

22. Challenges
▪ Beacon placement:
▪ Overhead, on the pole
▪ Works best when in line-of-sight
of mobile device
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23. Assumptions
▪ Pedestrian with mobile device, bluetooth and location enabled
▪ Average walking speed
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24. Tools
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RadBeacon Dot
by Radius Networks
Software
Android Studio (ver. 2.3.3)
Android Beacon Library (ver. 2.12.3
by AltBeacon/Radius Networks)
Deployed on
OnePlus 3 (A3003)
Android ver. 8.0 (Oreo)

25. Future work
▪ Improve functionality overall
▪ Incorporate direction to prevent false detections
▪ Develop pedestrian monitoring system - count, peak time, jaywalkers
▪ Work with better and stable BLE beacons
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26. Takeaway
▪ To develop a pedestrian safety system that always works, for all
pedestrians using smartphones.
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27. DEMO
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Thank you
Presented by:
K.K. Tripathi
Pratik Navale