During the Emerge Americas 2018 Hackathon I made an augmented reality application that worked as an Anemometer by pointing the camera to the storm the app was able to compute the wind speed.

1. We have survived many Hurricanes in Miami and Sfla in
Genera. Irma, Wilma, Andrew, who knows how many
more.
The storm chaser with the barometer are widely known
icons in Hurricane Season
ANEMOMETER
Augmented Reality
AR
Dr. Edwin A. Hernandez
EGLA COMMUNICATIONS
@edwinhm @eglacomm

3. ANEMOMETERAR
Dr. Edwin A. Hernandez
EGLA COMMUNICATIONS
@edwinhm @eglacomm
Augmented Reality
Mechanical Sound/Ultra Sound
Main Methods to measure wind speed
3
Old Ways – Require centralized validation
In S. Fla we need to make decisions quick

4. ANEMOMETERAR
Dr. Edwin A. Hernandez
EGLA COMMUNICATIONS
@edwinhm @eglacomm
Augmented Reality
My Approach
Using Machine Learning, Compute Speed and Storm Level using
a Mobile Phone (iPhone or Android with ARKIt)

5. How does it work
iPhone sends video + audio feeds
to server via ARKit and
SceneKit.Snapshot API
Server for Visual
and Audio
Analysis
OpenCV2
AI/Neural Net
Have learned
from Audio +
Video
JSON with Speed/Wind/Accuray
Audio
+
Video
ANEMOMETERAR Augmented Reality Upload a file

6. Deep Learning Training
Youtube and people using Anemometers,
Howl sound of 100’s or 1000’s of videos from
IKE, Irma, etc
Nnetwork
LaRosa
OpenCV +
Neural Nets
Speed/Wind/Accuray
Audio
+
Video
ANEMOMETERAR Augmented Reality

8. ANEMOMETERAR Augmented Reality
OpenCV – Video How it works
• HSV – Hue Saturation, and Value
• Difference per frames after Gaussian Blur filter
• Number of contours detected is learned as a function of
Wind speed
• Multiple videos.
Audio – How it works
• Pattern of Audio as a function of speed
• Both together generate a fingerprint to an anemometer
reading
(_, cnts, _) = cv2.findContours(thresh.copy(),
cv2.RETR_EXTERNAL,
cv2.CHAIN_APPROX_SIMPLE)
# loop over the contours
for c in cnts:
# if the contour is too small, ignore it
if cv2.contourArea(c) <
args["min_area"]:
continue
# compute the bounding box for the
contour, draw it on the frame,
# and update the text
(x, y, w, h) = cv2.boundingRect(c)

9. ANEMOMETERAR Augmented Reality
Math/Mapping
• Less 0.8 less than 30 MPH
• 0.8-1.0 30 – 40 MPH
• 1 – 2 60 – 80 MPH
• 2.1 – 3.5 90 – 120 MPH
• Over 3.5/4.0 – Over 140 MPH
Audio – How it works
• Fingerprinting, high frequency over 1200Hz, higher speed
• Lower frequency, needs to be fingerprinted
Filtering
• May need a L1 or L2 Filter coefficient,
• Linear alpha*Current + (1-alpha)*Previous
Technologies
• AR Kit – IOS / AVPlayer
• OpenCV - Computer Vision
• LibRosa – Audio Encoding
• Machine Learning / Deep Learning
• Python/Flask/JSON
• Signal Processing Math