One of the features I have in mind for my bicycle dashcam was license plate recognition. In parts 1, 2 and 3, I experimented with the OpenALPR license plate recognition library and a couple different Pi cameras. I encountered a few challenges:

• Image quality challenges: out-of-focus images, warped images due to the “rolling shutter” of the Pi camera
• Field of view: capturing more than just the license plate
• Speed: Only able to process 1 image every 8 seconds on my Pi 3

I acquired the Luxonis Oak-D AI accelerated camera to experiment with different image sensors which could potentially address my image quality challenges, stereo vision/depth sensing provided interesting capabilities, and the AI acceleration to increase the speed. This spring, I mounted it to my bike and started capturing images on my rides.

Ever since the Espressif’s ESP8266 wi-fi capable microcontroller was launched, I’ve been thinking about all the possibilities for low cost network connected devices. And, nothing world changing, but I have used it to build a data logging CO2 monitor and a device to control my old TV with Alexa.

I have been thinking of NEW possibilities as I see development boards with the ESP8266’s successor, the ESP32, with a small screen, for less than $20CAD shipped from Aliexpress. What can I build with a really tiny internet connected dashboard? So I ordered a Lilygo TTGO.

I continue to experiment with how a dashcam can assist urban cyclists. This time, I’ve started a fresh design with a different idea, a new camera, new models, and new code, which I’m submitting as an entry for the Toronto ♥️’s Bikes Make-a-Thon.

I enjoy biking from my home in North York, near Mel Lastman Square, to my office near Union Station during the week. The most harrowing part of this ride is the Yonge-401 interchange, which requires two lane changes with fast moving traffic from the 401 on and off ramp.

By Richard Audette, richard@hotelexistence.ca

Introduction

I first heard about measuring CO2 as a risk proxy for Covid-19 from a Radiolab podcast. Covid-19 can be transmitted through respiratory droplets produced during exhalation. CO2 is also exhaled. We can’t easily measure Covid-19 droplets in the air, but we can inexpensively measure CO2.

A CO2 measurement greater than atmospheric levels (400 ppm) is a sign of air that has recently been exhaled. If a person were infected with Covid-19, aerosols containing Covid-19 could be lingering in the air. Proper ventilation decreases the concentration of aerosols that may be suspended in the air, as well as the concentration of CO2. As such, measuring CO2 is potentially a useful proxy indicator for airborne infection risk. A “HIGH” CO2 reading doesn’t mean there are Covid-19 aerosols, but a “LOW” reading suggests a low probability of infectious aerosols.

By Richard Audette, richard@hotelexistence.ca

Introduction

I have created a Voice Assistant File Transfer Protocol for Alexa-powered voice assistants, like the Amazon Echo. The protocol uses verbal encoding to transfer the file through Alexa - it is not the control an external file transfer application. I have developed a proof of concept, which includes a client application, a server application, and an Alexa Skill. The client encodes a binary file as English words, launches an Alexa Skill and verbally sends the data through the PC’s speakers to an Amazon Echo device. The server decodes the words, saves the binary file, and makes it available on the Internet.

By Richard Audette, richard@hotelexistence.ca

Introduction

Credential stuffing is a type of cyberattack where stolen account credentials typically consisting of lists of usernames and/or email addresses and the corresponding passwords (often from a data breach) are used to gain unauthorized access to user accounts through large-scale automated login requests directed against a web application.
from: https://en.wikipedia.org/wiki/Credential_stuffing

These attacks are pretty common. In August, the Canada Revenue Agency was the subject of an attack. Approximately 5500 taxpayers were impacted, including one of my friends: