I wanted a hard copy of an eBook I had that is out of print. There are many resources out there for binding books. Many recommend using acid free PVA glue. I can’t speak to how it compares to other glues, but “Aleene’s Tacky Glue” is a PVA glue, available acid free, which was available at craft stores in my area. This post will focus on prepping an eBook for print.

I wanted to build my own vision model for a few reasons: I wanted to learn how In my limited experience with OpenALPR, it looked like it was missing some license plates that seemed fairly readable to my eyes - could I possibly do better training my own model? Just the way it is built, I know I wouldn’t be able to get OpenALPR to run faster on my Pi - I wouldn’t be able to get it to run faster by off loading image processing to a VPU like the Myriad X in my Oak D camera.

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.

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.

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. Inexpensive CO2eq Sensor on Prototype Board in Elevator A CO2 measurement greater than atmospheric levels (400 ppm) is a sign of air that has recently been exhaled.