So, my Smart Poi are battery powered, of course. I chose AAA NIMH batteries in a pack of 4 for this originally as this provides around 5 volts of power for the LED strip, and I have a voltage regulator to turn that into 3.3 volts for the ESP8266. Originally I got the batteries with tags on and had them soldered together into a battery pack (by a pro) and added a jack input for the charger. Nothing lasts forever, and after almost two years of use I find my battery packs are degraded to the point that they don’t power the poi anymore.
The simple solution would be to get some more packs made and simply replace the old ones, however I have found myself in situations where the one hour (big poi) or two hours (small poi) is simply not enough time. While they are charging the poi are not earning me money, so the plan now is to take the same batteries and make them replaceable. I found a cheap spring loaded plastic battery holder which fits inside the poi housing, so a simple jtag connector (molex whatever you want to call it, I am getting the cheapest one) will give me hours more poi spinning time, which means more money of course!
In addition, I am going to be adding a tilt switch to the LED strip power line, so while the poi are held upside down the strip will be off, but the controller will still be on, and connected to the Android app. This will save power significantly during down time (walking from one area to another for example).
Simple improvements, but with a major impact on my performance.
Now to get onto improving the code I promised to release as open source! A hard task but it’s coming.
So I have been working on the vervet monkey detector idea for a little while now. So far I have had some success with the back end. Here is an update on how it works so far. (tldr I used Google Cloud Vision api and some bash scripts)
1. I take a photo of the monkey (I still need to automate this, with motion detection)
2. Upload to my server using scp
3. Some moving around on the server to make the image public for Google Cloud Vision to see it – using inotifywait and mv
4. Google cloud vision api call with image url using curl
5. To do: parse json response from google to check if a monkey is actually there.
6. Send a signal to wireless valve (switches on the sprinkler and hopefully gives the monkeys a fright) – I have built one already, just need to modify the code slightly for wireless. Thinking of using esp8266 for this, since I have so many lying around, and a 12v battery since the tap valve solenoid runs off of 12v. I have a nice circuit board I built for my wireless poi which incorporates an ESP-01 and a voltage regulator. Add in a relay to switch 12v and it’s done.
So there is much to do. There is also the question of accuracy, obviously I don’t want any false positives wetting any unwary visitors, so I need to test this a lot before using it. The first version will trigger an alarm only, which in itself could be useful as a phone app, for example. We might be able to leave the windows open on occasion, with a monkey detector to alert us when one tries to get in and steal our food (this happened twice in the last week)
At some point I will have to make my own machine learning classifier for monkey images, as Google charges $1.50 currently per 1000 images classified. The first 1000 are free, but they have a habit of changing the pricing on their products without notice.