What do you do when you want to add a new feature to some electronics but you can’t or don’t want to tear into the guts? You look for something external with which you can interface. We like these hacks because they take some thinking outside the box, literally and figuratively, and often involve an Aha! moment.
[Simon Aubury’s] big household load was electric heating and his ancient heaters didn’t provide any way to monitor their usage. His power meters weren’t smart meters and he didn’t want to open them up. But the power meters did have an external LED which blinked each time 1 Wh was consumed. Aha! He could monitor the blinks.
Doing so was simple enough. Just point photoresistors at the two meter’s LEDs and connect them and capacitors to a Raspberry Pi’s GPIO pins. Every time a pulse is detected, his Python code increments the LED’s counter and every fifteen minutes he writes the counters to an SQL database. Analysing his data he saw that nothing much happens before 5 AM and that the lowest daytime usage is around noon. The maximum recorded value was due to a heater accidentally being left on and the minimum is due to a mini holiday. Pretty good info given that all he had to go on was a blinking light.
Where else are there LED indicators which you can tap into? Here’s an only slightly more invasive usage where a washing machine’s “end of cycle” LED was removed and the power going to it was rerouted to an Arduino for remote monitoring.
[tomek] was aware of this hip knowledge domain called Digital Signal Processing but hadn’t done any of it themselves. Like many algorithmic problems the first step was to figure out the fastest way to bolt together a prototype to prove a given technique worked. We were as surprised as [tomek] by how simple this turned out to be. Fundamentally it required a single function – cross-correlation – to measure the similarity of two data samples (audio files in this case). And it turns out that 
At this point all that was left was packaging it all into a one click tool to listen to the radio without loading an entire analysis package. Conveniently Octave is open source software, so [tomek] was able to dig through its sources until they found the bones of the critical xcorr() function. [tomek] adapted their code to pour the audio into a circular buffer in order to use an existing Java FFT library, and the magic was done. Piping the stream out of ffmpeg and into the ad detector yielded events when the given ad jingle samples were detected.
