Housemachine

Revision as of 20:53, 19 January 2016 by Rtwomey (talk | contribs) (Video playback service on raspbian jessie)

Revision as of 20:53, 19 January 2016 by Rtwomey (talk | contribs) (Video playback service on raspbian jessie)

Work page for dissertation project

Contents

Overview

The dissertation, A Machine for Living In stages intelligent systems in domestic space to study the home as a site of intimate life. Designed to be inhabited, this project examines how technologies are altered through inhabitation. Upending the typical utilitarian concerns of the smart home with optimization and efficiency, I focus instead on the home as a nexus of personal history, desires, relationships, episodic narrative, and bodily praxis. I deploy technologies that purport to represent and analyze the self--speech recognition and synthesis, motion capture, and facial recognition, for example--and engage them with the messy conditions of domestic life. Living within the machine for a number of weeks, I produce a durable record of the home and its inhabitants: human, animal, machine. This material is restaged for viewers as a hybrid experience of recorded media and live interaction.

Process

  1. design/build
  2. inhabit
  3. summarize

To Do

  • indoor positioning system
    • people / inhabitant tracking
  • sensing doors / appliances / objects / actions
  • event logging
  • audio recording system
  • audio plan
  • video plan
  • robot / mechatronc plan
  • tracking plan
  • event logging (house data recorder)

Components

Black Box Recorder

  • airplane / vessel / ship analogy
  • telemetry
  • Flight Data Recorder (FDR)
  • Cockpit Voice Recorder (CVR)

Voice Assistant

  • voice operation
  • always listening in the different rooms

conventional

agonist / antagonist

  • lightswitch robots
  • door locks
  • other ways to provide / deny access

gleeker

lipstick robot

head stain wiper

garbage sensor

Technology

Spark Core with OSC

Audio

2009_locusschema.png

http://locusonus.org/w/?page=Locustream+LocusMic


Test throughput raspberry pi (mic to headphone):

arecord -f DAT | aplay -f DAT

Record and playback on Raspberry Pi:

arecord -f DAT -D plughw:0 | aplay -f DAT -D plughw:1
  • mics in each room

Preamp to Line Level

Electret_Preamp_TL071

picam

https://github.com/iizukanao/picam

Start picam

picam -w 1296 -h 972 --alsadev hw:1,0
touch hooks/start_record
touch hooks/stop_record

time lapse from FLIR

ffmpeg -framerate 5 -f image2 -i %04d.jpg -c:v libx264 -r 30 -pix_fmt yuv420p time-lapse.mp4

Video playback service on raspbian jessie

  • Create a service file in
/etc/systemd/system
  • flir.service:
[Unit]
Description=Plays FLIR footage on loop
After=syslog.target network.target

[Service]
Type=forking
ExecStart=/usr/bin/screen -dmS video omxplayer -b --loop --win 0,0,1280,1024 /home/pi/housemachine/data/flir/bed4.mp4

[Install]
WantedBy=multi-user.target
  • enable:
sudo systemctl enable flir.service
  • start:
sudo systemctl start flir.service
  • connect:
sudo screen -r video