{"id":3987,"date":"2015-01-02T21:53:31","date_gmt":"2015-01-02T21:53:31","guid":{"rendered":"http:\/\/www.haydnwilliams.com\/blog\/?p=3987"},"modified":"2022-04-11T21:32:28","modified_gmt":"2022-04-11T20:32:28","slug":"airpi-a-tentative-v1-0-release","status":"publish","type":"post","link":"https:\/\/www.haydnwilliams.com\/blog\/airpi-a-tentative-v1-0-release\/","title":{"rendered":"AirPi – a tentative v1.0 release"},"content":{"rendered":"

Earlier this year I forked the software used to control the AirPi<\/a>, a small board which fits a Raspberry Pi<\/a> to monitor environmental phenomena such as temperature, humidity and air pressure along with air quality measures including Carbon Monoxide, Nitrogen Dioxide and VOC<\/abbr>s. Having made quite a lot of changes, I’ve just tagged a v1.0 release<\/a> on GitHub<\/a>, so thought it might be prudent to take a look at what’s been added and\/or amended.<\/p>\n

\"The

The pride of the fleet – Model B+, and the AirPi has the GPS chip. #bling.<\/p><\/div>\n

The original software<\/a> was released by one of the projects instigators, Tom Hartley<\/a>. This was forked by Fred Sonnenwald<\/a>\u00a0as part of the pi.gate.ac.uk<\/a> project – he\u00a0added a number of useful features, not least of\u00a0which\u00a0was the web server to display figures and pretty charts.\u00a0I forked from his work<\/a> because I needed to make a couple of tweaks, but they turned into a fairly major update.<\/p>\n

\"AirPi

AirPi software – original release (left) vs. my v1.0 release (right).<\/p><\/div>\n

The original release of the software would read from sensors and either print the results to screen or send to a Xively<\/a> feed. At the end of 2013 the code was updated\u00a0so that sensors and outputs became modular. Fred Sonnenwald’s update added support for a number of new sensors (including the TGS2600 air quality sensor), output to CSV files,\u00a0the aforementioned HTTP output, and the ability to dial in calibration functions for individual sensors. The latter is particularly important, as the cheap nature of the sensors used by the AirPi mean there is great variability between individual instances of the same model even from the same production run. Fred did a great post<\/a> giving an initial look at interpreting readings from the AirPi.<\/p>\n

I stood on Tom and Fred’s shoulders, and added a number of other features, including:<\/p>\n