Personal Comfort Monitor
This is a project focuses on the area of Smart Cities and in this case in particular looking at London Underground journeys and avoiding congestion and uncomfortable travel.
We use the Intel Edison together with the Grove Sensors to capture
- noise level
- air quality (simulated using a rotary sensor as we don't have a gas / dust sensor available)
and then calculate onboard a "comfort level" value using a weighted average of the sensor data between each pair of stations during the journey.
This value is then notified locally to the user via a smartphone app or optional rgb display (which also warns when the air quality deteriorates beyond a set level).
In addition to this, the data from each individual user is crowdsourced using the free wifi within each station to form an aggregated analytics platform for use by other commuters and Transport for London as a valuable data resource for planning purposes. The BSSID of the wifi access points is used for identifying which pair of stations each journey relates to (including direction of travel) as there is no GPS available underground.
For deployment, this would be a wearable sensor which communicates using BLE to a user's smartphone (to conserve battery power - energy harvesting from motion would also be a viable option to add) which then relays the data via the wifi network. We envision this being