The smartphone as a platform for wearable cameras in health research.

BACKGROUND: The Microsoft SenseCam, a small camera that is worn on the chest via a lanyard, increasingly is being deployed in health research. However, the SenseCam and other wearable cameras are not yet in widespread use because of a variety of factors. It is proposed that the ubiquitous smartphones can provide a more accessible alternative to SenseCam and similar devices. PURPOSE: To perform an initial evaluation of the potential of smartphones to become an alternative to a wearable camera such as the SenseCam. METHODS: In 2012, adults were supplied with a smartphone, which they wore on a lanyard, that ran life-logging software. Participants wore the smartphone for up to 1 day and the resulting life-log data were both manually annotated and automatically analyzed for the presence of visual concepts. The results were compared to prior work using the SenseCam. RESULTS: In total, 166,000 smartphone photos were gathered from 47 individuals, along with associated sensor readings. The average time spent wearing the device across all users was 5 hours 39 minutes (SD=4 hours 11 minutes). A subset of 36,698 photos was selected for manual annotation by five researchers. Software analysis of these photos supports the automatic identification of activities to a similar level of accuracy as for SenseCam images in a previous study. CONCLUSIONS: Many aspects of the functionality of a SenseCam largely can be replicated, and in some cases enhanced, by the ubiquitous smartphone platform. This makes smartphones good candidates for a new generation of wearable sensing devices in health research, because of their widespread use across many populations. It is envisioned that smartphones will provide a compelling alternative to the dedicated SenseCam hardware for a number of users and application areas. This will be achieved by integrating new types of sensor data, leveraging the smartphone's real-time connectivity and rich user interface, and providing support for a range of relatively sophisticated applications.

Remote real-time monitoring of subsurface landfill gas migration.

The cost of monitoring greenhouse gas emissions from landfill sites is of major concern for regulatory authorities. The current monitoring procedure is recognised as labour intensive, requiring agency inspectors to physically travel to perimeter borehole wells in rough terrain and manually measure gas concentration levels with expensive hand-held instrumentation. In this article we present a cost-effective and efficient system for remotely monitoring landfill subsurface migration of methane and carbon dioxide concentration levels. Based purely on an autonomous sensing architecture, the proposed sensing platform was capable of performing complex analytical measurements in situ and successfully communicating the data remotely to a cloud database. A web tool was developed to present the sensed data to relevant stakeholders. We report our experiences in deploying such an approach in the field over a period of approximately 16 months.