The TECO Envboard: A mobile sensor platform for accurate urban sensing &amp;#x2014; And more

2012 Ninth International Conference on Networked Sensing (INSS)

Busse

Beigl

2012

Self Cite

Abstract-A variety of studies in the past decades have shown that fine particulate matter can be a serious health hazard, contributing to respiratory and cardiovascular disease. Due to this, more and more regulations defining certain permissible concentration limits have been set by governments around the world. However, current standard measurement equipment is large, expensive and sparsely deployed. Additionally, both the exposure to hazardous conditions and the susceptibility to negative health effects vary from person to person. As a result, we see the need for fine-grained, mobile and distributed measurements, e.g. to identify hot spots or monitor people at risk. Our research investigates the feasibility of particulate matter measurements using cheap, commodity dust sensors which are small enough to be incorporated into mobile devices. This paper first discusses application scenarios which would benefit from inexpensive methods to assess the particulate matter load. Subsequently, commercial-off-the-shelf (COTS) sensors are compared and their general suitability for the application scenarios is examined. Finally, an experimental setup for the evaluation of one of the sensors is presented along with preliminary results.

Section: Methodsmentioning

confidence: 99%

Investigating the use of commodity dust sensors for the embedded measurement of particulate matter

2012 Ninth International Conference on Networked Sensing (INSS)

Busse

Beigl

2012

Self Cite

“…We conducted experiments with a special platform [3,1] that incorporates the Sharp GP2Y1010 dust sensor. Its measurement principle is the same as that of most optical dust sensors: light is emitted into a measurement area.…”

Section: System Design and Experimentsmentioning

confidence: 99%

Retrofitting smartphones to be used as particulate matter dosimeters

Proceedings of the 2013 International Symposium on Wearable Computers

Barbera

Masri

et al. 2013

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This work discusses ways of measuring particulate matter with mobile devices. Solutions using a dedicated sensor device are presented along with a novel method of retrofitting a sensor to a camera phone without need for electrical modifications. Instead, the flash and camera of the phone are used as light source and receptor of an optical dust sensor respectively. Experiments to evaluate the accuracy are presented.

“…Example technology ranges from multi-sensor devices (e.g. CommonSense [8], Envboard [5]) over mobile phone accessories and body-worn sensors (e.g. Breathe [15]) to sensor-enabled clothing (e.g.…”

Section: Introductionmentioning

confidence: 99%

Robust in-situ data reconstruction from poisson noise for low-cost, mobile, non-expert environmental sensing

Proceedings of the 2015 ACM International Symposium on Wearable Computers - ISWC '15

Köpke

Beigl

2015

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Abstract-Personal and participatory environmental sensing, especially of air quality, is a topic of increasing importance. However, as the employed sensors are often cheap, they are prone to erroneous readings, e.g. due to sensor aging or low selectivity. Additionally, non-expert users make mistakes when handling equipment. We present an elegant approach that deals with such problems on the sensor level. Instead of characterizing systematic errors to remove them from the noisy signal, we reconstruct the true signal solely from its Poisson noise. Our approach can be applied to data from any phenomenon that can be modeled as particles and is robust against both offset and drift, as well to a certain extent against cross-sensitivity. We show its validity on two real-world datasets.