Editing Wireless sensor network (section)

====Air quality monitoring====
Experiments have shown that personal exposure to [[air pollution]] in cities can vary a lot.<ref>{{cite journal |last1=Apte |first1=J.S. |last2=Messier |first2=K.P. |last3=Gani |first3=S. |last4=Brauer |first4=M. |last5=Kirchstetter |first5=T.W. |last6=Lunden |first6=M.M. |last7=Marshall |first7=J.D. |last8=Portier |first8=C.J. |last9=Vermeulen |first9=R.C.H. |last10=Hamburg |first10=S.P. |date=2017 |title=High-Resolution Air Pollution Mapping with Google Street View Cars: Exploiting Big Data |journal=Environmental Science and Technology |volume=51 |issue=12 |pages=6999–7008 |doi=10.1021/acs.est.7b00891|pmid=28578585 |bibcode=2017EnST...51.6999A |doi-access=free }}</ref> Therefore, it is of interest to have higher temporal and spatial resolution of [[pollutants]] and [[particulates]]. For research purposes, wireless sensor networks have been deployed to monitor the concentration of [[air pollution|dangerous gases for citizens]] (e.g., in [[London]]).<ref>{{cite web |url=https://www.breathelondon.org/ |title=Breathe London |author=<!--Not stated--> |website=Breathe London |access-date=27 April 2021}}</ref> However, sensors for gases and particulate matter suffer from high unit-to-unit variability, cross-sensitivities, and (concept) drift.<ref>{{cite journal |last1=Feinberg |first1=S. |last2=Williams |first2=R. |last3=Hagler |first3=G.S.W. |last4=Rickard |first4=J. |last5=Garver |first5=D. |last6=Harshfield |first6=G. |last7=Stauffer |first7=P. |last8=Mattson |first8=E. |last9=Judge |first9=R. |last10=Garvey |first10=S. |date=2018 |title=Long-term evaluation of air sensor technology under ambient conditions in Denver, Colorado |journal=Atmospheric Measurement Techniques |volume=11 |issue=8 |pages=4605–4615 |doi=10.5194/amt-11-4605-2018|pmid=31595175 |pmc=6781239 |bibcode=2018AMT....11.4605F |doi-access=free }}</ref> Moreover, the quality of data is currently insufficient for trustworthy decision-making, as field calibration leads to unreliable measurement results, and frequent recalibration might be required. A possible solution could be blind calibration or the usage of mobile references.<ref>{{cite book |last1=Balzano |first1=L. |last2=Nowak |first2=R. |title=Networked Sensing Information and Control |chapter=Blind Calibration of Networks of Sensors: Theory and Algorithms |date=2008 |pages=9–37 | doi=10.1007/978-0-387-68845-9_1|isbn=978-0-387-68843-5 }}</ref><ref>{{cite book |last1=Sauce |first1=O. |last2=Hasenfratz |first2=D. |last3=Thiele|first3=L. |title=Proceedings of the 14th International Conference on Information Processing in Sensor Networks |chapter=Reducing multi-hop calibration errors in large-scale mobile sensor networks |date=2015 |pages=274–285 | doi=10.1145/2737095.2737113|isbn=978-1-4503-3475-4 |s2cid=15171166 }}</ref>