Editing Wireless sensor network (section)

===Environmental/Earth sensing ===
There are many applications in monitoring environmental parameters,<ref>{{Cite web|url=http://eprints.soton.ac.uk/263093/1/esn.pdf|archive-url=https://web.archive.org/web/20151123185424/http://eprints.soton.ac.uk/263093/1/esn.pdf|title=J.K.Hart and K. Martinez, "Environmental Sensor Networks: A revolution in the earth system science?", Earth-Science Reviews, 2006|archive-date=November 23, 2015}}</ref> examples of which are given below. They share the extra challenges of harsh environments and reduced power supply.

====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>

====Forest fire detection====
A network of Sensor Nodes can be installed in a forest to detect when a [[forest fire|fire]] has started. The nodes can be equipped with sensors to measure temperature, humidity and gases which are produced by fire in the trees or vegetation. The early detection is crucial for a successful action of the firefighters; thanks to Wireless Sensor Networks, the fire brigade will be able to know when a fire is started and how it is spreading.

====Landslide detection====
A [[landslide]] detection system makes use of a wireless sensor network to detect the slight movements of soil and changes in various parameters that may occur before or during a landslide. Through the data gathered it may be possible to know the impending occurrence of landslides long before it actually happens.

====Water quality monitoring====
[[Water quality]] monitoring involves analyzing water properties in dams, rivers, lakes and oceans, as well as underground water reserves. The use of many wireless distributed sensors enables the creation of a more accurate map of the water status, and allows the permanent deployment of monitoring stations in locations of difficult access, without the need of manual data retrieval.<ref>{{Cite journal | last1 = Spie | doi = 10.1117/2.3201305.05 | title = Vassili Karanassios: Energy scavenging to power remote sensors | journal = SPIE Newsroom | year = 2013 }}</ref>

====Natural disaster prevention====
Wireless sensor networks can be effective in preventing adverse consequences of [[natural disaster]]s, like floods. Wireless nodes have been deployed successfully in rivers, where changes in water levels must be monitored in real time.