In the environmental research setting, novel smartphone-based software that records people's movements and physical activity levels in the urban environment and is integrated with spatial temporal maps of air pollution is already being developed to enhance large-scale air pollution exposure data collection in a cost-effective, accurate unobtrusive way (de Nazelle et al. 2013).
Underwater sensor networks find applications in oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, and tactical surveillance.
This interest is highly motivated by various applications, such as scientific exploration, commercial exploitation, oceanographic data collection, pollution monitoring, tactical surveillance, and coastline protection.
UASNs are poised to enable a wide range of underwater-specific applications such as oceanographic data collection, pollution monitoring, disaster prevention, assisted navigation, marine surveillance, etc. [1].
Three-dimensional (3D) wireless sensor networks have attracted a lot of attention due to their great potential usages in both commercial and civilian applications, such as environmental data collection, pollution monitoring, space exploration, disaster prevention, and tactical surveillance.
Recently, there has been a growing interest in monitoring aqueous environments for scientific exploration, commercial exploitation and attack protection, such as oceanographic data collection, pollution monitoring, offshore exploration, disaster prevention, assisted navigation, and tactical surveillance.
Due to its wide-range potential applications (such as environmental data collection, pollution monitoring, space exploration, disaster prevention, and tactical surveillance), 3D wireless sensor network has recently emerged as a premier research topic.
So far, India's collection of pollution data has been haphazard and compares poorly with regional rival China.
One possible reason for seeing consistently stronger associations with APMoSPHERE based analyses is that APMoSPHERE used air pollution data closer in time to the collection of health data.
