Integrating modelling and smart sensors for environmental and human health

Reis, Stefan ORCID: https://orcid.org/0000-0003-2428-8320; Seto, Edmund; Northcross, Amanda; Quinn, Nigel W.T.; Convertino, Matteo; Jones, Rod L.; Maier, Holger R.; Schlink, Uwe; Steinle, Susanne; Vieno, Massimo ORCID: https://orcid.org/0000-0001-7741-9377; Wimberly, Michael C.. 2015 Integrating modelling and smart sensors for environmental and human health. Environmental Modelling & Software, 74. 238-246. https://doi.org/10.1016/j.envsoft.2015.06.003

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Official URL: http://dx.doi.org/10.1016/j.envsoft.2015.06.003

Abstract/Summary

Sensors are becoming ubiquitous in everyday life, generating data at an unprecedented rate and scale. However, models that assess impacts of human activities on environmental and human health, have typically been developed in contexts where data scarcity is the norm. Models are essential tools to understand processes, identify relationships, associations and causality, formalize stakeholder mental models, and to quantify the effects of prevention and interventions. They can help to explain data, as well as inform the deployment and location of sensors by identifying hotspots and areas of interest where data collection may achieve the best results. We identify a paradigm shift in how the integration of models and sensors can contribute to harnessing ‘Big Data’ and, more importantly, make the vital step from ‘Big Data’ to ‘Big Information’. In this paper, we illustrate current developments and identify key research needs using human and environmental health challenges as an example.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1016/j.envsoft.2015.06.003
UKCEH and CEH Sections/Science Areas:	Dise
ISSN:	1364-8152
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	integrated modelling, environmental sensors, population health, environmental health, big data
NORA Subject Terms:	Health Atmospheric Sciences Computer Science
Date made live:	01 Sep 2015 11:52 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/511700

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1016/j.envsoft.2015.06.003

UKCEH and CEH Sections/Science Areas:

Dise

ISSN:

1364-8152

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

integrated modelling, environmental sensors, population health, environmental health, big data