Concluding remarks and future directions
The use of AR and VR technologies shows great potential for applications in environmental and disaster studies in the contexts of decision-making, education and awareness. Conventional data-sensing approaches can be complemented with modem data-collection methods using AR to reduce the cost of sensor deployment and maintenance in terms of invested time and resources and increase data coverage complementing conventional sensor technologies. Furthermore, AR-based data-collection approaches can enable citizen science applications for crowdsourcing geospatial data, thus decreasing the cost of computational resources supported by an agency or an organization. These developments can be facilitated by several factors including advancements in mobile sensor technologies in terms of accuracy, size and cost. Another factor is the newly available 5G cellular network that will result in increasing mobile streaming capabilities for faster transfers of complex and high-resolution 3D models, denser sensor coverage and data points with a more comprehensive and detailed reporting.
Immersive simulation environments can support advanced analysis and scenario evaluation applications in decision support systems. The presented applications serve as prototypes and a demonstration of the potential of AR and VR applications in environmental science education and training. They also highlight various opportunities for advancement and directions for future research. Collaborative activities in immersive simulations are vital for allowing stakeholders from different physical locations to work on a common goal. AR and VR applications can support the new science of socio-hydrolog)', which treats people as an important part of the water cycle through water consumption, pollution of freshwater resources, policies and technology (Sivapalan, Savenije, & Bloschl, 2012). For 3D representation of real-world features, structural and terrain-related data need to be shared in a consensual format for easy integration to immersive systems to support the vision of global and generalized simulation platforms. Physics-based scientific dynamics and animations need to be incorporated into these applications to examine the chain-reactions caused by extreme events and human intervention. Benefiting the recent developments in deep learning and artificial intelligence in general, detailed simulations of people and their behaviours during various environmental scenarios can be developed and integrated into immersive frameworks.
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