Ambient-aware continuous aid for mountain rescue activities

Abstract

Ambient-awareness in conjunction with pervasive computing is a significant challenge for system designers. It follows the necessity of gathering raw, massive and heterogeneous environmental data which we obtained, while middleware processes must merge context modelling and reasoning seamlessly. We proposed a system supporting mountain rescuers which is demanding due to the large number of environmental objects interacting, as well as high data variability. We presented complex context processing embedded in the proposed context life cycle and implemented it in a difficult mountain environment. We introduced five weather scenarios which are a basis for contextual and perceptual processing during the validation of our model. The system merges a message streaming broker for massive data transport, low and high-level processing algorithms, repositories and a logical SAT solver. It constitutes a Context-Aware-as-a-Service (CAaaS) system, offering advanced support for mountain rescue operations. The provided software model defines middleware components which act on a predicted context and transform in situ sensor data into smart decisions, and which could operate as a platform-based cloud computing model. It is an enabler yielding a synergy effect with different software components orchestration when providing pro-activeness and non-intrusiveness concerning smart decisions.