A framework for collaborative computing and multi-sensor data fusion in body sensor networks

Body Sensor Networks (BSNs) have emerged as the most effective technology enabling not only new e-Health methods and systems but also novel applications in human-centered areas such as electronic health care, fitness/welness systems, sport performance monitoring, interactive games, factory workers monitoring, and social physical interaction. Despite their enormous potential, they are currently mostly used only to monitor single individuals. Indeed, BSNs can proactively interact and collaborate to foster novel BSN applications centered on collaborative groups of individuals. In this paper, C-SPINE, a framework for Collaborative BSNs (CBSNs), is proposed. CBSNs are BSNs able to collaborate with each other to fulfill a common goal. They can support the development of novel smart wearable systems for cyberphysical pervasive computing environments. Collaboration therefore relies on interaction and synchronization among the CBSNs and on collaborative distributed computing atop the collaborating CBSNs. Specifically, collaboration is triggered upon CBSN proximity and relies on service-specific protocols allowing for managing services among the collaborating CBSNs. C-SPINE also natively supports multi-sensor data fusion among CBSNs to enable joint data analysis such as filtering, time-dependent data integration and classification. To demonstrate its effectiveness, C-SPINE is used to implement e-Shake, a collaborative CBSN system for the detection of emotions. The system is based on a multi-sensor data fusion schema to perform automatic detection of handshakes between two individuals and capture of possible heart-rate-based emotion reactions due to the individuals’ meeting

Collaborative body sensor networks

In this paper we propose reference architectures and SPINE-based middleware for Collaborative Body Sensor Networks (CBSNs) that can enable new smart wearable systems in the context of physical pervasive computing environments. CBSNs are wireless BSNs that are able to cooperate to support a common goal. Cooperation is therefore based on interaction among the CBSNs and distributed computation across the interacting CBSNs. In particular, interaction can be activated when CBSNs are in proximity and based on service-specific protocols that allow for service management between the involved CBSNs. Specifically, the paper presents C-SPINE, an enhancement of the SPINE middleware for CBSN applications. Finally, a collaborative emotion detection system, integrating heart rate sensing with handshake detection, is developed through C-SPINE and experimentally analyzed

TinyMAPS : a lightweight Java-based mobile agent system for wireless sensor networks

In the context of the development of wireless sensor network (WSN) applications, effective programming frameworks and middlewares for rapid and efficient prototyping of resource-constrained applications are highly required. Mobile agents are an effective distributed programming paradigm that is being used for WSN programming. However its diffusion is limited mainly due to the scarce availability of usable mobile agent systems for WSNs. This paper proposes TinyMAPS, a mobile agent system for programming WSNs based on the Sentilla sensor platform. TinyMAPS derives from MAPS (Mobile Agent Platform for Sun SPOT) and is specifically tailored for sensors more constrained than the Sun SPOTs. After providing a description of TinyMAPS and its comparison with MAPS, a simple yet effective case study implemented with TinyMAPS and concerning a real-time WBSN-based system for human activity monitoring is described

An analysis of java-based mobile agent platforms for wireless sensor networks

Wireless sensor networks (WSNs) represent a new form of pervasive and ubiquitous computing systems successfully exploited in many different application areas within which they will play an increasingly important role in future. However, the development of applications for WSNs is an extremely challenging and error-prone task, so that the need for high-level, effective programming approaches is quite evident. Among the programming paradigms proposed so far, the agent-based approach can be seen as an effective promising solution on the basis of which a few software platforms for WSNs have been already developed. This paper proposes an in-depth analysis of the only two available Java-based mobile agent platforms for WSNs: Mobile Agent Platform for Sun SPOT (MAPS) and Agent Factory Micro Edition (AFME). In particular, the architecture, programming model and basic performance of MAPS and AFME are described and compared. Moreover, a simple yet effective case study concerning a mobile agent-based monitoring system for remote sensing and aggregation is proposed. This case study is developed both in MAPS and AFME on Sun SPOTs so as to allow both an analysis of efficacy of their programming models and an evaluation of their performances