Modern wireless sensor and actuator networks (WSANs) are composed of spatially distributed low cost nodes that can contain different sensors and actuators. Event condition action (ECA) based languages have been widely proposed in order to program WSANs. Implementing applications by using ECA rules is an error-prone process thus various formal methods have been proposed. In spite of this great variety, formal verification of ECA rules has not been tailored to the context of WSANs. In this paper we present IRON, an ECA language for programming WSANs. IRON allows the automatic verifications of ECA rules. These are used by the IRON run-time platform in order to implement the required behaviour

In this paper we show how state-of-the art SMT-based techniques for software verification can be employed in the verification of event–condition–action rules in intelligent environments. Moreover, we exploit the specific features of intelligent environments to optimise the verification process. We compare our approach with previous work in a detailed evaluation section, showing how it improves both performance and expressivity of the language for event–condition–action rules

Proliferation of structural, semi-structural and no-structural data, has challenged the scalability, flexibility and processability of the traditional relational database management systems (RDBMS). The next generation systems demand horizontal scaling by distributing data over autonomously addable nodes to a running system. For schema flexibility, they also want to process and store different data formats along the sequence factor in the data. NoSQL approaches are solutions to these, hence big data solutions are vital nowadays. But in monitoring scenarios sensors transmit the data continuously over certain intervals of time and temporal factor is the main property of the data. Therefore the key research aspect is to investigate schema flexibility and temporal data integration aspects together. We need to know that: what data modelling should we adopt for a data driven real-time scenario; that we could store the data effectively and evolve the schema accordingly during data integration in NoSQL environments without losing big data advantages. In this paper we explain a middleware based schema model to support the temporal oriented storage of real-time data of ANT+ sensors as hierarchical documents. We explain how to adopt a schema for the data integration by using an algorithm based approach for flexible evolution of the model for a document oriented database, i.e, MongoDB. The proposed model is logical, compact for storage and evolves seamlessly upon new data integration

In remote health care Body Area Networks (BAN) are very popular but demand low energy consumption due to very constrained resources. For it several protocols, such as ZigBee, BlueTooth, WiFi etc, have been proposed but non has delivered the optimum results. These systems also demand vast interoperability among devices. Recently a propriety protocol ANT+ provides such features and strengthens the goals for Internet of Things (IOT). The authors describe a software architecture which flexibly integrates ANT+ protocol enabled sensors to deliver health care services. The approach is validated on a health care application that integrates heart rate, cadence, distance, foot steps and environmental temperature sensors. Described architecture is modular, flexible, scalable and possess several features

No abstract