In this paper, we build upon the Internet of Things (IoT) paradigm, with aim of delivering networked solutions that enable to connect not only single sensors, but also whole wireless sensor networks (WSN) to the Internet in a secure, simple and efficient way, and describe the design and implementation of a smart-home management system. The system is composed of a lightweight tool with an intuitive user interface for commissioning of IPenabled WSN with constrained capabilities. The solution includes a visual programming interface with a common framework for discovering smart home services on the constrained WSN, and a code analysis and translation engine to generate python code. This engine analyses the application rules defined with the graphical user interface and translates them into distributed application scripts. The system also includes modules to plan the optimization of the deployment, and deploy and start the generated code. A prototype of the system, with the visual programming solution and code generation module developed is presented in this paper. Abstract-Most of the currently deployed integrated home management products require an experienced technician to install and configure the system. In this paper, we build upon the Internet of Things (IoT) paradigm, with the aim of delivering networked solutions that enable multi-node wireless sensor networks (WSNs) to connect to the Internet in a secure, simple and efficient way. We also describe the design and implementation of a smart-home management system. The system is composed of a lightweight tool with an intuitive user interface for commissioning of IP-enabled WSNs. The solution includes a visual programming interface with a common framework for discovering smart home services on the WSN, and a code analysis and translation engine to generate Python code. This engine analyses the application rules defined with the graphical user interface and translates them into distributed application scripts. The system also includes modules to plan the optimization of the deployment, and deploy and start the generated code. In this paper we present a prototype of the system, with the visual programming solution and code generation module.

This paper presents the simulation environment for the EIDOS (EquIpment Destined for Orientation and Safety) architecture applied to wildfire fighting operations. The development of this environment involves a multidisciplinary study, in which we have to handle several different types of information (geographical data, vegetation models, fire models, etc.) and devices (sensors, aerial vehicles, and mobile devices). Therefore, the simulation tool is actually composed of several independent and interconnected modules. Motivation and scopeForest fires represent one of the main causes of environmental degradation in many countries. Moreover, very often the people working directly on their extinction and residing in the area affected by the fire is in serious danger. With the final goal of reducing the risk to which these people are exposed, and increasing the efficacy of wildfire fighting operations, recently we have proposed the EIDOS system [4]. This architecture is based on the use of a WSN (wireless sensor network), which is deployed over the area affected by the fire, and is able to provide the fire-fighters with critical information in real time, contributing to increment their safety.Several recent works propose using WSNs for firefighting. As an example, FireNet [2] focuses on fire rescue in urban areas. In this proposal, each fire-fighter carries a Crossbow Mica2/MicaZ [1] (attached with a sensor board), that is able to sense data and forward packets to the sink node (located in the incident commander vehicle). Another representative proposal may be FireWxNet [7], which presents a complex tiered architecture for wildfire environments. In almost all these proposals, the purpose of the sensor network consists in just acquiring environmental data. Then, this information is gathered in a central server (for example a PC), where it is displayed, stored in a database, processed, used as input for some fire prediction software, or sent to a remote location.However, in the EIDOS system, the information collected by the network is processed by the sensors themselves in a collaborative way, with the aim of obtaining information about the localization of the active fire fronts and their evolution along the time. Finally, the result of this processing can be transmitted either to the people working in fighting operations (equipped with mobile devices), or to a base station.Although we plan to build a real prototype bringing together the subsystems we are designing, the initial phase of the EIDOS development will be carried out over a simulation environment. This platform will allow us to analyze and refine the behavior of our proposals. In this paper, we provide a description of this simulation environment.Next, the architecture and functionality of the EIDOS system are introduced. Then, an outlook of the simulator tool is presented, and the modules composing it are detailed. Finally, some conclusions are given, and future work is proposed. EIDOS system ArchitectureAt a glance, the EIDOS system consists of three types ...

Disaster management is one of the most relevant application fields of wireless sensor networks. In this application, the role of the sensor network usually consists of obtaining a representation or a model of a physical phenomenon spreading through the affected area. In this work we focus on forest firefighting operations, proposing three fully distributed ways for approximating the actual shape of the fire. In the simplest approach, a circular burnt area is assumed around each node that has detected the fire and the union of these circles gives the overall fire’s shape. However, as this approach makes an intensive use of the wireless sensor network resources, we have proposed to incorporate two in-network aggregation techniques, which do not require considering the complete set of fire detections. The first technique models the fire by means of a complex shape composed of multiple convex hulls representing different burning areas, while the second technique uses a set of arbitrary polygons. Performance evaluation of realistic fire models on computer simulations reveals that the method based on arbitrary polygons obtains an improvement of 20% in terms of accuracy of the fire shape approximation, reducing the overhead in-network resources to 10% in the best case.