In the new era of connectivity, marked by the explosive number of wireless electronic devices and the need for smart and pervasive applications, Machine-to-Machine (M2M) communications are an emerging technology that enables the seamless device interconnection without the need of human interaction. The use of M2M technology can bring to life a wide range of mHealth applications, with considerable benefits for both patients and healthcare providers. Many technological challenges have to be met, however, to ensure the widespread adoption of mHealth solutions in the future. In this context, we aim to provide a comprehensive survey on M2M systems for mHealth applications from a wireless communication perspective. An end-to-end holistic approach is adopted, focusing on different communication aspects of the M2M architecture. Hence, we first provide a systematic review ofWireless Body Area Networks (WBANs), which constitute the enabling technology at the patient’s side, and then discuss end-to-end solutions that involve the design and implementation of practical mHealth applications. We close the survey by identifying challenges and open research issues, thus paving the way for future research opportunities.

This paper describes a new industrial case on automation, for large‐scale systems with high environmental impact: the mining ventilation control systems. Ventilation control is essential for the operation of a mine in terms of safety (CO and NO_x regulation) and energy optimization. We first discuss a novel regulation architecture, highlighting the interest for a model‐based control approach and the use of distributed sensing capabilities thanks to a wireless sensor network (WSN). We propose a new model for underground ventilation. The main components of the system dynamics are described with time‐delays, transmission errors, energy losses and concentration profiles. Two different model‐based control approaches, which can embody the complex dynamics of the system, are proposed. The first one resorts to a nonlinear model predictive control strategy (receding horizon) and aims to energy minimization, thanks to a continuous operation of the fans. The second one, based on a hybrid description of the model and fans operation, provides automatic verification of the wireless control thanks to abstraction techniques. These control strategies are compared with simulations, in terms of regulation efficiency, energy consumption and the need for computational capabilities. The industrial case description and control strategies open new vistas for the development of global system approaches that allow for the optimization of energy consumption of complex large‐scale systems. Copyright © 2009 John Wiley & Sons, Ltd.

People worldwide are getting older and this fact has pushed the need for designing new, more pervasive, and possibly cost effective healthcare systems. In this field, distributed and networked embedded systems, such as wireless sensor networks (WSNs), are the most appealing technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. This paper proposes recent advancements in this field by introducing WSN4QoL, a Marie Curie project which involves academic and industrial partners from three EU countries. The project aims to propose new WSN-based technologies to meet the specific requirements of pervasive healthcare applications. In particular, in this paper, the system architecture is presented to cope with the challenges imposed by the specific application scenario. This includes a network coding (NC) mechanism and a distributed localization solution that have been implemented on WSN testbeds to achieve efficiency in the communications and to enable indoor people tracking. Preliminary results in a real environment show good system performance that meet our expectations.

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.