Marco Messina

SNMP Proxy for Wireless Sensor Network

In this paper the authors describe the implementation of a wireless sensor network of Micaz motes as a viable and effective solution for a health monitoring application that is connected to the Internet for global and remote monitoring. An architecture for this purpose has been developed. First, the network of wireless sensors gathers environmental and medical data and, using an enhanced graphical user interface (GUI) based on the CodeBlue software, then displays and stores data on the PC. The locally stored data are available for remote access via an SNMP-proxy connection. Finally a network management system installed on the remote server analyses the data collected. This approach provides a straightforward solution for an effective remote health monitoring application. The system has been tested using a series of experimental scenarios that have been established in the laboratory to (1) determine the reliability of the data collected from the mobile sensor network, and (2) determine the parameters for future expansion of the health monitoring network by introducing new sensors, alarm triggering algorithms, advanced security techniques, and location tracking capabilities.

Implementing and Validating an Environmental and Health Monitoring System

In this paper the authors describe the implementation and validation of a prototype of an environmental and health monitoring system based on a Wireless Sensor Network (WSN). The solution proposed for our system combines environmental and medical sensors in order to monitor both the surrounding area of the patient and the patients health status simultaneously. This feature would allow a comprehensive understanding of the patients condition by the specialist caring for the subject. Another key feature of the system is the development of an architecture which provides an easy, viable, cheap and effective way for connecting our environmental and medical sensor network of MicaZ motes to the outside world using Simple Network Management Protocol (SNMP) version 3. A series of experimental scenarios were developed and implemented in a laboratory setting; firstly for evaluating the reactivity of the monitoring system to changes and secondly for understanding the reliability of the data obtained for benchmarking purposes. The conclusion considers the implementation of future improvements to the health monitoring network by introducing new sensors and location tracking capabilities, and by integrating alarm triggering algorithms and advanced security techniques.

Design and Simulation of a Novel Biomechanic Piezoresistive Sensor With Silicon Nanowires

This paper presents the design of a novel single square millimeter three-axial accelerometer for head injury detection of racing car drivers. The main requirements of this application are miniaturization and medium/high-G measurement range. We propose a new miniature accelerometer to be incorporated into an earpiece. Nanowires as nanoscale piezoresistive devices have been chosen as sensing element, due to their high sensitivity and miniaturization achievable. By exploiting the electromechanical features of nanowires as nanoscale piezoresistors, the nominal sensor sensitivity is overall boosted by more than 30 times. This approach allows significant higher accuracy and resolution with smaller sensing element in comparison with conventional devices without the need of signal amplification. This achievement opens up new developments in the area of implanted devices where the high-level of miniaturization and sensitivity is essential.

Potential of silicon nanowires structures as nanoscale piezoresistors in mechanical sensors

This paper presents the design of a single square millimeter 3-axial accelerometer for bio-mechanics measurements that exploit the potential of silicon nanowires structures as nanoscale piezoresistors. The main requirements of this application are miniaturization and high measurement accuracy. Nanowires as nanoscale piezoresistive devices have been chosen as sensing element, due to their high sensitivity and miniaturization achievable. By exploiting the electro-mechanical features of nanowires as nanoscale piezoresistors, the nominal sensor sensitivity is overall boosted by more than 30 times. This approach allows significant higher accuracy and resolution with smaller sensing element in comparison with conventional devices without the need of signal amplification.

Mechanical Structural Design of a MEMS-Based Piezoresistive Accelerometer for Head Injuries Monitoring: A Computational Analysis by Increments of the Sensor Mass Moment of Inertia

This work focuses on the proof-mass mechanical structural design improvement of a tri-axial piezoresistive accelerometer specifically designed for head injuries monitoring where medium-G impacts are common; for example, in sports such as racing cars or American Football. The device requires the highest sensitivity achievable with a single proof-mass approach, and a very low error (<1%) as the accuracy for these types of applications is paramount. The optimization method differs from previous work as it is based on the progressive increment of the sensor proof-mass mass moment of inertia (MMI) in all three axes. Three different designs are presented in this study, where at each step of design evolution, the MMI of the sensor proof-mass gradually increases in all axes. The work numerically demonstrates that an increment of MMI determines an increment of device sensitivity with a simultaneous reduction of cross-axis sensitivity in the particular axis under study. This is due to the linkage between the external applied stress and the distribution of mass (of the proof-mass), and therefore of its mass moment of inertia. Progressively concentrating the mass on the axes where the piezoresistors are located (i.e., x- and y-axis) by increasing the MMI in the x- and y-axis, will undoubtedly increase the longitudinal stresses applied in that areas for a given external acceleration, therefore increasing the piezoresistors fractional resistance change and eventually positively affecting the sensor sensitivity. The final device shows a sensitivity increase of about 80% in the z-axis and a reduction of cross-axis sensitivity of 18% respect to state-of-art sensors available in the literature from a previous work of the authors. Sensor design, modelling, and optimization are presented, concluding the work with results, discussion, and conclusion.