Acoustic Lamb Wave microsensors are suitable for label free sensing in liquid. The device relies on the interaction between acoustic waves propagating within a thin membrane and the liquid. Lamb wave sensors have been previously studied using AlN/Si structure to detect multi-parameters of a liquid, such as its temperature, density, sound velocity and viscosity using various modes as A₀ and S₀. These devices already showed good ability to perform measurements on fluids (gas or liquid) but in this case, chemical wet etching silicon was used to realize thin membranes combined with an Aln piezoelectric layer used to generate and detect the acoustic wave.

This paper reports the use of Gallium Arsenide as piezoelectric material to generate and propagate Lamb waves. GaAs material presents intrinsically interesting piezoelectric properties and is compatible with wet chemical etching process. The fabrication process allows producing a thin membrane but is also adapted for microfluidic microchannels. So, the same substrate can be used for the resonant structure and its excitation. The design of the resonant structure has been optimized using simulations to adapt the design of interdigital electrodes to the GaAs substrate taking into account the shear piezoelectric coefficient and its orientation. An experimental setup has been realized and measurements of the interaction with fluids are presented.

The flexibility of new age wireless networks and the variety of sensors to measure a high number of variables, lead to new scenarios where anything can be monitored by little electronic devices, thereby building Wireless Sensor Networks (WSN). Thanks to ZigBee, RFID or Wi-Fi networks the precise position of humans or animals as well as some biological parameters can be known in real-time. However, since wireless sensors must be attached to biological tissues and they are highly dispersive, propagation of the electromagnetic waves must be studied to build an efficient and well-working network. In this work, the radio wave propagation produced by ZigBee devices working over ISM 2.4GHz based network is studied through a home-made 3D Ray Launching simulation tool. Furthermore, a simplified dog model is developed for the chosen simulation code, considering not only its morphology but also its dielectric properties. This model is placed inside a home, taking under consideration all the furniture (tables, chairs, mirrors, etc.) and some measurements have been carried out attaching ZigBee based Xbee motes to a real dog. Power distribution, Power delay profile and delay spread graphs are extracted from simulation results concluding in an extensive and accurate wireless radio propagation studio. Finally, a dog monitoring system is presented, it works over the zigbee network and sends information to Android based devices.

Two main uncertainty sources can affect the response of polysilicon MEMS during standard on-chip measurements: the overetch induced by the deep reactive-ion etching process; the mechanical properties of the aggregate of silicon grains. The former one can be reduced by finer fabrication techniques, not adopted indeed in mass production processes, while the latter one is related to the length-scale of the devices.

Due to the increasing miniaturization, the width of some MEMS components may become comparable to that of a silicon grain and the relevant effective mechanical properties can vary significantly from one device to another. In this work, through on-chip tests we investigate the response of polysilicon films using standard electrostatic actuation/sensing. The results of such experimental campaign are then compared to an analytical reduced-order model of the structure, and to coupled electro-mechanical simulations accounting for the stochastic morphology of the silicon film. These two models are adopted to bilaterally bound the experimental data up to pull-in, and to assess the scattering induced by the random orientation of the crystal lattice of each grain in digital Voronoi tessellations of the slender parts of the devices.

Future factory production and assembly environments require smart automation and are controlled by a massively increasing number of computers with sensorial feedback from machines, parts, products, and humans, consisting of a wide variety of different networked devices and software programs, which can be considered as one big use case of pervasive and cloud computing with vanishing boundaries between the computing and the environment, and with a strong focus on decentralized distributed computing and information storage. These new complex information processing architectures are composed of hierarchical network graphs, and require some kind of self-organization and adaptability to overcome single-point of failure and robustness constraints. The data acquired from machines and sensitive products or parts are growing at a fast rate, leading to a large data volume that must be handled distributed  with pre-processing, map- and reduce, and filtering algorithms.

Mobile Agents can be deployed in such large-scale and hierarchical network environments crossing barriers transparently, for example, industrial manufacturing and assembly environments, the Internet, Sensor Networks, and Cyber-Physical Systems. The networks can consist of high- and low-resource nodes ranging from generic computers to microchips, and the supported network classes range from body area networks to the Internet including any kind of sensor and ambient network. Mobile Agents can perform distributed computation in an autonomous manner.

In this work Agents are represented by mobile program code that can be modified at run-time by the Agents themselves. The presented approach enables the development of sensor clouds and smart systems of the future integrated in daily use computing environments and the Internet. Agents can migrate between different hardware and software platforms by migrating the program code of the agent, which embeds  the control state and the private data of an agent, finally encapsulated in self-initializing and self-containing code frames.

This cross-platform interoperability is ensured by a modular and scalable Agent Processing Platform. The entire information exchange and co-ordination of Agents with other Agents and the environment is performed by using a Tuple Space database, unifying the platform and architecture specific data representation. The Tuple Space is used for any kind of information exchange including program code and directory and file system services mapped on the Tuple Space. Beside architecture specific hardware and software implementations of the agent processing platform, there is a JavaScript (JS) implementation layered on the top of a distributed co-ordination and management layer including distributed file and name services. The JS platform enables the integration of Multi-Agent Systems (MAS) in Internet server and application environments (e.g., WEB browser). Agents can migrate transparently between different classes of computing devices and environments, ranging from hardware-level sensor networks (embedded in technical structures) to WEB browser applications or network servers without any required transformation.

Smart meter facilitates real-time communication between the customer and the utility company offering various advantages to both the suppliers and the consumers. Problems such as meter reading, information on energy and water usage, demand requirements, varying tariff, billing and theft can be solved through smart metering. This paper presents the design and implementation of an automatic electricity and water meter system. The system consists of the smart meter comprising a GSM board, Arduino microcontroller, a clamp current sensor together with a water flow sensor for measuring the amount of electricity and water consumed.  An in-house display which communicates with the smart meter via a RF link offers the consumers access to real-time data of their consumption.  The in-house display system, which requires authentication to communicate with the smart meter, also offers the users to set usage limits with short message service (SMS) alerts, and turn on/off the supply of electricity or water. The usage details are also sent to the suppliers via a SMS for billing purpose. The supplier also has access to the smart meter system, as they can set usage limits or cut off supply in cases such as bills not being paid.

Current small unmanned aerial vehicles (UAV) or target drones used for artillery training are being made of materials other than metallic, such as carbon-fiber or fiberglass composites. From the electromagnetic point of view this fact forces engineers and scientists to assess how these changes may affect the structure in terms of, for instance, electromagnetic compatibility (EMC) or radar response. In order to do so, estimations of the constitutive parameters of these new materials has become a need. Several techniques exist to perform this kind of estimations, all of them based on the utilization of different sensors. For this paper, an own implementation of the so-called metal-backed free-space technique, based on the employment of antenna probes, is utilized. Apart from the technique itself, different extraction algorithms can be chosen.

In this regard, this paper examines the behavior of several algorithms when applied to extract the complex permittivity from the reflection coefficient of a set of materials. The algorithms studied include Pattern Search, Genetic Algorithms, Particle Swarm Optimization, Newton Search and Müller Search. First, the algorithms are analyzed using simulated reflection coefficient data. Then, those that perform better are applied to actual measured reflection coefficients of fiberglass materials that form part of a target drone employed by INTA. The results are compared with the estimations given by a commercial solution based on another sensor and technique: the open ended coaxial probe. Proper conclusions are extracted regarding the performance of the adopted approach.

With the popularity of visual sensor on mobile devices, that is the cameras, it becomes a habit for many people to take photos everyday and everywhere.
This led to the rapid expansion in number of personal photos and becomes a problem to the users in storing and organizing them, which had not been faced before.
Fortunately, cloud storage provided a comprehensive solution at the right moment, and it facilitates the synchronization and sharing of photos acquired.
However, organizing this large number of personal photos is still a tedious and painful task.
Common needs in photo organization may include tagging, removing duplicated or similar photos, and grouping photos into albums.
In this paper, we target to provide a smart personal photo organizing application which make use of existing sensors and related technologies to help users to handle duplicated or similar photos more efficiently.
For example, photos can be sorted, reorganized or searched according to different information, like geographical, time or appearance, acquired from various sensors on the mobile device.
By harnessing the power of cloud computing for image analysis and face recognition algorithm, our system significantly reduce the time spent on managing photos in a neat and tidy way which reduce user frustration and enhance user experience.

There are studies that use a combination of daylight and automatic electric lighting systems that allow a noticeable energy reduction in no residential buildings. However, in order to be able to determine the energetic performance of a building, it is necessary to know the natural illumination levels of natural lighting of the location were the maximum benefit is found. Recently, several illuminance studies are being done focusing on the construction field due to the trend of saving energy and the design of sustainable buildings. Nevertheless, studies that match outside daylight measurements with building inside illumination measurement or with building scale models measurement are not found. But currently, it is a priority for engineers, architects and researchers to reduce the number of luminaires and electricity consumption through the suitable and efficient use of sunlight. The aim of this work is to obtain an empirical model that allows determining the illuminances in a projected building, based on a scale model and daylight measurements. This way, it is possible to optimize some building parameters as orientation, numbers and sizes of the windows, etc…, to obtain the best conditions for the maximum use of natural light with the consistently energy saving. To do this, the global illuminance on horizontal surfaces within a room and in its scale model for different distances from the façade windows has been measured with photometric sensors previously calibrated and connected to dataloggers. Also, one photometric sensor is placed outside the model to known the global exterior horizontal illuminance. From these measures a ratio between global horizontal illuminance in the real space and in the scale model has been obtained. This ratio depends on the global horizontal exterior illuminance and the facade distance. For each distance to the facade the relation between the global horizontal illuminance on the real space and the scale model depends linearly on the global horizontal exterior illuminance. From this linearly relation, the slope an intercept parameters and its variation to the face distance has been obtained. It has been observed that not only the slope of each fitted line as well as the intercept have a linear dependence with the façade distance. From this data, a general equation that allows obtaining a global horizontal illuminance in a real enclosure from measurements taken inside a scale model and the global horizontal exterior illuminance has been obtained.

Since many senior citizens in nowadays choose to live alone, providing health care initiates to have its new challenges. Many examples demonstrated that in certain situations our senior citizens happen to be badly injured within their home and not capable of seeking a help. The work presented in this paper is a part of the SMARTA project focused on the wearable and environmental monitoring for the active aging. Sensorized garments and accelerometers fixed on the ground can implement an integrated sensor system for monitoring elderly indoor and outdoor for a smart house and a smart city.

The Wearable system consists in a sensorized garment in male and female version and coupled with a small electronic unit allows for the realization of a wearable system for non-intrusive monitoring of individual parameters characterizing the elderly and its physiological state in terms of health and well-being.

These sensory systems send data to a body/home gateway that redirects them to a center which concentrates data and implements the monitoring and intervention services.

A clinical trial is testing the reliability, the acceptability and the performance of the system for future implementation of new prevention services.

Obesity and other lifestyle-related illness are among the top healthcare challenges in Europe. Obesity alone accounts for up to 7% of healthcare costs in the EU, as well as wider economy costs associated with lower productivity, lost output and premature death. Obesity in younger age is an alarming predictor for obesity in adulthood, but also entails short term health complications in juvenile age along with greater risk of social and psychological problems.
Knowing how to stay healthy is not enough to motivate individuals to adopt healthy lifestyles, but relevant progress can be achieved through the use of incentives delivered through a combination of processes and mobile technologies.

The PEGASO system framework will address prevention, by offering to teenagers – the primary target of PEGASO - three main functionalities:
1) Individual & Environmental Monitoring – This dimension consists of the environmental, behavioural and physiological analysis of young users, through a high level-monitoring platform including wearable sensors and mobile phone as well as multimedia diaries for the acquisition of physical, behavioural and emotional attitude of adolescent.
2) Feedback System - the second functionality is aimed at providing a feedback in terms of “health status” changes, required actions to undertake and so on. This function will also propose personalized healthy modification of the lifestyle (in terms of diet and/or physical activity), thus promoting the active involvement of adolescents in changing their behaviours.
3) Social connectivity and engagement - The third dimension extends to include a social network where the user can share experiences with a community of peers concerning e.g. physical activity, food consumptions and everyday habits through different gaming strategies.

This paper presents the results of design, development and validation of the wearable platform of the PEGASO system, in which aesthetical and technical requirements are equally crucial for the acceptability and reliability of the complete system.