Wireless Sensor Networks are an emerging technology which has been recently adopted in many applications. Due to its wireless nature, the analysis of the radio propagation models plays an important role for performance evaluation in both theoretical and practical aspects. In this regards, path loss exponent is one of the most important parameter which has been considered widely in wireless communications analysis. There are several theoretical evaluations of path loss exponent for wireless sensor networks available in the literature. However there is a lack of experimental evaluation of both path loss exponent and the effect of shadowing. In this paper, three environments (free space, in building and industrial), where wireless sensor nodes are widely deployed, have been chosen in order to evaluate the experimental analysis. Path loss and path loss exponent are measured by means of Received Signal Strength Indicator (RSSI) and based on them, the standard deviation of shadowing effect is also calculated. All the measured parameters are compared with the theoretical analysis available in the literatures.

Background: Pedometers are considered desirable devices for monitoring physical activity. Two population groups of interest include patients having undergone surgery in the lower extremities or who are otherwise weakened through disease, medical treatment, or surgery procedures, as well as the slow walking senior population. For these population groups, pedometers must be able to perform reliably and accurately at slow walking speeds. The objectives of this study were to evaluate the step count accuracy of three commercially available pedometers, the Yamax (Tokyo, Japan) Digi-Walker ^® SW-200 (YM), the Omron (Kyoto, Japan) HJ-720 (OM), and the Fitbit (San Francisco, CA) Zip (FB), at slow walking speeds, specifically at 1, 2, and 3 km/h, and to raise awareness of the necessity of focusing research on step-counting devices and algorithms for slow walking populations. Materials and Methods: Fourteen participants 29.93 ±4.93 years of age were requested to walk on a treadmill at the three specified speeds, in four trials of 100 steps each. The devices were worn by the participants on the waist belt. The pedometer counts were recorded, and the error percentage was calculated. Results: The error rate of all three evaluated pedometers decreased with the increase of speed: at 1 km/h the error rates varied from 87.11% (YM) to 95.98% (FB), at 2 km/h the error rates varied from 17.27% (FB) to 46.46% (YM), and at 3 km/h the error rates varied from 22.46% (YM) to a slight overcount of 0.70% (FB). Conclusions: It was observed that all the evaluated devices have high error rates at 1 km/h and mixed error rates at 2 km/h, and at 3 km/h the error rates are the smallest of the three assessed speeds, with the OM and the FB having a slight overcount. These results show that research on pedometers' software and hardware should focus more on accurate step detection at slow walking speeds.

Population aging and increasing pressure on health systems are two issues that demand solutions. Involving and empowering citizens as active managers of their health represents a desirable shift from the current culture mainly focused on treatment of disease, to one also focused on continuous health management and well-being. Current developments in technological areas such as the Internet of Things (IoT), lead to new technological solutions that can aid this shift in the healthcare sector. This study presents the design, development, implementation and evaluation of a platform called Common Recognition and Identification Platform (CRIP), a part of the CareStore project, which aims at supporting caregivers and citizens to manage health routines in a seamless way. Specifically, the CRIP offers sensor-based support for seamless identification of users and health devices. A set of initial requirements was defined with a focus on usability limitations and current sensor technologies. The CRIP was designed and implemented using several technologies that enable seamless integration and interaction of sensors and people, namely Near Field Communication and fingerprint biometrics for identification and authentication, Bluetooth for communication with health devices and web services for wider integration with other platforms. Two CRIP prototypes were implemented and evaluated in laboratory during a period of eight months. The evaluations consisted of identifying users and devices, as well as seamlessly configure and acquire vital data from the last. Also, the entire Carestore platform was deployed in a nursing home where its usability was evaluated with caregivers. The evaluations helped assess that seamless identification of users and seamless configuration and communication with health devices is feasible and can help enable the IoT on healthcare applications. Therefore, the CRIP and similar platforms could be transformed into a valuable enabling technology for secure and reliable IoT deployments on the healthcare sector.

Wireless technologies are currently among the most prominent candidates for use by the medical and care-giving community as a part of the development of telemedicine systems. The exponential progress of these technologies is expected to open a multitude of opportunities and choices for enhanced patient safety, better data collection, increased convenience for patients, and reduced costs for health systems. Thanks to the cost effectiveness and clinical acceptability of wireless telecommunication technology, patient diagnosis and treatment have been significantly improved. Technology for remote sensing of patients' activity is also being developed.

An innovative e-healthcare platform named common recognition and identification platform (CRIP) was developed and tested as part of the CareStore project. CareStore and CRIP aims at delivering accurate and safe disease management by minimising human operator errors in hospitals and care facilities. To support this, the CRIP platform features fingerprint biometrics and near field communication (NFC) for user identification; and Bluetooth communication support for a range of telemedicine medical devices adhering to the IEEE 11073 standard. The aim of this study was to evaluate the electromagnetic compatibility (EMC) immunity of the CRIP platform in order to validate it for medical application use. The first prototype of CRIP was demonstrated to operate as expected by showing the user identification function feasibility, both via NFC and biometric, and by detection of Bluetooth devices via radio frequency (RF) scanning. The NFC module works in the 13.56 MHz band and the Bluetooth module work in the 2.4 GHz band, according to the IEEE 802.15.1 standard. The standard test qualification of the CRIP was performed based on the radiated EMC immunity with respect to the EN 61000-4-3 standard. The immunity tests were conducted under industrial EMC compliance with electric field aggression, with levels up to 10 V/m in both horizontal and vertical polarisations when the test antenna and the CRIP were placed at a distance of 3 m. It was found that the CRIP device complies with the European electromagnetic (EM) radiation immunity requirements.

This paper presents a real-time system based on Wireless Sensor Network (WSN) capable of detecting collisions of vehicles with motorways' guardrails. The system is based on Service Oriented Architecture (SOA) with web services, where the WSN and other applications, like alarm systems and management of WSNs, are connected. It is also presented a simulation based mathematical model using finite element methods, in order to improve the reliability of collision detection.