Design and realisation of a substrate integrated waveguide (SIW) planar sensor for the non-invasive monitoring of blood glucose concentration (BGC) is described. The structure of the presented sensor is similar to a conventional band-stop filter. To produce a substantial and localised field enhancement in the sensing region by the SIW technology, the slots and interdigital arms on the upper conductor of the SIW cavity are utilised. Further, the fingertip is used as materials under test and its displacement and fingerprints effects are studied. The introduced sensor is then fabricated and measured. The evaluated results indicate that the developed sensor features improvement in both the fingertip positioning and fingerprints effects compared to the other work. Also, the frequency resonance shift of the proposed sensor observing the valuable enhancement of non-invasive BGC detection sensitivity is much more than the previous study.

In this study, the authors address the problem of combining hierarchical and flat techniques to construct and maintain nodes’ connectivity as well as links’ symmetry (bidirectionality) in a wireless sensor network (WSN) comprising static nodes. They propose a localised and asynchronous self-stabilising hybrid message passing a solution that seamlessly merges three well known connectivity control techniques for such ad hoc networks, namely k-hop clustering , power control (transmission range adjustment) and sleep/wake scheduling. Their stigmergy-based strategy (i.e. inspired from ants’ pheromone-based communication, division of labour and swarming behaviours) allows a WSN to simultaneously cope with issues such as scalability, fault tolerance, transmission range minimisation, energy hole problem (i.e. premature node deaths in the vicinity of the sink), channel overhearing and signalisation reduction. To the best of their knowledge, such a solution does not exist in the literature. The few self-stabilising hybrid connectivity control protocols currently proposed use only two of the above-mentioned techniques. The authors formally prove the correctness of their scheme and its self-stabilisation property under an unfair distributed daemon. Simulation results show that the proposed scheme has a low average convergence time, is energy efficient and can prolong network lifetime.

In this study, a solution focusing on energy efficiency of wireless sensor nodes is presented. Energy dissipation is a key factor affecting the usability of wireless sensor networks (WSNs) in that, in worst cases, in systems without electric mains, the life of a sensor node battery may last even only a few hours. The proposed solution is characterised by very low costs thanks to the use of a small number of electronic components: it allows the optimisation of duty cycling (i.e. the ratio between activity and inactivity periods of sensor nodes) by power gating the node (i.e. turning the whole circuitry off). In particular, this solution is useful for applications that use active power-hungry sensors that are sampled regularly 10 to 1000 times a day. The described power control logic system is able to optimise the duty cycling, notably reducing the power consumption during idle periods, thus increasing the battery life at best up to 100–200 times: this means that the autonomous operation time of a WSN can increase from a few days to several months or even to some years according to the required sampling rate.

Energy efficiency is a fundamental aspect for wireless body area networks (WBANs) due to the limited battery capacity and miniaturisation of sensor nodes. Prolonging the lifespan of a WBAN depends mostly on maximising the energy efficiency. WBAN systems operate under conflicting requirements of energy and spectrum efficiency. In this study, the two metrics of energy and spectrum efficiency for direct communication links for in-body and on-body sensor nodes are analysed. A general device-to-device communication model was adapted to WBAN. Optimal transmission power values to achieve maximum energy efficiency for in-body and on-body communication links are found. With reference to a maximum power level of 1.5 W compliant with the Federal Communications Commission for WBAN, it is also deduced that for on-body communication, decreasing maximum possible spectrum efficiency by 33% for medical devices operating in 400–450 and 950–956 MHz would improve energy efficiency by 75 times. Moreover, by decreasing spectrum efficiency by 38.3 and 48% leads to an increase in energy efficiency by 45.3 and 39.3 times in 2.4–2.5 and 3.1–10.6 GHz frequency bands, respectively. This trade-off is significant for medical applications having strict energy requirements.

The Internet Engineering Task Force (IETF) has developed and promoted several standards intended to facilitate Internet of things communication among constrained devices in low-power low-rate networks (LLNs). Specifically, IETF introduces a series of protocols that deal with different layers of the stack ranging from IPv6 adaptation to routing in LLN. Among them, the constrained application protocol (CoAP) is a session protocol that is used to carry sensor and actuator traffic. Since CoAP transport relies on the user datagram protocol, and in order to provide reliability, it introduces a mode operation known as confirmable where messages are considered delivered once they have been acknowledged. One drawback of this approach, however, is the latency that results from the retransmission of packets in lossy networks. In this study, the authors present, model, compare and evaluate a forward error correction mechanism that enables CoAP to improve its reliability while reducing latency.

MEMS based wireless sensor network (WSN) for real-time human health monitoring is promising in home-based rehabilitation. It requires effective integration of a number of MEMS sensors and their placement on the human body to create a wireless body area network for continuous and timely monitoring of various biophysical parameters. This study attempts to develop an XBee-based WSN for real-time monitoring of human gait. Traditionally, the optical motion systems were used for gait analysis but they suffer from certain limitations such as the development of the complex algorithm and constrains in the work space. In comparison to the optical system, the attractive benefits of MEMS-based sensor systems are small size and low cost. Magnetic field angular rate and gravity sensor system can perform a complete analysis of the human gait. The sensor modules were developed using the inertial sensors mainly accelerometer and gyro sensor. LabVIEW software is used for data acquisition from the body sensor nodes and gait analysis. Biometrics Lab System is used as the standard system for calibration of data obtained from sensors. The joint angle range of motion was calculated using both the systems. The advantage of the proposed system is that it facilitates wireless transmission of gait parameters (joint angle measurement) for easy monitoring of human gait in various rehabilitation programmes.