Cognitive Radio Networks: A Practical Perspective

Guest Editoria

Energy-aware systems for improving the well-being of older people by reducing their energy consumption

Fuel poverty is becoming a problem amongst the older community in the UK. To help reduce the anxiety that fuel poverty places on older members of the community, this paper will first address why such systems are necessary before introducing a system and various interfaces for engaging and promoting better energy usage. Key areas of the proposed prototype will be discussed which focuses on a recommender and behavioural change system which enables older people to improve their energy footprint through energy-aware systems. Using systems to help reduce fuel poverty will invariably improve their general well-being. Results show how this technology can be accepted and act as an enabler in improving the overall well-being of older people as well as other system considerations. In addition, a number of subsequent phases of the project will be detailed which will discuss a longer test duration, an analysis of the data harvested and future directions

Energy-Aware systems for improving the well-being of older people by reducing their energy consumption

Fuel poverty is becoming a problem amongst the older community in the UK. To help reduce the anxiety that fuel poverty places on older members of the community, this paper will first address why such systems are necessary before introducing a system and various interfaces for engaging and promoting better energy usage. Key areas of the proposed prototype will be discussed which focuses on a recommender and behavioural change system which enables older people to improve their energy footprint through energy-aware systems. Using systems to help reduce fuel poverty will invariably improve their general well-being. Results show how this technology can be accepted and act as an enabler in improving the overall well-being of older people as well as other system considerations. In addition, a number of subsequent phases of the project will be detailed which will discuss a longer test duration, an analysis of the data harvested and future directions

Miniaturized antenna and transponder based wireless sensors for internet of things in healthcare

Future medical and healthcare systems will be largely improved by the wide-spreading of internet of things (IoTs). One of the crucial challenges of IoTs for healthcare is at the wireless sensors. Miniaturization of sensor node profile, minimizing power consumption as well as lowering down design/production cost of antenna, RF circuits and sensor modules have become the key issues for realizing more exciting applications in medical and healthcare fields that never seemed to be possible before. In this dissertation work, we first focus on electrically small antenna (ESA) design and fabrication for medical telemetry. A comprehensive analysis of the radiation properties of a novel electrically small folded ellipsoidal ESA is presented, showing its ability to self-resonate and impedance match without external components. It will benefit various size-restricted applications especially with wireless medical implants. The second focus is on healthcare sensors using ESA as the sensing agent, which saves the power and cost by eliminating the need of extra sensing modules. Specifically, miniaturized helix ESAs are integrated with drug reservoirs to function as wireless transponder sensors for real-time drug dosage monitoring. We also introduce a system level innovation of a passive wireless harmonic transponder/harmonic sniffer/frequency hopped interrogator based sensing system. The μL- liquid level resolution and absolute-accuracy passive sensing is demonstrated in the presence of strong direct coupling, background scatters, distance variance as well as near-filed human body movement interference. Furthermore, we investigate how modern ubiquitous wireless sensor networks could take advantage of sensitive nanostructure materials for enhanced performance. Here we propose a new paradigm of chemically-gated mixed modulation on a single homogeneous graphene device in which the chemical exposure directly modulates an electrical carrier signal. To make the device ubiquitously reusable, a method of precisely tuning the charge neutrality point (Vcnp) is introduced by electrochemical calibration with gate voltage pulse sequence. Such chemically gated graphene modulator can be potentially used in a harmonic transponder as a passive ubiquitous sensor node for chemical and bio sensing applications. Overall the research work presented in the dissertation will help enable cost and power-efficient wireless sensor networks in future healthcare IoTs.Electrical and Computer Engineerin

Analysis of the Performance of IoT Networks in Acoustic Environment by using LZW Data Compression Technique

The Internet of Things (IoT) has experienced phenomenal growth, opening up a wide range of applications in many settings. Due to the properties of sound propagation, IoT networks operating in acoustic environments in particular present special difficulties. Data compression techniques can be used to minimize overhead and maximize resource utilization in these networks to increase performance. The performance of IoT networks in acoustic environments is examined in this study, with a focus on routing overhead, throughput, and typical end-to-end delay. Lempel-Ziv-Welch (LZW) data compression is used to reduce data size and boost communication effectiveness. Three well-known protocols—MQTT, CoAP, and Machine-to-Machine (M2M)—are assessed in relation to acoustic Internet of Things networks. To mimic different acoustic conditions and collect performance metrics, a thorough experimental setup is used. Different network topologies, data speeds, and compression settings are used in the studies to determine how they affect the performance metrics. According to the analysis's findings, all three protocols' routing overhead is greatly decreased by the LZW data compression approach, which enhances network scalability and lowers energy usage. Additionally, the compressed data size has a positive impact on network throughput, allowing for effective data transmission in acoustic contexts with limited resources. Additionally, using LZW compression is seen to minimize the average end-to-end delay, improving real-time communication applications. This study advances knowledge of IoT networks operating in acoustic environments and the effects of data reduction methods on their functionality. The results offer useful information for network engineers and system designers to optimize the performance of IoT networks in similar situations. Additionally, a comparison of the MQTT, CoAP, and M2M protocols' suitability for acoustic IoT deployments is provided, assisting in the choice of protocol for particular application needs

Real-time signal detection and classification algorithms for body-centered systems

El principal motivo por el cual los sistemas de comunicación en el entrono corporal se desean con el objetivo de poder obtener y procesar señales biométricas para monitorizar e incluso tratar una condición médica sea ésta causada por una enfermedad o el rendimiento de un atleta. Dado que la base de estos sistemas está en la sensorización y el procesado, los algoritmos de procesado de señal son una parte fundamental de los mismos. Esta tesis se centra en los algoritmos de tratamiento de señales en tiempo real que se utilizan tanto para monitorizar los parámetros como para obtener la información que resulta relevante de las señales obtenidas. En la primera parte se introduce los tipos de señales y sensores en los sistemas en el entrono corporal. A continuación se desarrollan dos aplicaciones concretas de los sistemas en el entorno corporal así como los algoritmos que en las mismas se utilizan. La primera aplicación es el control de glucosa en sangre en pacientes con diabetes. En esta parte se desarrolla un método de detección mediante clasificación de patronones de medidas erróneas obtenidas con el monitor contínuo comercial "Minimed CGMS". La segunda aplicacióin consiste en la monitorizacióni de señales neuronales. Descubrimientos recientes en este campo han demostrado enormes posibilidades terapéuticas (por ejemplo, pacientes con parálisis total que son capaces de comunicarse con el entrono gracias a la monitorizacióin e interpretación de señales provenientes de sus neuronas) y también de entretenimiento. En este trabajo, se han desarrollado algoritmos de detección, clasificación y compresión de impulsos neuronales y dichos algoritmos han sido evaluados junto con técnicas de transmisión inalámbricas que posibiliten una monitorización sin cables. Por último, se dedica un capítulo a la transmisión inalámbrica de señales en los sistemas en el entorno corporal. En esta parte se estudia las condiciones del canal que presenta el entorno corporal para la transmisión de sTraver Sebastiá, L. (2012). Real-time signal detection and classification algorithms for body-centered systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/16188Palanci