Planning and Deployment of Wireless Sensor Networks

Editorial introduction to special issue on Planning and Deployment of Wireless Sensor Networks published in the International Journal of Distributed Sensor Networks, 9(5). 2014

Markov Decision Processes with Applications in Wireless Sensor Networks: A Survey

Wireless sensor networks (WSNs) consist of autonomous and resource-limited devices. The devices cooperate to monitor one or more physical phenomena within an area of interest. WSNs operate as stochastic systems because of randomness in the monitored environments. For long service time and low maintenance cost, WSNs require adaptive and robust methods to address data exchange, topology formulation, resource and power optimization, sensing coverage and object detection, and security challenges. In these problems, sensor nodes are to make optimized decisions from a set of accessible strategies to achieve design goals. This survey reviews numerous applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs. Furthermore, various solution methods are discussed and compared to serve as a guide for using MDPs in WSNs

Subsea inspection and monitoring challenges

Master's thesis in Offshore technology : industrial asset managementThis paper uncovers and suggests solutions for the challenges to control change over time more reliable and cost effective. Front-end concept engineering, design, inspection and monitoring strategies, technologies, systems and methods for Life-of-Field are recommended. Autonomous underwater vehicles (AUV) are identified as a possible cost- efficient opportunity to reduce cost of inspections and monitoring operations while safeguarding asset integrity. A recognized design spiral methodology is used to perform a front-end concept evaluation of an AUV system. Investigation of key technological limitations and new developments within underwater communication, energy storage and wireless power transmission is performed. It further enables opportunities such as AUV recharging station on the seafloor for better utilization. One major learning point is through the use of numerical models and the outcome being a better and more hydro effective hull design. One expectation from this paper may be the aid to collaborating partners in their design work

A Novel Non-Enzymatic Glucose Biofuel Cell with Mobile Glucose Sensing

Herein, we report a novel non-enzymatic glucose biofuel cell with mobile glucose sensing. We characterized the power generation and biosensing capabilities in presence of glucose analyte. This system was developed using a non-enzymatic glucose biofuel cell consisting of colloidal platinum coated gold microwire (Au-co-Pt) employed as an anode and the cathode which was constructed using a Gas diffusion electrode (GDE) with a platinum catalyst. The non-enzymatic glucose biofuel cell produced a maximum open circuit voltage of 0.54 V and delivered and a maximum short circuit current density of 1.6 mA/cm2 with a peak power density of 0.226 mW/cm2 at a concentration of 1 M glucose. The non-enzymatic glucose biofuel cell produced an open circuit voltage of 0.38 V and delivered and a short circuit current density of 0.225 mA/cm2 with a peak power density of 0.022 mW/cm 2 at a concentration of 5 mM glucose. These findings showed that glucose biofuel cells can be further investigated in the development of a self-powered glucose biosensor. When used as self-powered glucose sensor, the system showed a good sensitivity of 0.616 μA mM−1 and linear dependence with a correlation coefficient of 0.995 in the glucose concentration range of 2 mM to 50 mM. The system was further characterized by testing the performance of the system at various temperature, pH and amidst various interfering and competing chemical species such as uric acid, ascorbic acid, fructose, maltose and galactose. A charge pump circuit consisting of a blinking LED was connected to the biofuel cell to amplify the input voltage to power small electronic devices. The blinking frequency of the LED corresponds to the glucose concentration. An android mobile phone camera application was used to measure this LED blinking frequency which was in turn converted into the glucose concentration readings using image processing in MATLAB. The user was notified via text message and an email

A Preventive Medicine Framework for Wearable Abiotic Glucose Detection System

In this work, we present a novel abiotic glucose fuel cell with battery-less remote access. In the presence of a glucose analyte, we characterized the power generation and biosensing capabilities. This system is developed on a flexible substrate in bacterial nanocellulose with gold nanoparticles used as a conductive ink for piezoelectric deposition based printing. The abiotic glucose fuel cell is constructed using colloidal platinum on gold (Au-co-Pt) and a composite of silver oxide nanoparticles and carbon nanotubes as the anodic and cathodic materials. At a concentration of 20 mM glucose, the glucose fuel cell produced a maximum open circuit voltage of 0.57 V and supplied a maximum short circuit current density of 0.581 mA/cm2 with a peak power density of 0.087 mW/cm2 . The system was characterized by testing its performance using electrochemical techniques like linear sweep voltammetry, cyclic voltammetry, chronoamperometry in the presence of various glucose level at the physiological temperatures. An open circuit voltage (Voc) of 0.43 V, short circuit current density (Isc) of 0.405 mA/cm2 , and maximum power density (Pmax) of 0.055 mW/cm2 at 0.23 V were achieved in the presence of 5 mM physiologic glucose. The results indicate that glucose fuel cells can be employed for the development of a self-powered glucose sensor. The glucose monitoring device demonstrated sensitivity of 1.87 uA/mMcm2 and a linear dynamic range of 1 mM to 45 mM with a correlation coefficient of 0.989 when utilized as a self-powered glucose sensor. For wireless communication, the incoming voltage from the abiotic fuel cell was fed to a low power microcontroller that enables battery less communication using NFC technology. The voltage translates to the NFC module as the digital signals, which are displayed on a custom-built android application. The digital signals are converted to respective glucose concentration using a correlation algorithm that allows data to be processed and recorded for further analysis. The android application is designed to record the time, date stamp, and other independent features (e.g. age, height, weight) with the glucose measurement to allow the end-user to keep track of their glucose levels regularly. Analytics based on in-vitro testing were conducted to build a machine learning model that enables future glucose prediction for 15, 30 or 60 minutes

Portable Bio-Devices: Design of Electrochemical Instruments from Miniaturized to Implantable Devices

The integration of biosensors and electronic technologies allows the development of biomedical systems able to diagnose and monitoring pathologies by detecting specific biomarkers. The chapter presents the main modules involved in the development of such devices, generically represented in Fig. 1, and focuses its attention on the essential components of these systems to address questions such as: how is the device powered? How does it communicate the measured data? What kind of sensors could be used?, and What kinds of electronics are used