Smart Grid for the Smart City

Modern cities are embracing cutting-edge technologies to improve the services they offer to the citizens from traffic control to the reduction of greenhouse gases and energy provisioning. In this chapter, we look at the energy sector advocating how Information and Communication Technologies (ICT) and signal processing techniques can be integrated into next generation power grids for an increased effectiveness in terms of: electrical stability, distribution, improved communication security, energy production, and utilization. In particular, we deliberate about the use of these techniques within new demand response paradigms, where communities of prosumers (e.g., households, generating part of their electricity consumption) contribute to the satisfaction of the energy demand through load balancing and peak shaving. Our discussion also covers the use of big data analytics for demand response and serious games as a tool to promote energy-efficient behaviors from end users

Helmholtz Portfolio Theme Large-Scale Data Management and Analysis (LSDMA)

The Helmholtz Association funded the "Large-Scale Data Management and Analysis" portfolio theme from 2012-2016. Four Helmholtz centres, six universities and another research institution in Germany joined to enable data-intensive science by optimising data life cycles in selected scientific communities. In our Data Life cycle Labs, data experts performed joint R&D together with scientific communities. The Data Services Integration Team focused on generic solutions applied by several communities

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

A Survey on Distributed Fibre Optic Sensor Data Modelling Techniques and Machine Learning Algorithms for Multiphase Fluid Flow Estimation

Real-time monitoring of multiphase fluid flows with distributed fibre optic sensing has the potential to play a major role in industrial flow measurement applications. One such application is the optimization of hydrocarbon production to maximize short-term income, and prolong the operational lifetime of production wells and the reservoir. While the measurement technology itself is well understood and developed, a key remaining challenge is the establishment of robust data analysis tools that are capable of providing real-time conversion of enormous data quantities into actionable process indicators. This paper provides a comprehensive technical review of the data analysis techniques for distributed fibre optic technologies, with a particular focus on characterizing fluid flow in pipes. The review encompasses classical methods, such as the speed of sound estimation and Joule-Thomson coefficient, as well as their data-driven machine learning counterparts, such as Convolutional Neural Network (CNN), Support Vector Machine (SVM), and Ensemble Kalman Filter (EnKF) algorithms. The study aims to help end-users establish reliable, robust, and accurate solutions that can be deployed in a timely and effective way, and pave the wave for future developments in the field.publishedVersio

Automated Attendance System using Active RFID

The main focus ofthis project is to enhance the integrity and the authenticity ofdata, whereby, conventional system couldn't ensure the safety of the data. As the result, many employees neglect the importance of attitude in working environment. This project offers a safety towards the data, and in the same time helping in monitoring the movement of employees. Given a number of time, this project will undergo several phases which are planning, analysis, design and implementation. Lastly, the success ofthis project will be determined, and a conclusion should be made based on the result obtained, whether the objective has been met or not