Smart and sustainable public transport systems through improving level and quality of service

Buses are considered a slow, low comfort and low reliability transport system, thus its negative and por image. In the framework of the 3iBS project (2012), several examples of innovative and/or effective solutions regarding the Level of Service (LoS) were analysed aiming to provide operators, practitioners and policy makers with a set of Good Practice Guidelines to strengthen the competitiveness of the bus in the urban environment. The identification of the key indicators regarding vehicles, infrastructure and operation was possible through the analysis of a set of case studies -among which Barcelona (Spain), Cagliari (Italy), London (United Kingdom), Paris and Nantes (France). A cross comparison between the case studies was carried out for contrasting the level of achievement of the different criteria considered. The information provided on Regulatory, Financial and Technical issues allows the identification of a number of specific factors influencing the implementation of a high quality transport scheme, and set the basis for the elaboration of a set of Guidelines for the implementation of an intelligent, innovative and integrated bus system, including the main barriers to be tackled.

Time-of-use electricity tariffs with smart meters

This paper proposes a method for scheduling tariff time periods for electricity consumers. Europe will see a broader use of modern smart meters for electricity at residential consumers which must be used for enabling demand response. A heuristic-based method for tariff time period scheduling and pricing is proposed which considers different consumer groups with parameters studied a priori, taking advantage of demand response potential for each group and the fairness of electricity pricing for all consumers. This tool was applied to the case of Portugal, considering the actual network and generation costs, specific consumption profiles and overall electricity low voltage demand diagram. The proposed method achieves valid results. Its use will provide justification for the setting of tariff time periods by energy regulators, network operators and suppliers. It is also useful to estimate the consumer and electric sector benefits from changes in tariff time periods.

CLARK - Smart Clinic Assistant Robot for CGA

En esta presentación se exponen la arquitectura general y el estado actual de desarrollo del sistema CLARK. Dicho sistema tiene como objetivo el despliegue de un asistente robótico para ayudar a un médico en la realización de procedimientos CGA (Comprehensive Geriatric Assessment), de forma que ciertas tareas, tales como la realización de cuestionarios o pruebas de movimiento, puedan ser realizadas por el robot de forma paralela al resto del procedimiento CGA, aumentando así su eficiencia.

Enhancing smart environments with mobile robots

Sensor networks are becoming popular nowadays in the development of smart environments. Heavily relying on static sensor and actuators, though, such environments usually lacks of versatility regarding the provided services and interaction capabilities. Here we present a framework for smart environments where a service robot is included within the sensor network acting as a mobile sensor and/or actuator. Our framework integrates on-the-shelf technologies to ensure its adaptability to a variety of sensor technologies and robotic software. Two pilot cases are presented as evaluation of our proposal.

Computer Aided Design Algorithmic Technique for Very Large Scale Integrated Circuit Design and Smart Home Embedded System Design

To tackle the challenges at circuit level and system level VLSI and embedded system design, this dissertation proposes various novel algorithms to explore the efficient solutions. At the circuit level, a new reliability-driven minimum cost Steiner routing and layer assignment scheme is proposed, and the first transceiver insertion algorithmic framework for the optical interconnect is proposed. At the system level, a reliability-driven task scheduling scheme for multiprocessor real-time embedded systems, which optimizes system energy consumption under stochastic fault occurrences, is proposed. The embedded system design is also widely used in the smart home area for improving health, wellbeing and quality of life. The proposed scheduling scheme for multiprocessor embedded systems is hence extended to handle the energy consumption scheduling issues for smart homes. The extended scheme can arrange the household appliances for operation to minimize monetary expense of a customer based on the time-varying pricing model.

ADVANCED COMPUTATIONAL MODELING OF THE INTERNAL STRUCTURE OF SMART WIND-TURBINE BLADES

Implementation of stable aeroelastic models with the ability to capture the complex features of Multi concept smartblades is a prime step in reducing the uncertainties that come along with blade dynamics. The numerical simulations of fluid structure interaction can thus be used to test a realistic scenarios comprising of full-scale blades at a reasonably low computational cost. A code which was a combination of two advanced numerical models was designed and was run with the help of paralell HPC supercomputer platform. The first model was based on a variation of dimensional reduction technique proposed by Hodges and Yu. This model was the one to record the structural response of heterogenous composite blades. This technique reduces the geometrical complexities of the heterogenous blade section into a stiffness matrix for an equivalent beam. This derived equivalent 1-D strain energy matrix is similar to the actual 3-D strain energy matrix in an asymptotic sense. As this 1-D matrix helps in accurately modeling the blade structure as a 1-D finite element problem, this substantially redues the computational effort and subsequently the computational cost that are required to model the structural dynamics at each step. Second model comprises of implementation of the Blade Element Momentum Theory. In this approach we map all the velocities and the forces with the help of orthogonal matrices that help in capturing the large deformations and the effects of rotations in calculating the aerodynamic forces. This ultimately helps us to take into account the complex flexo torsional deformations. In this thesis we have succesfully tested these computayinal tools developed by MTU’s research team lead by for the aero elastic analysis of wind-turbine blades. The validation in this thesis is majorly based on several experiments done on NREL-5MW blade, as this is widely accepted as a benchmark blade in the wind industry. Along with the use of this innovative model the internal blade structure was also changed to add up to the existing benefits of the already advanced numerical models.

STUDIES OF FUNCTIONALIZED NANOPARTICLES FOR SMART SELF-ASSEMBLY AND AS CONTROLLED DRUG DELIVERY

This dissertation is related to the studies of functionalized nanoparticles for self-assembly and as controlled drug delivery system. The whole topic is composed of two parts. In the first part, the research was conducted to design and synthesize a new type of ionic peptide-functionalized copolymer conjugates for self-assembly into nanoparticle fibers and 3D scaffolds with the ability of multi-drug loading and governing the release rate of each drug for tissue engineering. The self-assembly study confirmed that such peptide-functionalized amphiphilic copolymers underwent different self-assembly behavior. The bigger nanoparticles were more easily assembled into nanoparticle fibers and 3D scaffolds with larger pore size, while the smaller nanoparticle underwent faster self-assembly to form more compact 3D scaffolds with smaller porosity but more stable structure. Controlled release studies confirmed the ability of governing simultaneous release of different model drugs with independent release rate from a same scaffold. Cytotoxicity tests showed that all synthesized peptides, copolymers and peptide-copolymer conjugates were biocompatible with SW-620 cell lines and NIH3T3 cell lines. This new type of self-assembled scaffolds combined the advantages of peptide nanofibers and versatile controlled release of polymeric nanoparticles to achieve simultaneous multi-drug loading and controlled release of each drug, uniform distribution and flexibility of hydrogel scaffolds. The investigations in second part were first to design and synthesize organic biocide-loaded nanoparticles for low-leaching wood preservation using a cost-effective one-pot method to synthesize amphiphilic chitosan-g-PMMA nanoparticles loading with ~25-28 wt.% of the fungicide tebuconazole with particle size of ~100 nm diameter by FESEM. FESEM analysis confirmed efficient penetration of nanoparticles throughout the treated wooden stake with dimension of 19 × 19 × 455 mm^3. Leaching studies showed that biocide introduced into sapwood via nanoparticles leached only ~9% compared with the amount leached from tebuconazole solution-treated control, while soil jar tests showed that the nanoparticle-treated wood blocks were effectively protected from biological decay tested against G. trabeum, a brown rot fungus. Copper oxide nanoparticles with and without polymer stabilizers were also investigated to use as inorganic wood preservatives to clarify the factor affecting copper leaching from treated wood. Copper oxide nanoparticles with uniform diameters of ~10 nm and ~50 nm were prepared, and the leachates from southern pine sapwood treated with these nanoparticles were analyzed. It was found by TEM and EDS analysis that significant numbers of nanoparticles leached from the treated wood. The 50 nm nanoparticles leached slightly less than a soluble copper salt control, but 10 nm nanoparticles leached substantially more than the control. The effect of polymer stabilizers on nanoparticle leaching was also investigated. Results showed that polymer stabilizers increased leaching. The trends showed that nanoparticle size was a major factor in copper leaching.

A Collaborative Mobile Crowdsensing System for Smart Cities

Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.

Sistema di navigazione aumentata per Smart Glasses

Questa tesi si pone come obiettivo di arricchire l’applicazione per dispositivi Android creata da OpenTripPlanner, aggiungendo funzionalità di navigazione aumentata, rendendola utilizzabile da Smart Glasses. L’utente sarà guidato a passo a passo nel percorso grazie a informazioni visive e uditive sulle direzioni da prendere. L’applicazione può essere personalizzata per l’utente che la sta utilizzando grazie alla possibilità di inserire le proprie generalità e informazioni, utili per calcolare le calorie bruciate dall’utente durante il tragitto. All’applicazione l’utente può anche connettere, tramite Bluetooth, un mi band. In questo modo, una volta raggiunta la destinazione prescelta l’utente può avere informazioni sul numero di passi effettuati durante il tragitto e le calorie bruciate.

Development and Verification of Control and Protection Strategies in Hybrid AC/DC Power Systems for Smart Grid Applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Designing intrinsically photostable low band gap polymers:a smart tool combining EPR spectroscopy and DFT calculations

A rapid and efficient method to identify the weak points of the complex chemical structure of low band gap (LBG) polymers, designed for efficient solar cells, when submitted to light exposure is reported. This tool combines Electron Paramagnetic Resonance (EPR) using the 'spin trapping method' coupled with density functional theory modelling (DFT). First, the nature of the short life-time radicals formed during the early-stages of photo-degradation processes are determined by a spin-trapping technique. Two kinds of short life-time radical (R and R′O) are formed after 'short-duration' illumination in an inert atmosphere and in ambient air, respectively. Second, simulation allows the identification of the chemical structures of these radicals revealing the most probable photochemical process, namely homolytical scission between the Si atom of the conjugated skeleton and its pendent side-chains. Finally, DFT calculations confirm the homolytical cleavage observed by EPR, as well as the presence of a group that is highly susceptible to photooxidative attack. Therefore, the synergetic coupling of a spin trapping method with DFT calculations is shown to be a rapid and efficient method for providing unprecedented information on photochemical mechanisms. This approach will allow the design of LBG polymers without the need to trial the material within actual solar cell devices, an often long and costly screening procedure.

Do intelligent heating controls out-smart ordinary users?

Nearly a third of UK gas and electricity is used in homes, of which 80% is for space heating and hot water provision. Rising consumer bills, concerns about climate change and the surge in personal digital technology use has provoked the development of intelligent domestic heating controls. Whilst the need for having suitable control of the home heating system is essential for reducing domestic energy use, these heating controls rely on appropriate user interaction to achieve a saving and it is unclear whether these ‘smart’ heating controls enhance the use of domestic heating or reduce energy demand. This paper describes qualitative research undertaken with a small sample of UK householders to understand how people use new heating controls installed in their homes and what the requirements are for improved smart heating control design. The paper identifies, against Nielsen’s usability heuristics, the divergence between the householder’s use, understanding and expectations of the heating system and the actual design of the system. Digital and smart heating control systems should be designed to maximise usability so that they can be effectively used for efficient heating control by all users. The research highlights the need for development of new systems to readdress the needs of users and redefine the system requirements.

Matching theory based travel plan aware charging algorithms in V2G smart grid networks

The frequency, time and places of charging have large impact on the Quality of Experience (QoE) of EV drivers. It is critical to design effective EV charging scheduling system to improve the QoE of EV drivers. In order to improve EV charging QoE and utilization of CSs, we develop an innovative travel plan aware charging scheduling scheme for moving EVs to be charged at Charging Stations (CS). In the design of the proposed charging scheduling scheme for moving EVs, the travel routes of EVs and the utility of CSs are taken into consideration. The assignment of EVs to CSs is modeled as a two-sided many-to-one matching game with the objective of maximizing the system utility which reflects the satisfactory degrees of EVs and the profits of CSs. A Stable Matching Algorithm (SMA) is proposed to seek stable matching between charging EVs and CSs. Furthermore, an improved Learning based On-LiNe scheduling Algorithm (LONA) is proposed to be executed by each CS in a distributed manner. The performance gain of the average system utility by the SMA is up to 38.2% comparing to the Random Charging Scheduling (RCS) algorithm, and 4.67% comparing to Only utility of Electric Vehicle Concerned (OEVC) scheme. The effectiveness of the proposed SMA and LONA is also demonstrated by simulations in terms of the satisfactory ratio of charging EVs and the the convergence speed of iteration.

Effectively positioning water loss event in smart water networks

With the eye-catching advances in sensing technologies, smart water networks have been attracting immense research interest in recent years. One of the most overarching tasks in smart water network management is the reduction of water loss (such as leaks and bursts in a pipe network). In this paper, we propose an efficient scheme to position water loss event based on water network topology. The state-of-the-art approach to this problem, however, utilizes the limited topology information of the water network, that is, only one single shortest path between two sensor locations. Consequently, the accuracy of positioning water loss events is still less desirable. To resolve this problem, our scheme consists of two key ingredients: First, we design a novel graph topology-based measure, which can recursively quantify the "average distances" for all pairs of senor locations simultaneously in a water network. This measure will substantially improve the accuracy of our positioning strategy, by capturing the entire water network topology information between every two sensor locations, yet without any sacrifice of computational efficiency. Then, we devise an efficient search algorithm that combines the "average distances" with the difference in the arrival times of the pressure variations detected at sensor locations. The viable experimental evaluations on real-world test bed (WaterWiSe@SG) demonstrate that our proposed positioning scheme can identify water loss event more accurately than the best-known competitor.

The Impact of Regulation on a Firm's Incentives to Invest in Emergent Smart Grid Technologies

This paper analyzes the implementation of new technologies in network industries through the development of a suitable regulatory scheme. The analysis focuses on Smart Grid (SG) technologies which, among others benefits, could save operational costs and reduce the need for further conventional investments in the grid. In spite of the benefits that may result from their implementation, the adoption of SGs by network operators can be hampered by the uncertainties surrounding actual performances. A decision model has been developed to assess the firms' incentives to invest in "smart" technologies under different regulatory schemes. The model also enables testing the impact of uncertainties on the reduction of operational costs, and of conventional investments. Under certain circumstances, it may be justified to support the development and early deployment of emerging innovations that have a high potential to ameliorate the efficiency of the electricity system, but whose adoption faces many uncertainties.