804 resultados para Smart appliance
Resumo:
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.
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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.
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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.
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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.
Resumo:
The concept of SG (Smart Grids) encompasses a set of technologies that raise the intelligence of the electrical networks, such as smart meters or instruments of communication, sensing and auto-correction of networks. Nevertheless, the cost is still an important obstacle for the transformation of the current electricity system into a smarter one. Regulation can have an important role in setting up a favorable framework that fosters investments. However, the novelty with SG is the disembodied character of the technology, which may change the incentives of the regulated network companies to invest, affecting the effectiveness of the regulatory instruments (“cost plus” or “price cap”). This paper demonstrates that the solution to this “Smart” paradox requires strong incentive regulation mechanisms able to stimulate the adoption of SG technologies. Moreover, the regulation should not jeopardize conventional investments that are unable to be substituted by SG. Thus, a combination of performance regulation and efficiency obligations may be necessary.
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Objectives: To discuss how current research in the area of smart homes and ambient assisted living will be influenced by the use of big data. Methods: A scoping review of literature published in scientific journals and conference proceedings was performed, focusing on smart homes, ambient assisted living and big data over the years 2011-2014. Results: The health and social care market has lagged behind other markets when it comes to the introduction of innovative IT solutions and the market faces a number of challenges as the use of big data will increase. First, there is a need for a sustainable and trustful information chain where the needed information can be transferred from all producers to all consumers in a structured way. Second, there is a need for big data strategies and policies to manage the new situation where information is handled and transferred independently of the place of the expertise. Finally, there is a possibility to develop new and innovative business models for a market that supports cloud computing, social media, crowdsourcing etc. Conclusions: The interdisciplinary area of big data, smart homes and ambient assisted living is no longer only of interest for IT developers, it is also of interest for decision makers as customers make more informed choices among today's services. In the future it will be of importance to make information usable for managers and improve decision making, tailor smart home services based on big data, develop new business models, increase competition and identify policies to ensure privacy, security and liability.
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In this paper, a smart wireless wristband is proposed. The potential of innovative gesture based interactivity with connected lighting solutions is reviewed. The solution is intended to offer numerous benefits, in terms of ease of use, and enhanced dynamic interactive functionality. A comparative analysis will be carried out between this work and existing solutions. The evolution of lighting and gesture controls will be discussed and an overview of alternative applications will be provided, as part of the critical analysis.
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This paper presents a development of a semi-active prosthetic knee, which can work in both active and passive modes based on the energy required during the gait cycle of various activities of daily livings (ADLs). The prosthetic limb is equipped with various sensors to measure the kinematic and kinetic parameters of both prosthetic limbs. This prosthetic knee is designed to be back-drivable in passive mode to provide a potential use in energy regeneration when there negative energy across the knee joint. Preliminary test has been performed on transfemoral amputee in passive mode to provide some insight to the amputee/prosthesis interaction and performance with the designed prosthetic knee.
Resumo:
Ever since the birth of the Smart City paradigm, a wide variety of initiatives have sprung up involving this phenomenon: best practices, projects, pilot projects, transformation plans, models, standards, indicators, measuring systems, etc. The question to ask, applicable to any government official, city planner or researcher, is whether this effect is being felt in how cities are transforming, or whether, in contrast, it is not very realistic to speak of cities imbued with this level of intelligence. Many cities are eager to define themselves as smart, but the variety, complexity and scope of the projects needed for this transformation indicate that the change process is longer than it seems. If our goal is to carry out a comparative analysis of this progress among cities by using the number of projects executed and their scope as a reference for the transformation, we could find such a task inconsequential due to the huge differences and characteristics that define a city. We believe that the subject needs simplification (simpler, more practical models) and a new approach. This paper presents a detailed analysis of the smart city transformation process in Spain and provides a support model that helps us understand the changes and the speed at which they are being implemented. To this end we define a set of elements of change called "transformation factors" that group a city's smartness into one of three levels (Low/Medium/Fully) and more homogeneously identify the level of advancement of this process. © 2016 IEEE.
Resumo:
Syftet med rapporten är att utgöra underlag för Dalarnas strategi för smart specialisering inom energiområdet, vilken görs enligt den europeiska modellen framarbetad av Sevilla-plattformen; Regional Forsknings- och Innovationsstrategi (RIS3). Rapporten motsvarar enligt denna modell steg 5 i processen. Rapporten ger svar på om kunskapsområdet Energieffektivt samhällsbyggande kan kvalificera sig för att vara ett prioriterat område för smart specialisering i Dalarna och lämnar förslag på hur en öppen innovationsarena inom kunskapsområdet kan organiseras. Förslag lämnas på roller och funktioner för respektive organisation inom innovationssystemet, däribland Högskolan. EUs strategi för tillväxt och jobb ”EU 2020 – Smart och hållbar tillväxt för alla” kopplar samman tillväxt och lösningen av samhällsutmaningar. I strategin ingår att styra alla befintliga verktyg i strategins riktning, vilket innebär skärpta krav på att jobba enligt strategin om man vill komma åt stöd från olika finansiella program. EUs flaggskepp ”Innovationsunionen” framhåller att konkurrenskraft och tillväxt är beroende av innovation inom produkter, tjänster, handel och samhällsmässiga processer och modeller. För att lyckas med detta behöver varje europeisk region analysera och fokusera på sina starkaste områden. EUs program för forskning och innovation Horizon 2020 ställer krav på nyttiggörande av forskning och samverkan med omgivande samhälle, varför ökad företagssamverkan behövs. Dalarnas satsning på smart specialisering inom området Energieffektivt samhällsbyggande stöds av såväl nationella som regionala innovationsstrategin, Dalarnas regionala utvecklingsstrategi, Norra Mellansveriges strukturfondsprogram, m fl programskrivningar. Kunskapsområdet energieffektivt samhällsbyggande spänner över ett brett område där allt från energiproduktion och energiöverföring till energins användning ingår. Ordet samhälle i namnet för kunskapsområdet markerar att det omfattar mer än byggande av hus. Det är energieffektiviteten som är den samlande faktorn. En vision för kunskapsområdet finns redan beslutad i Dalarnas energi- och klimatstrategi. Analysen av spetskompetens visar att det finns förutsättningar att hävda eller utveckla excellens och nå tillväxt inom flera områden inom energieffektivt samhällsbyggande, däribland elöverföring, smarta elnät, energisystem, solenergi, energieffektivt byggande och IT-transportlösningar. Dock saknas i flera fall dokumentation av hur olika verksamheter och spetskompetenser befinner sig i jämförelse med andra. Baserat på analysen konstateras att Energieffektivt samhällsbyggande kvalificerar sig för att vara ett prioriterat område för smart specialisering i Dalarna. I rapporten kartläggs och beskrivs alla aktörer inom kunskapsområdet. Tillsammans täcker de in de flesta delar av energiomställningen och innovationssystemet, uppbackat av ett starkt regionalt ledarskap och Dalarna som Pilotlän för grön utveckling. En ingående funktionsanalys av innovationssystemet inom kunskapsområdet identifierar några brister som föreslås lösas. Förslag lämnas på alla berörda aktörers roller och funktioner i innovationssystemet, där klustren förväntas ta en nyckelroll i att generera idéflöden och implementera innovationer. Högskolan Dalarna ges en central roll i specialiseringen inom energiområdet och föreslås inneha både ett energikompetenscentrum och ett innovationscenter. En öppen innovationsarena kan skapas av de tre FoI-miljöerna byggande, smarta elnät och IT i transportsektorn. Rapporten föreslår innovationsarenans arbetssätt och verksamhet.
Resumo:
I-SMART is an Internet-based client management system that allows the State of Iowa and its licensed substance abuse treatment providers to administer, manage and provide cost efficient and quality substance abuse assessment and treatment services. Implementation of the I-SMART System is a key product in meeting the federal government requirements for National Outcome Monitoring System (NOMS).
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This paper presents a methodology to forecast the hourly and daily consumption in households. The methodology was validated for households in Lisbon region, Portugal. The paper shows that the forecast tool allows obtaining satisfactory results for forecasting. Models of demand response allow the support of consumer’s decision in exchange for an economic benefit by the redefinition of load profile or changing the appliance consumption period. It is also in the interest of electric utilities to take advantage of these changes, particularly when consumers have an action on the demand-side management or production. Producers need to understand the load profile of households that are connected to a smart grid, to promote a better use of energy, as well as optimize the use of micro-generation from renewable sources, not only to delivering to the network but also in self-consumption.
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This paper proposes a process for the classifi cation of new residential electricity customers. The current state of the art is extended by using a combination of smart metering and survey data and by using model-based feature selection for the classifi cation task. Firstly, the normalized representative consumption profi les of the population are derived through the clustering of data from households. Secondly, new customers are classifi ed using survey data and a limited amount of smart metering data. Thirdly, regression analysis and model-based feature selection results explain the importance of the variables and which are the drivers of diff erent consumption profi les, enabling the extraction of appropriate models. The results of a case study show that the use of survey data signi ficantly increases accuracy of the classifi cation task (up to 20%). Considering four consumption groups, more than half of the customers are correctly classifi ed with only one week of metering data, with more weeks the accuracy is signifi cantly improved. The use of model-based feature selection resulted in the use of a signifi cantly lower number of features allowing an easy interpretation of the derived models.