Optimising market share and profit margin:SMDP-based tariff pricing under the smart grid paradigm

Smart grid technologies have given rise to a liberalised and decentralised electricity market, enabling energy providers and retailers to have a better understanding of the demand side and its response to pricing signals. This paper puts forward a reinforcement-learning-powered tool aiding an electricity retailer to define the tariff prices it offers, in a bid to optimise its retail strategy. In a competitive market, an energy retailer aims to simultaneously increase the number of contracted customers and its profit margin. We have abstracted the problem of deciding on a tariff price as faced by a retailer, as a semi-Markov decision problem (SMDP). A hierarchical reinforcement learning approach, MaxQ value function decomposition, is applied to solve the SMDP through interactions with the market. To evaluate our trading strategy, we developed a retailer agent (termed AstonTAC) that uses the proposed SMDP framework to act in an open multi-agent simulation environment, the Power Trading Agent Competition (Power TAC). An evaluation and analysis of the 2013 Power TAC finals show that AstonTAC successfully selects sell prices that attract as many customers as necessary to maximise the profit margin. Moreover, during the competition, AstonTAC was the only retailer agent performing well across all retail market settings.

Public libraries and the right to the [smart] city

The future of public libraries has been threatened by funding cuts and new digital technologies which have led many people to question their traditional role and purpose. However, freedom of information, ready access to knowledge and information literacy in all its digital and analog guises are more important than ever. Thus, public libraries remain significant spaces and places where people can socially interact and learn. In many countries public libraries are reinventing themselves and part of this process has been the redesign of library services and the design and construction of new library building and facilities that articulate the values, purpose and role of what has been termed 'the next library'. Following discussion of new library developments in London, Birmingham and Worcester in the UK, Aarhus in Denmark and Helsinki in Finland, the article concludes that public libraries are now both social and media spaces as well as being important physical places that can help city dwellers decide what type of urban world they want to see.

A smart micro-drill for cochleostomy formation:a comparison of cochlear disturbances with manual drilling and a human trial

Background: Cochleostomy formation is a key stage of the cochlear implantation procedure. Minimizing the trauma sustained by the cochlea during this step is thought to be a critical feature in hearing preservation cochlear implantation. The aim of this paper is firstly, to assess the cochlea disturbances during manual and robotic cochleostomy formation. Secondly, to determine whether the use of a smart micro-drill is feasible during human cochlear implantation. Materials and methods: The disturbances within the cochlea during cochleostomy formation were analysed in a porcine specimen by creating a third window cochleostomy, preserving the underlying endosteal membrane, on the anterior aspect of the basal turn of the cochlea. A laser vibrometer was aimed at this third window, to assess its movement while a traditional cochleostomy was performed. Six cochleostomies were performed in total, three manually and three with a smart micro-drill. The mean and peak membrane movement was calculated for both manual and smart micro-drill arms, to represent the disturbances sustained within cochlea during cochleostomy formation. The smart micro-drill was further used to perform live human robotic cochleostomies on three adult patients who met the National Institute of Health and Clinical Excellence criteria for undergoing cochlear implantation. Results: In the porcine trial, the smart micro-drill preserved the endosteal membrane in all three cases. The velocity of movement of the endosteal membrane during manual cochleostomy is approximately 20 times higher on average and 100 times greater in peak velocity, than for robotic cochleostomy. The robot was safely utilized in theatre in all three cases and successfully created a bony cochleostomy while preserving the underlying endosteal membrane. Conclusions: Our experiments have revealed that controlling the force of drilling during cochleostomy formation and opening the endosteal membrane with a pick will minimize the trauma sustained by the cochlea by a factor of 20. Additionally, the smart micro-drill can safely perform a bony cochleostomy in humans under operative conditions and preserve the integrity of the underlying endosteal membrane. © W. S. Maney & Son Ltd 2013.

Static, dynamic, and adaptive heterogeneity in distributed smart camera networks

We study heterogeneity among nodes in self-organizing smart camera networks, which use strategies based on social and economic knowledge to target communication activity efficiently. We compare homogeneous configurations, when cameras use the same strategy, with heterogeneous configurations, when cameras use different strategies. Our first contribution is to establish that static heterogeneity leads to new outcomes that are more efficient than those possible with homogeneity. Next, two forms of dynamic heterogeneity are investigated: nonadaptive mixed strategies and adaptive strategies, which learn online. Our second contribution is to show that mixed strategies offer Pareto efficiency consistently comparable with the most efficient static heterogeneous configurations. Since the particular configuration required for high Pareto efficiency in a scenario will not be known in advance, our third contribution is to show how decentralized online learning can lead to more efficient outcomes than the homogeneous case. In some cases, outcomes from online learning were more efficient than all other evaluated configuration types. Our fourth contribution is to show that online learning typically leads to outcomes more evenly spread over the objective space. Our results provide insight into the relationship between static, dynamic, and adaptive heterogeneity, suggesting that all have a key role in achieving efficient self-organization.

Participatory research with older adults with AMD:co-designing a SMART diet diary app

The global population of people aged 60 years and older is growing rapidly. In the UK, there are currently around 10 million people aged 65 and over, and the number is projected to rise by 50% in the next 20 years (RNIB, 2013). While ongoing advances in information technology (IT) are undoubtedly increasing the scope for IT to enhance and support older adults' daily living, the digital divide between older and younger adults - 43% of people below the age of 55 own and use a smartphone, compared to only 3% of people aged 65 and over (AgeUK, 2013) - raises concerns about the suitability of technological solutions for older adults, especially for older adults with impairments. Evidence suggests that sympathetic design of mobile technology does render it useful and acceptable to older adults: the key issue is, however, how best to achieve such sympathetic design when working with impaired older adults. We report here on a case study in order to outline the practicalities and highlight the benefits of participatory research for the design of sympathetic technology for (and importantly with) older adults with impairments.

Enhanced connectivity and QoE through LTE-WiFi interworking in Smart Cities

Mobile communication and networking infrastructures play an important role in the development of smart cities, to support real-time information exchange and management required in modern urbanization. Mobile WiFi devices that help offloading data traffic from the macro-cell base station and serve the end users within a closer range can significantly improve the connectivity of wireless communications between essential components including infrastructural and human devices in a city. However, this offloading function through interworking between LTE and WiFi systems will change the pattern of resource distributions operated by the base station. In this paper, a resource allocation scheme is proposed to ensure stable service coverage and end-user quality of experience (QoE) when offloading takes place in a macro-cell environment. In this scheme, a rate redistribution algorithm is derived to form a parametric scheduler to meet the required levels of efficiency and fairness, guided by a no-reference quality assessment metric. We show that the performance of resource allocation can be regulated by this scheduler without affecting the service coverage offered by the WLAN access point. The performances of different interworking scenarios and macro-cell scheduling policies are also compared.

Co-designing a SMART diet diary application with older adults with AMD

The global population of people aged 60 years and older is growing rapidly. In the UK, there are currently around 10 million people aged 65 and over, and the number is projected to rise by 50% in the next 20 years (RNIB, 2013). While ongoing advances in information technology (IT) are undoubtedly increasing the scope for IT to enhance and support older adults’ daily living, the digital divide between older and younger adults – 43% of people below the age of 55 own and use a smartphone, compared to only 3% of people aged 65 and over (AgeUK, 2013) – raises concerns about the suitability of technological solutions for older adults, especially for older adults with impairments. Evidence suggests that sympathetic design of mobile technology does render it useful and acceptable to older adults: the key issue is, however, how best to achieve such sympathetic design when working with impaired older adults. We report here on a case study in order to outline the practicalities and highlight the benefits of participatory research for the design of sympathetic technology for (and importantly with) older adults with impairments.

Sensing information modelling for smart city

Sensing technology is a key enabler of the Internet of Things (IoT) and could produce huge volume data to contribute the Big Data paradigm. Modelling of sensing information is an important and challenging topic, which influences essentially the quality of smart city systems. In this paper, the author discusses the relevant technologies and information modelling in the context of smart city and especially reports the investigation of how to model sensing and location information in order to support smart city development.

A smart surgical robotic for cochlear implantation

In this paper a surgical robotic device for cochlear implantation surgery is described that is able to discriminate tissue interfaces and other controlling parameters ahead of a drill tip. The advantage in surgery is that tissues at interfaces can be preserved. The smart tool is able to control interaction with respect to the flexing tissue to avoid penetration control the extent of protrusion with respect to the real-time position of the tissue. To interpret drilling conditions, and conditions leading up to breakthrough at a tissue interface, the sensing scheme used enables discrimination between the variety of conditions posed in the drilling environment. The result is a robust fully autonomous system able to respond to tissue type, behaviour and deflection in real-time. The paper describes the robotic tool that has been designed to be used in the surgical environment where it has been used in the operating room.

Discriminating ambulation using a smart sensing plate

The automated sensing scheme described in this paper has the potential to automatically capture, discriminate and classify transients in gait. The mechanical simplicity of the walking platform offers advantages over standard force plates. There is less restriction on dimensions offering the opportunity for multi-contact and multiple steps. This addresses the challenge of patient targeting and the evaluation of patients in a variety of ambulatory applications. In this work the sensitivity of the distributive tactile sensing method has been investigated experimentally. Using coupled time series data from a small number of sensors, gait patterns are compared with stored templates using a pattern recognition algorithm. By using a neural network these patterns were interpreted classifying normal and affected walking events with an accuracy of just under 90%. This system has potential in gait analysis and rehabilitation as a tool for early diagnosis in walking disorders, for determining response to therapy and for identifying changes between pre and post operative gait. Copyright © 2009 by ASME.

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.