Modelling busway station dwell time using smart cards

Dwell time at the busway station has a significant effect on bus capacity and delay. Dwell time has conventionally been estimated using models developed on the basis of field survey data. However field survey is resource and cost intensive, so dwell time estimation based on limited observations can be somewhat inaccurate. Most public transport systems are now equipped with Automatic Passenger Count (APC) and/or Automatic Fare Collection (AFC) systems. AFC in particular reduces on-board ticketing time, driver’s work load and ultimately reduces bus dwell time. AFC systems can record all passenger transactions providing transit agencies with access to vast quantities of data. AFC data provides transaction timestamps, however this information differs from dwell time because passengers may tag on or tag off at times other than when doors open and close. This research effort contended that models could be developed to reliably estimate dwell time distributions when measured distributions of transaction times are known. Development of the models required calibration and validation using field survey data of actual dwell times, and an appreciation of another component of transaction time being bus time in queue. This research develops models for a peak period and off peak period at a busway station on the South East Busway (SEB) in Brisbane, Australia.

Design led innovation : shifting from smart follower to digital strategy leader in the Australian airport sector

This paper presents and discusses organisational barriers and opportunities arising from the dissemination of design led innovation within a leading Australian airport corporation. This research is part of a greater action research program which aims to integrate design as a strategic capability through design led innovation within Australian businesses. Findings reveal that there is an opportunity to employ the theoretical framework and tools of design led innovation in practice to build collaborative idea generation by involving customers and stakeholders within the proposal of new to world propositions. The iterative gathering of deep customer insights also provided an opportunity to leverage a greater understanding of stakeholders and customers in strengthening continuing business partnerships through co-design. Challenges to the design led approach include resistance to the exploratory nature of gathering deep customer insights, the testing of long held assumptions and market data, and the disruption of an organisational mindset geared toward risk aversion instilled within the aviation industry. The implication from these findings is that design led innovation can provide the critical platform to allow for a business to grow and sustain internal design capabilities necessary to challenge prevailing assumptions about how its business model operates to deliver value to customers and stakeholders alike. The platform of design led innovation also provides an avenue to support a cultural transformation towards anticipating future needs necessary for establishing a position of leadership within the broader economic environment.

Storage - the necessity for a Smart-Grid

Energy policy is driving renewable energy deployment with most of the developed countries having some form of renewable energy portfolio standard and emissions reduction target. To deliver upon these ambitious targets, those renewable energy technologies that are commercially available, such as wind and solar, are being deployed, but inherently have issues with intermittency of supply. To overcome these issues, storage options will need to be introduced into the distribution network with benefits for both demand management and power systems quality. How this can be utilised most effectively within the distribution network will allow for an even greater proportion of our energy demand to be met through renewable resources and meet the aspirational targets set. The distribution network will become a network of smart-grids, but to work efficiently and effectively, power quality issues surrounding intermittency must be overcome, with storage being a major factor in this solution.

Smart grid-demand side response model to mitigate prices and peak impact on the electrical system

The aims of this project is to develop demand side response model which assists electricity consumers who are exposed to the market price through aggregator to manage the air-conditioning peak electricity demand. The main contribution of this research is to show how consumers can optimise the energy cost caused by the air-conditioning load considering the electricity market price and network overload. The model is tested with selected characteristics of the room, Queensland electricity market data from Australian Energy Market Operator and data from the Bureau of Statistics on temperatures in Brisbane, during weekdays on hot days from 2011 - 2012.

Digitally enabled?! An analysis of law and justice students' use of smart devices

The research seeks to understand the nature of law and justice students’ use of technology for their learning purposes. There is often an assumption made that all students have, and engage with, technology to the same degree. The research tests these assumptions by means of a survey conducted of first year law and justice students to determine their actual use of smart devices inside and outside classes. The analysis of results reveals that while the majority of respondents own at least one smart device; most rarely use their device for their learning purposes.

A methodological framework for benchmarking smart transport cities

Besides responding to challenges of rapid urbanization and growing traffic congestion, the development of smart transport systems has attracted much attention in recent times. Many promising initiatives have emerged over the years. Despite these initiatives, there is still a lack of understanding about an appropriate definition of smart transport system. As such, it is challenging to identify the appropriate indicators of ‘smartness’. This paper proposes a comprehensive and practical framework to benchmark cities according to the smartness in their transportation systems. The proposed methodology was illustrated using a set of data collected from 26 cities across the world through web search and contacting relevant transport authorities and agencies. Results showed that London, Seattle and Sydney were among the world’s top smart transport cities. In particular, Seattle and Paris ranked high in smart private transport services while London and Singapore scored high on public transport services. London also appeared to be the smartest in terms of emergency transport services. The key value of the proposed innovative framework lies in a comparative analysis among cities, facilitating city-to-city learning.

Towards persistent visual navigation using SMART

In this paper, we present SMART (Sequence Matching Across Route Traversals): a vision- based place recognition system that uses whole image matching techniques and odometry information to improve the precision-recall performance, latency and general applicability of the SeqSLAM algorithm. We evaluate the system’s performance on challenging day and night journeys over several kilometres at widely varying vehicle velocities from 0 to 60 km/h, compare performance to the current state-of- the-art SeqSLAM algorithm, and provide parameter studies that evaluate the effectiveness of each system component. Using 30-metre sequences, SMART achieves place recognition performance of 81% recall at 100% precision, outperforming SeqSLAM, and is robust to significant degradations in odometry.

Perdido : the first Smart Field in the western hemisphere

Located in the Gulf of Mexico in nearly 8,000 feet of water, the Perdido development is the world’s deepest spar and Shell’s first Smart Field in the Western hemisphere. Jointly developed by Shell, BP, and Chevron, the spar and the subsea equipment connected to it will eventually capture approximately an order of magnitude more data than is collected from any other Shell-designed and managed development currently operating in the Gulf of Mexico. This paper will describe Shell’s Smart Fields design philosophy, briefly explain the five design elements that underpin “smartness” in Shell’s North and South American operations—specifically, remote assisted operations, exception-based surveillance, collaborative work environments, hydrocarbon development tools and workflows, and Smart Fields Foundation IT infrastructure—and shed light on the process by which a highly customized Smart Fields development and management plan was put together for Perdido.

Establishing sustainable and reliable smart grids

This paper addresses challenges part of the shift of paradigm taking place in the way we produce, transmit and use power related to what is known as smart grids. The aim of this paper is to explore present initiatives to establish smart grids as a sustainable and reliable power supply system. We argue that smart grids are not isolated to abstract conceptual models alone. We suggest that establishing sustainable and reliable smart grids depend on series of contributions including modeling and simulation projects, technological infrastructure pilots, systemic methods and training, and not least how these and other elements must interact to add reality to the conceptual models. We present and discuss three initiatives that illuminate smart grids from three very different positions. First, the new power grid simulator project in the electrical engineering PhD program at Queensland University of Technology (QUT). Second, the new smart grids infrastructure pilot run by the Norwegian Centers of Expertise Smart Energy Markets (NCE SMART). And third, the new systemic Master program on next generation energy technology at østfold University College (Hiø). These initiatives represent future threads in a mesh embedding smart grids in models, technology, infrastructure, education, skills and people.

Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.

A new approach for evaluating the benefits of smart grid development

In this paper, the inherent mechanism of benefits associated with smart grid development is examined based on the Pressure-State-Response (PSR) model from resource economics. The emerging types of technology brought up by smart grid development are taken as pressures. The improvements of the performance and efficiency of power system operation are taken as states. The effects of smart grid development on society are taken as responses. Then, a novel method for evaluating social benefits in energy saving and CO2 emission reduction from smart grid development is presented. Finally, the benefits in a province in northwest China is carried out by employing the developed evaluation system, and reasonable evaluation results are attained.

Residential voltage dip and swell mitigation using Plug-in Hybrid Electric Vehicle in smart grid

Solutions to remedy the voltage disturbances have been mostly suggested only for industrial customers. However, not much research has been done on the impact of the voltage problems on residential facilities. This paper proposes a new method to reduce the effect of voltage dip and swell in smart grids equipped by communication systems. To reach this purpose, a voltage source inverter and the corresponding control system are employed. The behavior of a power system during voltage dip and swell are analyzed. The results demonstrate reasonable improvement in terms of voltage dip and swell mitigation. All simulations are implemented in MATLAB/Simulink environment.

Voltage regulation, power balancing and battery storage discharge control by smart demand side management and multi-objective decision making

A novel intelligent online demand side management system is proposed for peak load management. The method also regulates the network voltage, balances the power in three phases and coordinates the battery storage discharge within the network. This method uses low cost controllers with low bandwidth two-way communication installed in costumers' premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified through an event-based developed simulation in Matlab.

Smart Inter-Phase Switching of Residential Loads in Low Voltage Distribution Feeders

In order to dynamically reduce voltage unbalance along a low voltage distribution feeder, a smart residential load transfer system is discussed. In this scheme, residential loads can be transferred from one phase to another to minimize the voltage unbalance along the feeder. Each house is supplied through a static transfer switch and a controller. The master controller, installed at the transformer, observes the power consumption in each house and will determine which house(s) should be transferred from an initially connected phase to another in order to keep the voltage unbalance minimum. The performance of the smart load transfer scheme is demonstrated by simulations.

On-line Demand Management of Low Voltage Residential Distribution Networks in Smart Grids

A novel intelligent online demand management system is discussed in this chapter for peak load management in low voltage residential distribution networks based on the smart grid concept. The discussed system also regulates the network voltage, balances the power in three phases and coordinates the energy storage within the network. This method uses low cost controllers, with two-way communication interfaces, installed in costumers’ premises and at distribution transformers to manage the peak load while maximizing customer satisfaction. A multi-objective decision making process is proposed to select the load(s) to be delayed or controlled. The efficacy of the proposed control system is verified by a MATLAB-based simulation which includes detailed modeling of residential loads and the network.