9,926 research outputs found
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iSEA: IoT-based smartphone energy assistant for prompting energy-aware behaviors in commercial buildings
Providing personalized energy-use information to individual occupants enables the adoption of energy-aware behaviors in commercial buildings. However, the implementation of individualized feedback still remains challenging due to the difficulties in collecting personalized data, tracking personal behaviors, and delivering personalized tailored information to individual occupants. Nowadays, the Internet of Things (IoT) technologies are used in a variety of applications including real-time monitoring, control, and decision-making due to the flexibility of these technologies for fusing different data streams. In this paper, we propose a novel IoT-based smartphone energy assistant (iSEA) framework which prompts energy-aware behaviors in commercial buildings. iSEA tracks individual occupants through tracking their smartphones, uses a deep learning approach to identify their energy usage, and delivers personalized tailored feedback to impact their usage. iSEA particularly uses an energy-use efficiency index (EEI) to understand behaviors and categorize them into efficient and inefficient behaviors. The iSEA architecture includes four layers: physical, cloud, service, and communication. The results of implementing iSEA in a commercial building with ten occupants over a twelve-week duration demonstrate the validity of this approach in enhancing individualized energy-use behaviors. An average of 34% energy savings was measured by tracking occupants’ EEI by the end of the experimental period. In addition, the results demonstrate that commercial building occupants often ignore controlling over lighting systems at their departure events that leads to wasting energy during non-working hours. By utilizing the existing IoT devices in commercial buildings, iSEA significantly contributes to support research efforts into sensing and enhancing energy-aware behaviors at minimal costs
Towards Smarter Management of Overtourism in Historic Centres Through Visitor-Flow Monitoring
Historic centres are highly regarded destinations for watching and even participating in diverse and unique forms of cultural expression. Cultural tourism, according to the World Tourism Organization (UNWTO), is an important and consolidated tourism sector and its strong growth is expected to continue over the coming years. Tourism, the much dreamt of redeemer for historic centres, also represents one of the main threats to heritage conservation: visitors can dynamize an economy, yet the rapid growth of tourism often has negative effects on both built heritage and the lives of local inhabitants. Knowledge of occupancy levels and flows of visiting tourists is key to the efficient management of tourism; the new technologies—the Internet of Things (IoT), big data, and geographic information systems (GIS)—when combined in interconnected networks represent a qualitative leap forward, compared to traditional methods of estimating locations and flows. A methodology is described in this paper for the management of tourism flows that is designed to promote sustainable tourism in historic centres through intelligent support mechanisms. As part of the Smart Heritage City (SHCITY) project, a collection system for visitors is developed. Following data collection via monitoring equipment, the analysis of a set of quantitative indicators yields information that can then be used to analyse visitor flows; enabling city managers to make management decisions when the tourism-carrying capacity is exceeded and gives way to overtourism.Funded by the Interreg Sudoe Programme of the European Regional Development Funds (ERDF
Towards sustainable transport: wireless detection of passenger trips on public transport buses
An important problem in creating efficient public transport is obtaining data
about the set of trips that passengers make, usually referred to as an
Origin/Destination (OD) matrix. Obtaining this data is problematic and
expensive in general, especially in the case of buses because on-board
ticketing systems do not record where and when passengers get off a bus. In
this paper we describe a novel and inexpensive system that uses off-the-shelf
Bluetooth hardware to accurately record passenger journeys. Here we show how
our system can be used to derive passenger OD matrices, and additionally we
show how our data can be used to further improve public transport services.Comment: 13 pages, 4 figures, 1 tabl
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System-level key performance indicators for building performance evaluation
Quantifying building energy performance through the development and use of key performance indicators (KPIs) is an essential step in achieving energy saving goals in both new and existing buildings. Current methods used to evaluate improvements, however, are not well represented at the system-level (e.g., lighting, plug-loads, HVAC, service water heating). Instead, they are typically only either measured at the whole building level (e.g., energy use intensity) or at the equipment level (e.g., chiller efficiency coefficient of performance (COP)) with limited insights for benchmarking and diagnosing deviations in performance of aggregated equipment that delivers a specific service to a building (e.g., space heating, lighting). The increasing installation of sensors and meters in buildings makes the evaluation of building performance at the system level more feasible through improved data collection. Leveraging this opportunity, this study introduces a set of system-level KPIs, which cover four major end-use systems in buildings: lighting, MELs (Miscellaneous Electric Loads, aka plug loads), HVAC (heating, ventilation, and air-conditioning), and SWH (service water heating), and their eleven subsystems. The system KPIs are formulated in a new context to represent various types of performance, including energy use, peak demand, load shape, occupant thermal comfort and visual comfort, ventilation, and water use. This paper also presents a database of system KPIs using the EnergyPlus simulation results of 16 USDOE prototype commercial building models across four vintages and five climate zones. These system KPIs, although originally developed for office buildings, can be applied to other building types with some adjustment or extension. Potential applications of system KPIs for system performance benchmarking and diagnostics, code compliance, and measurement and verification are discussed
Deep Underground Science and Engineering Laboratory - Preliminary Design Report
The DUSEL Project has produced the Preliminary Design of the Deep Underground
Science and Engineering Laboratory (DUSEL) at the rehabilitated former
Homestake mine in South Dakota. The Facility design calls for, on the surface,
two new buildings - one a visitor and education center, the other an experiment
assembly hall - and multiple repurposed existing buildings. To support
underground research activities, the design includes two laboratory modules and
additional spaces at a level 4,850 feet underground for physics, biology,
engineering, and Earth science experiments. On the same level, the design
includes a Department of Energy-shepherded Large Cavity supporting the Long
Baseline Neutrino Experiment. At the 7,400-feet level, the design incorporates
one laboratory module and additional spaces for physics and Earth science
efforts. With input from some 25 science and engineering collaborations, the
Project has designed critical experimental space and infrastructure needs,
including space for a suite of multidisciplinary experiments in a laboratory
whose projected life span is at least 30 years. From these experiments, a
critical suite of experiments is outlined, whose construction will be funded
along with the facility. The Facility design permits expansion and evolution,
as may be driven by future science requirements, and enables participation by
other agencies. The design leverages South Dakota's substantial investment in
facility infrastructure, risk retirement, and operation of its Sanford
Laboratory at Homestake. The Project is planning education and outreach
programs, and has initiated efforts to establish regional partnerships with
underserved populations - regional American Indian and rural populations
How to Improve the Capture of Urban Goods Movement Data?
The surveys specifically focused on the thorough knowledge of urban freight transport appeared about ten years ago. The local problematic of goods transport at local level was partially taken into account by the city planners and by the researchers: until recent years, the integration of goods transport in the total urban flows models was estimated applying a multiplying factor to car traffic. Delivering goods was not considered like a concern.Because of the quick growth of car traffic in the cities, the main stakes changed too: the fight against traffic congestion, the management of the lack of space (shipment consolidation and storage), the attempts to reduce local environmental impacts and global externalities (energy saving, reduction of greenhouse gas emissions), and economic valuation of city centres (under the pressure of a slowed down economic growth).All these changes were taking place in a context in which available rooms for manoeuvre were limited by factors such as congestion, concerns about the quality of urban life and budget restriction. It resulted in a growing unease on the freight transport industry and the city authorities, the latter having little or no data, methods and references in order to elaborate a satisfactory policy framework.surveys on urban freight transport ; urban freight movements ; urban freight data collection ; urban goods data collection ; diversity of measurement units and methods ; state of the art
Citywide Transportation Greenhouse Gas Emissions Inventories: A Review of Selected Methodologies
Outlines the methodological issues in creating transportation emissions inventories and how they affect the results, reviews currently used methodologies, and explores ways to integrate inventories with climate policies to inform reduction strategies
The Sanford Underground Research Facility at Homestake
The former Homestake gold mine in Lead, South Dakota is being transformed
into a dedicated laboratory to pursue underground research in rare-process
physics, as well as offering research opportunities in other disciplines such
as biology, geology and engineering. A key component of the Sanford Underground
Research Facility (SURF) is the Davis Campus, which is in operation at the
4850-foot level (4300 m.w.e) and currently hosts three projects: the LUX dark
matter experiment, the MAJORANA DEMONSTRATOR neutrinoless double-beta decay
experiment and the CUBED low-background counter. Plans for possible future
experiments at SURF are well underway and include long baseline neutrino
oscillation experiments, future dark matter experiments as well as nuclear
astrophysics accelerators. Facility upgrades to accommodate some of these
future projects have already started. SURF is a dedicated facility with
significant expansion capability.Comment: 14 pages, 10 figures, Proceedings of the VII International Conference
on Interconnections between Particle Physics and Cosmology (PPC2013),
Deadwood, SD, July 8-13, 201
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