Competitive Internal Projects
EPSSI - Exploring the Potential of the Sentinel missions Satellite Imagery
Title: Cityndex II – Soft Accessibility City Index – part II
Principal investigator: Eduardo Natividade
Research team: João Manuel Coutinho Rodrigues, John Current
Dates start/end: 10-2016 / 03-2018
Synopsis
During the last decades, mobility has become an ever-increasing need. Transport is also an issue be- cause this sector is a major consumer of energy, responsible for about one-quarter of total energy con- sumed in the EU and even a large emitter of GHG emissions (nearly one-third of all emissions) factors which are nowadays hot topics in the political agenda.
With increasing concern about global warming, greenhouse gas emissions and rising fuel prices, non- motorized modes, such as bicycle are gaining importance as a viable mode in urban transportation worldwide and has been actively encouraged by the European Agenda for transport and sustainable mobility and by national and local policies, in several countries.
In fact, cycling is a promising way for mobility in an urban context due to their many benefits, compared with motorised transports (reduced carbon footprint, lower maintenance, health, social and infrastructur- al costs).
One of the main obstacles to increase the bicycle as a mode of transport are safety concerns due to in- teractions with motorised traffic. For uncongested traffic cities or areas, the simple and best option is to separate cyclists from motorists through exclusive bicycle priority lanes. However, for congested roads enforcing bicycle lanes may degenerate the network, making the idea very hard to sell both to the pub- lic and the traffic authorities.
The primary objective of this project is to create a multicriteria indicator that assesses the suitability of the existing urban network for cycling. And to develop a methodology which, from that index, helps the responsible entities to improve the cycling conditions of their urban network and select the best places for the creation of new bike lanes. By suitability, we mean non-subjective factors that characterise the suitability of a route for cycling, including safety, traffic volumes, traffic speeds, presence of bicycle lanes, whether the terrain is flat or hilly, etc.
The final objective is to incorporate this cyclical indicator into the Soft Accessibility City Index – Cityndex – developed in our previous project.
CityModel - City Model Benchmarking
Title: CityModel – City Model Benchmarking
Principal investigator: Nuno Miguel Marques de Sousa
Research team: Nuno Sousa, Luís Alçada, John Current, Junior Researcher
Dates start/end: 1st of November 2019/31 October 2020
Synopsis
The structure and form of the cities, their disposition and the spatial location of their areas, zones and facilities has been an open discussion, as old as cities themselves. This has been an active debate by academia researchers, with concepts like the Garden City, Radiant City or Linear City, firing up theoretical discussions, mainly questioning what the ideal form of a city would be, as well as which model would be most efficient. However, in practice cities ended up growing based on different criteria, ideas, models, many times in a chaotic way with different influences along the years.
Theoretical debates on structure and form were mostly academic due to lack of adequate analysis tools that could point out the advantages of the different urban design ideas, as well as providing an effective comparison between the different models and the real cities.
Until now.
The recent development of Geographical Information Systems (GIS) and the massive improvement in calculus capabilities of computers opened up the possibility of putting the theories to the test. By looking at a real city, as it stands, pinpointing its geographical layout of zones, buildings and facilities, and laying these down in the form of a classic concept like the Garden City, it is possible to compare the real situation with what would be if the city’s urban architecture was to follow a classic model. In short, to ascertain how good the classic city models are, after all.
But comparing requires defining some sort of performance indicator. Thus, it is necessary to look for core indicators by which cities can be compared. These may be connected to energy efficiency, mobility, accessibility, pleasantness and quality of life. In addition, they must be quantifiable and calculable in GIS.
This project aims to give a tentative answer to the question “what is the ideal city?” by comparing the city of Coimbra, Portugal, as it stands in real life, with its would-be layout as a classic city, the Garden City, using as comparison measure an accessibility indicator.
Garden city and accessibility are just one particular combination of model/indicator. Many more classic models and indicators could be envisioned, and will be explored, time permitting. This proposal can thus also be seen as a test ground for an ambitious, long-term project of benchmarking and comparing multiple city models in very many ways, possibly culminating in a multicriteria analysis.
ML2Building - Data-driven machine learning approach for building energy demand forecasting
Title: ML2Building – Data-driven machine learning approach for building energy demand forecasting
Principal investigator: João Miguel Charrua de Sousa
Research team: João Miguel Charrua de Sousa, Hermano Joaquim dos Santos Bernardo, Filipe Tadeu Soares Oliveira, Marcela Ribeiro Ferreira (Master Student in Energy and Environmental Engineering at ESTG/IPLeiria), Research Fellow (to be defined)
Dates start/end: 1st of November 2019/31 October 2020
Synopsis
This project aims at using a data-driven machine learning approach for forecasting the energy demand of buildings, particularly in the non-residential sector. As the prediction of energy consumption in buildings is usually made by detailed building energy performance simulation (using software tools such as EnergyPlus), it requires the training of the user, the feeding of the building data input to the software and the computational effort associated to calculations, that can be considerably time-consuming. Whenever the building starts to be operated and occupied, the factors affecting the energy consumption increase significantly adding uncertainty and difficulty to the process of creating accurate simulation models. Bearing in mind that in these circumstances historically recorded time series energy data becomes available, statistical and machine learning techniques appear to be an alternative tool for forecasting future energy demand scenarios. Therefore, the main goal of this project is to validate the proposed approach through the comparisons with previously calibrated detailed building energy simulation models and real energy measured data.
CO2Residenergy@cPT - Climate Change Impacts on Residential Heating and Cooling Energy Demand in the Centre of Portugal
Title: CO2Residenergy@cPT – Climate Change Impacts on Residential Heating and Cooling Energy Demand in the Centre of Portugal
Principal investigator: João António Esteves Ramos
Research team: Sandra Mourato, Cristina Andrade
Dates start/end: 11-2019 / 10-2020
Synopsis
Under future climate change projections, relevant impacts can be expected also on the energy use in buildings, especially their correlations with the prevailing weather conditions. The building energy sector is crucial to achieving emission reductions as it has an important energy-saving potential. In the present project, the potential effects of climate change on changes of heating and cooling energy demand and perceived thermal comfort in the household sector will be investigated.
The evolution of the heating and cooling degree day indicators, the mean outdoor and indoor air temperature, the solar radiation and the heating and cooling season durations are going to be analyzed for three different periods: 1961-1990, 1981-2010 and 2021-2050, over three NUT III regions in the center of Portugal. The temperature data will be retrieved from five high-resolution bias-adjusted EURO-CORDEX 0.11º simulations for two emission representative concentration pathways (RCP4.5 and RCP8.5).
Notable regional differences and trends are expected to be achieved in the building energetic performance results. The impacts of climate change should be an integral component in the design of residential buildings and in the future trends of building envelope requirements. Projections also should help people to understand the scale of climate changes in terms that could influence decisions not only about where to live and work, but also about what energy systems and behaviors should be adopted. A websig, to spatially represent the results, will support project dissemination to stakeholders.
LiveCITY - Data science for a live city
Title: LiveCITY – Data science for a live city
Principal investigator: João Manuel Coutinho Rodrigues
Research team: Eduardo Manuel Natividade de Jesus, Arminda Maria Marques Almeida, John Current, Junior Researcher
Dates start/end: 1st of November 2019/31 October 2020
Synopsis
Today’s flow of people towards cities will lead to 80% of the population living in urban areas by 2050. This fast growth of cities contrasts with their ageing infrastructure, some of which is centuries old. Dealing with infrastructure deterioration requires efficient tools that integrate the signalling, registering and attendance of operational occurrences.
Traditional reporting methods are field survey by a technician (slow, costly, not engaging) and direct phone call/email by citizens (time-consuming for the citizen, no feedback, reports not automatically processed). App-based engagement systems, with citizens reporting occurrences live via this App (e.g. fixMyStreet, seeClickFix) exist already, giving basic statistics on number/location of occurrences and feedback to users, but none offers decision support. Entities that manage the urban space rely solely on their empirical judgement to decide which occurrences to attend first.
ICT, ubiquitous connectivity, knowledge and creativity, big data and open data, social capital, business and entrepreneurialism, smart community, ecological sustainability etc. are being appointed to characterise the smart city discourse, bewildering the meaning of the concept. However, there is also another perspective of smart cities more focused on the human concept, which included social innovation, smart citizenry, learning and knowledge capital and inter-organisational collaboration. It is seeking to include these two perspectives that we intend to develop the project “Data science for a live city – LiveCITY”.
In the research and development work carried out in recent years, a prototype of a solution has been created. The aim of this project is to develop, implement and provide this prototype with a backoffice, mobile aplications, and a wider and more dedicated set of advanced algorithms, capable of handling big data, that give priorities based on technical aspects, economic and social impact of the occurrences in order to transform it into a TRL 7-8 solution that allows the testing of a pilot project, preferably in a medium-sized city (e.g. Coimbra). The planned structure encompasses a front-end/desktop interface, a back-office offering decision support algorithms and mobile Apps.
UArribaS - Unmanned Aerial Systems for monitoring coastal cliffs
Title: UArribaS – Unmanned Aerial Systems for monitoring coastal cliffs
Principal investigator: Gil Gonçalves (INESCC)
Research team: Umberto Andriolo (INESCC), Paulo Providência (INESCC), Diogo Duarte (INESCC), Alvaro Gomez Gutierrez (Universidade de Extremadura), Jose Juan de SanJose Blasco (Universidade de Extremadura)
Dates start/end: 01/02/2020 to 30/09/2020
Synopsis
The project aims to develop, test and validate novel UAS-based cost-effective techniques to measure and monitor coastal cliff-faces. The main purpose is to use images acquired by Unmanned Aerial Systems (UAS) to generate cliff-face 3D model datasets applying SfM-MVS (Structure-from-Motion and Multi-View Stereo) Photogrammetry. Coastal Cliff-face (CF) volume changes will be detected comparing results obtained by repeated UAS-surveys, with the final scope of realising high spatial and temporal resolution 4D maps of cliff erosion. Specifically, the project objectives are: i) test and set novel methods to optimize UAS vertical flight planning to monitor CFs; ii) improve UAS-based 3D model generation of vertical structures using SfM-MVS Photogrammetry; iii) develop an efficient change-detection analysis for CF monitoring.
CART - Computational Approaches for Automated Radiotherapy
Title: CART – Computational Approaches for Automated Radiotherapy
Principal investigator: Joana Dias
Research team: Humberto Rocha, Maria do Carmos Lopes, Brígida Ferreira, Tiago Ventura
Dates start/end: 10-2016 / 03-2018
Synopsis
Radiotherapy is the most technologically demanding cancer treatment approach, requiring cutting edge high cost technological equipment and trained personnel. The most common radiation therapy equipment is a linear accelerator where the patient lies down, properly immobilized in a movable couch. The prescribed radiation dose treatment is previously planned for each patient. In this project we aim at further develop the work that has already been done regarding the application of computational approaches and optimization algorithms to automated radiotherapy planning. W e have already developed successfully optimization algorithms applied to the beam angle optimization (deciding which the best incidence directions for each radiotherapy treatment are). We have recently developed a fuzzy reasoning approach that allows fully automation of the fluence optimization problem (the problem of determining, for a fixed set of beam angles, what are the best patterns of radiation allowed by the modulation of the radiation beam). In order to develop a fully automated RT multicriteria framework, we will embed the most promising beam angle optimization approaches (namely pattern search approaches) with fuzzy reasoning applied to fluence map optimization considering not one but a set of different objective functions. In reality, radiotherapy treatment planning is a multicriteria problem by nature, since we aim at simultaneously maximize the dose deposited in the volumes to treat and spare all healthy organs. The option for a multicriteria approach will also raise new problems regarding the decision-making process by the medical doctor. We can thus summarize the main goals of the project as follows:
- Achieve an automated multicriteria approach for radiotherapy planning.
- Develop procedures to support medical decision making in a multicriteria decision making framework.
Multistep - Multistep Repair
Title: Multistep – Multistep Repair
Principal investigator: Nuno Sousa
Research team: João Coutinho Rodrigues, John Current
Dates start/end: 10-2016 / 03-2018
Synopsis
Today’s urban landscape is populated by many infrastructures supporting city life. Some of these degrade quickly and require frequent repairs, while others, such as buildings, large scale structures, sidewalks, etc. degrade more slowly, i.e. have a longer durability cycle. Undertaking maintenance on the latter kind of urban infrastructures requires a well thought-out plan, as these actions are typically expensive, resource-intensive works and have long-lasting effects. It therefore becomes important to develop managerial tools for planning interventions that take into account both (1) the benefits that can be given to the population from servicing the infrastructures; and (2) the costs of doing so.
Given the motivation above, it is the objective of this project to devise and thoroughly test a multicriteria model for the important urban engineering problem of planning interventions on large, multiple feature urban infrastructures that degrade slowly. The model will aim at maximizing benefits to the population and minimizing costs, while taking into account real-life factors such as e.g. possible social synergies of actions undertaken, concomitance of assets and volume discounts.
NL-TCC - One-dimensional non-linear analysis of timber-concrete composite members
Title: NL-TCC – One-dimensional non-linear analysis of timber-concrete composite members
Principal investigator: Anísio Andrade
Research team: Fabian Cabrera Exeni
Dates start/end: 10-2016 / 03-2018
Synopsis
The sustainability of all human activities is a matter of major societal concern. This is particularly relevant to the construction industry, one of the larger contributors to resources consumption and waste production. As a result, recent years have seen a substantial increase in the use of timber-concrete composite construction, both for the retrofitting of existing structures and for the construction of new structures. However, accurate and efficient methods of analysis, readily available to practitioners and researchers alike, are still lacking. This project aims at developing, implementing and making available a simple-to-use 1D mixed finite element model for the materially non-linear analysis of planar timber-concrete composite beams.
Timber is a natural material, distinctively heterogeneous and with widely varying mechanical properties. It is also a hygroscopic material, whose properties depend on the environmental exposure conditions. Accordingly, a second main objective of the project is to investigate the influence of the variability of the timber and shear connection properties upon the overall mechanical behaviour of timber-concrete composite members.
EnergyBOR - Behavioural issues in decision making on energy efficiency
UNAUTHORIZED
Cityndex - Soft Accessibility City Index
Title: Cityndex – Soft Accessibility City Index
Principal investigator: Eduardo Natividade
Research team: Luis Alçada, Arminda Almeida, John Current
Dates start/end: 10-2016 / 03-2018
Synopsis
Sustainability worries related to the intensive use of energy by automobiles and traffic congestion issues have encouraged decision makers to look for alternative solutions, leading to an emerging shift towards soft/active transport modes. In tandem with this, recent years have witnessed a tendency of the younger generations to search for housing in city centers, aiming at a lifestyle where they can move around without the need for motorized transport.
This emergence of a New Urban Age calls for the development of new tools to assess a city’s response to the shift in transport demand patterns. Clearly soft modes travel modes, like walking and cycling, will play a major role in this changing context. Walking is the most basic and most often used urban mode of transport, not only per se, but also because practically every motorized trip begins or ends with pedestrian travel. The pedestrian mode of transport has well-known benefits at multiple levels: energy/emissions, sustainability, health, etc. The bicycle is a means of transport that can be adopted in most cities, which combines the readiness to use of the automobile with high efficiency, low congestion, health and quickness of travel for short distances (it is competitive with automobiles up to 5 km).
It is the goal of this project to construct and evaluate a city accessibility index for soft travel modes, namely walking and cycling, including the possibility of pedelec-type bicycles usage. Given the multiple aspects of reality that are involved in this problematic, a multicriteria approach is necessary (see e.g. for an example of the use of multicriteria methods in connection to urban problems).
NEDIPER - New Directions for Performance Evaluation and Resilience in Communication Networks
Title: NEDIPER – New Directions for Performance Evaluation and Resilience in Communication Networks
Principal investigator: Teresa Gomes
Research team: João Clímaco, José Craveirinha, Lúcia Martins, Rita Girão Silva, Paulo Melo, Luísa Jorge, Marta Pascoal
Dates start/end: 10-2016 / 03-2018
Synopsis
Three aspects of routing are explored: multi-attribute (MA) decision models for evaluation and selection of routing methods, bi-criteria approaches for multi-point routing and routing with specified elements. Then resilience requirements are introduced and explored in different contexts.
A formulation of a decision problem focused on the comparison and selection of flow-oriented routing models evaluated through multiple global network performance measures will be made. It will be shown that multi-attribute analysis with the VIP software, which may involve cooperative group decision with a facilitator, is appropriate in this context.
Multi-point routing is a difficult problem, and may involve different objectives. An effective heuristic approach for obtaining a larger set of non-dominated solutions will be pursued and compared with other approaches.
For certain types of applications, with path protection, each of the paths in the pair must visit each a set of network elements which are specified in advance. New effective algorithms will be developed for calculating disjoint path pairs in this context. New exact combinatorial approaches will be explored for solving the problems of obtaining totally or maximally Shared Risk Link Groups (SRLG)-disjoint path pairs. The spine concept, a sub-network structure embedded at the physical layer, will be explored, namely its use in the context of Software Defined Networking.
RCBCJSR - Strengthening and rehabilitation of beam-column joints of reinforced concrete frames
Title: RCBCJSR – Strengthening and rehabilitation of beam-column joints of reinforced concrete frames
Principal investigator: Paulo Providência
Research team: Miguel Ferreira
Dates start/end: 10-2016 / 03-2018
Synopsis
Inadequately designed reinforced concrete beam-column joints (RCBC joints) can lead to hard to predict, premature and non-ductile failure modes of moment resisting frames (MRFs). This is even more likely under seismic actions when RCBC joints have substandard detailing such as lack of transverse reinforcement in the joint core, the use of plain round bars and inadequate anchorage of the beam and column bars, typical of pre 1970 construction practice.
Among the RCBC joint models developed so far the macro-element type models seem to be the ones that better fulfil the requirements of objectivity, versatility, soundness, efficiency and robustness. On the other hand, a RCBC joint retrofitting technique that has revealed good results and actually seems to be feasible, independently of the joint typology, is the Fully Fastened Haunches (FFH). FFH consists in the introduction of haunch elements (a machined bar/plate connected to plates at both ends) connected to beam and column near to the RCBC joint using post-installed mechanical anchors.
This research project recognises addresses (i) the assessment and modelling of the static and cyclic behaviour of RCBC joints, particularly the combined effect within the joint of the forces applied at its boundary, and (ii) the development and implementation in common FEM based programs of suitable FEM models for RCBC joints properly/poor designed, possibly retrofitted using FFH.
The investigation encompasses the following steps: (i)identification of the most relevant systems of forces applied at RCBC joints periphery, (ii) quantification and modelling of the combined effect of these systems of forces on joint behaviour, (iii) quantification and modelling of FFH on RCBC joint behaviour, (iv) development of a RCBC joint model which applies as-built RCBC joints as well as to joints retrofitted with FFH, (v) implementation of the RCBC joint model in FEM based software and (vi) improvement of the available design and strengthening procedures for RCBC joints.
ExtremeCGI - Monitoring Extreme Events integrating Crowdsourced Geographic Information and Real-time Sensor Data
Title: ExtremeCGI – Monitoring Extreme Events integrating Crowdsourced Geographic Information and Real-time Sensor Data
Principal investigator: Cidália Fonte
Research team: José Paulo Elvas Duarte de Almeida, Alberto Cardoso, João Porto Albuquerque, Peter Mooney, Vyron Antoniou, Jacinto Estima
Dates start/end: 10-2016 / 03-2018
Synopsis
Information is the base for decision-making and the quality of information available is crucial towards good decisions. In particular, the amount and diversity of geospatial data currently available is huge and constantly growing. Although this gives a great opportunity for better decisions, there are also major challenges in integrating diverse sources of data with different characteristics. The main challenge raised is to effectively mine and integrate data so to extract relevant information, especially within a very short time window. In this context, the main aim of the project is to develop an information system capable of integrating diverse sources of geospatial data in such a way that makes it easily available to authorities in order to assist them in risk assessment and mitigation in case of extreme events.
Types of data to be integrated include: 1) Crowdsourced data gathered by citizens for various purposes (e.g. geo-tagged photos from social networks); 2) Environmental data from in-situ physical sensors (e.g. water gauges); 3) Event specific data collected by citizens using smartphone apps developed for the aim; 4) Other sources of geospatial data, including remotely sensed imagery and derived products.
The integration of diverse sources of data enables to: 1) Perform automatic validation procedures so to assist relevant data mining, using, for instance, the geographical location; 2) Increase the exploitation of crowdsourced data capabilities to provide useful information in real-time, or near real-time – e.g. quick identification of important information to assist mitigation operations or collect data about an occurring event; 3) Combine crowdsourced data with physical measurements, so to enable data validation and their quality assessment. The development of such system will provide authorities with valuable information, both in quantity and quality, especially in real-time situations where decisions that directly affect people’s life need to be taken quickly.
AFV - Alternative Fuel Vehicles
Title: AFV – Alternative Fuel Vehicles
Principal investigator: Nuno Sousa
Research team: Luis Miguel Tomás Alçada de Almeida, Arminda Maria Marques Almeida, John Current
Dates start/end: 6-2018 / 12-2018
Synopsis
Transport is responsible for almost a quarter of Europe’s greenhouse gas (GHG) emissions, with the road transport being the biggest emitter, with more than 70% of all GHG emissions from transport in 2014 [1]. Pressed by climate change fears and consequent emissions regulations demands, alternative fuel vehi- cles have emerged as a mitigation strategy to reduce GHG emissions from road transport [2]. Many auto- mobile brands have invested in the development of different propulsion and powertrain technologies, of which Liquefied Petroleum Gas (LPG), hybrid (HEV), plug-in hybrid (PHEV), and battery electric vehi- cles (BEV) are the most common examples.
However, although a considerable supply of alternative fuel vehicles is currently being offered on stock, in practice the consumer acceptance of these technologies is still low, as shown by low market penetra- tion rates [3]. Overall in 2016, 65.1% of all new passenger cars registered in Portugal ran on diesel fuel and 32% on petrol, while HEV accounted for 1.6% of new cars, electrically chargeable vehicles (PHEV and BEV) for 0.9% and other alternative fuels (such as LPG, natural gas and E85) for 0.5% [4].
The purpose of this project is to use multi-criteria decision methods (MCDM) to estimate how the various criteria consumers take into account when buying a new vehicle may influence their acceptance for al- ternative fuel vehicles, in particular private automobiles, using the Portuguese scenario as a case-study. Then, through a sensitivity analysis, to try and understand what would be the necessary changes to the status-quo to increase the attractiveness of these vehicles, from a potential buyer’s point of view.
The Fictitious Force Method-Numerical Applications and Arc-Length
Title: The Fictitious Force Method-Numerical Applications and Arc-Length
Principal investigator: Pedro Gala
Research team: Ricardo Joel Teixeira Costa
Dates start/end: 6-2018 / 12-2018
Synopsis
Practical Analysis and Design of Reinforced Concrete Structures nowadays still is based on simple com- prehensive global linear elastic models formed mainly with 1D elements, despite of the powerful 3D Nonlinear Finite Element Method (NLFEM) analysis packages available. The use of these complex NLFEM models, seems to be restricted to the study of local phenomena due to the large amount of time required to validate the models, perform the analysis and interpret the results. Accordingly, many times their use is replaced by Stress Field Models.
This scenario justified the development of the Fictitious Force Method (FFM), see [1], a simple but effec- tive 1D materially nonlinear analysis method of skeletal structures, emerging as a natural extension of the P-Delta geometric nonlinear analysis method [2]. In FFM the material nonlinear behavior is consid- ered in supplementary loading systems, during an iterative procedure made of simple operations where the same stiffness can be used in all iterations.
The FFM has been used in several recent studies [3][4][5] and is presently implemented in the software EvalS [6]. In the scope of these studies, it was found that in order to properly analyse the “post-peek” be- haviour of frame structures it is necessary to adapt the general FFM frame-work in order to make it suit- able to implement an arc-length procedure. Accordingly, the main objectives of this research project are:
i) To develop the desired FFM/arc-length procedure, making FFM suitable for the analysis of reinforced concrete structures exhibiting post-peak behaviour, e.g. a dedicated example previously studied by the research team and (exhibiting postpeak behaviour), see [7] and [8].
ii) To validate the FFM/arc-length procedure throughout the numerical analysis of a set of benchmark case studies.
iii) To identify the sufficient convergence conditions of FFM/arc-length procedure (therefore in cases whith post-peak behaviour).
GeoTimeLine - A system for Multi-Hazard Event Reconstruction in Space and Time
Title: GeoTimeLine – A system for Multi-Hazard Event Reconstruction in Space and Time
Principal investigator: José-Paulo de Almeida
Research team: Cidália Fonte, Alberto Cardoso, Jacinto Estima
Dates start/end: 6-2018 / 12-2018
Synopsis
Information adequately documented is crucial in supporting decision-making. The expansion of web 2.0 made available loads of information, with a great potential in a wide range of domains , and opened up to authorities a series of opportunities towards better decisions. This fact raises a few issues though re- lated to vast amounts of unclassified data, various sources and formats, and their dispersion across the web. Thus, one of the main challenges refers to the ability of effectively mining , validating, annotating, and integrating key data to extract relevant information about a specific context of interest, especially within very short time windows. As far as our own research interests are concerned, we are particularly interested in enriching data related to a specific event by inferring additional details on both their geo- location (where) and time-location (when).
In the light of the above, the main aim of this project is to establish documented databases provided with a “geotimeline” creation mechanism. Types of data to search and to be downloaded onto the data- bases include: 1) Crowdsourced data gathered by citizens for various purposes (e.g. social networks); 2) Environmental data from in-situ physical sensors (e.g. water gauges); Online newspaper archives.
The integration of diverse sources of such data within a single enriched database provided with features above will enable to: 1) Produce geotimelines of historical key events that took place and show both the geospatial and temporal organisational evolution of those events; 2) Set up a stand-alone system whose data validation & annotation tools, and geotimeline creation feature can be integrated into other deci- sion support platforms (e.g. for risk/emergency mitigation, our main immediate goal).
The development of such system will improve the support of decision making processes may assist by providing authorities with valuable information, both in quantity and quality, especially in real-time situa- tions where decisions directly affecting citizens need to be taken rapidly.
Heritage-3DIM - Modelling and Monitoring Cultural Heritage with 3D Geospatial Data
Cityndex II - Soft Accessibility City Index – part II
Title: Cityndex II – Soft Accessibility City Index – part II
Principal investigator: Eduardo Natividade
Research team: João Manuel Coutinho Rodrigues, John Current
Dates start/end: 10-2016 / 03-2018
Synopsis
During the last decades, mobility has become an ever-increasing need. Transport is also an issue be- cause this sector is a major consumer of energy, responsible for about one-quarter of total energy con- sumed in the EU and even a large emitter of GHG emissions (nearly one-third of all emissions) factors which are nowadays hot topics in the political agenda.
With increasing concern about global warming, greenhouse gas emissions and rising fuel prices, non- motorized modes, such as bicycle are gaining importance as a viable mode in urban transportation worldwide and has been actively encouraged by the European Agenda for transport and sustainable mobility and by national and local policies, in several countries.
In fact, cycling is a promising way for mobility in an urban context due to their many benefits, compared with motorised transports (reduced carbon footprint, lower maintenance, health, social and infrastructur- al costs).
One of the main obstacles to increase the bicycle as a mode of transport are safety concerns due to in- teractions with motorised traffic. For uncongested traffic cities or areas, the simple and best option is to separate cyclists from motorists through exclusive bicycle priority lanes. However, for congested roads enforcing bicycle lanes may degenerate the network, making the idea very hard to sell both to the pub- lic and the traffic authorities.
The primary objective of this project is to create a multicriteria indicator that assesses the suitability of the existing urban network for cycling. And to develop a methodology which, from that index, helps the responsible entities to improve the cycling conditions of their urban network and select the best places for the creation of new bike lanes. By suitability, we mean non-subjective factors that characterise the suitability of a route for cycling, including safety, traffic volumes, traffic speeds, presence of bicycle lanes, whether the terrain is flat or hilly, etc.
The final objective is to incorporate this cyclical indicator into the Soft Accessibility City Index – Cityndex – developed in our previous project.
