Sustainable built environment under natural hazards and extreme events


Natural hazards have long been responsible for a large number of fatalities and disruptions in a society causing high economic costs. Earthquakes, tornados and flooding rank as the most costly events. Recently, the progressive effects of human-induced climate change are slowly but steadily generating increased costs to society that will continue to increase throughout the XXI century. Two additional short term anthropogenic threats at the global scale, terrorism and increased regional conflicts characterized by high fatalities and systematic destruction of the built environment adds to the previous hazards. Dealing with these hazards and their consequences is today the primary challenge of our globalized world.
The primary aim of SUSPENSE is to address this challenge that may compromise the future of mankind and constitutes a major global and EU priority. Recognizing the the very wide scope addressed by the project, the following four main focus areas of intervention are defined:
  • sustainable exploitation of sea resources (SEAFACTORY),
  • effective implementation of industrialized construction practices (INDUSTRIALIZED CONSTRUCTION),
  • development of efficient solutions for aquatic ecosystems (SEA MONITORING AND ECOSYSTEM SERVICES)
  • addressing the major problems of growing urbanization with intensive use of technology to improve the cities (SMART CITIES).


Cities are the center of economic and societal development and today over half of the world’s population resides in cities, and up to 80% is projected for 2050. Cities generate more than 80 percent of global GDP, consume 75 % of natural resources and generate 50% of global waste. Resource efficiency is therefore key for cities to contribute to local and global sustainability and offer at the same time high potential for financial savings.

This project focuses on developing and integrating new tools and services to promote urban resource efficiency with minimum environmental impacts while contributing to promote economic development and preserving actual levels of reliability. Dispersion of agents producing data at urban level leads to mixed results in applying indicators in different environments and sometimes with little gain in urban performance. This project will advance the science of urban systems modeling and data representation supported by urban “big data” collection and processing.

This project takes an integrated and application-oriented research approach by focusing on urban interventions in Lisbon, at the “Parque das Nações” test bed. This is driven by a consortia including MIT and Portuguese universities.


Urban mobility analysis and prediction for non-routine scenarios using digital footprints


In this project we propose to study individual’s mobility for mining non-routine (leisure, social, etc.) mobility patterns from multiple data sources. The following mobility patterns are of great interest: locations of significance, modes of transport, trajectory patterns and location-based activities for destination choice modelling. Data collected via ubiquitous devices and smart metering combined with data from social media platforms provides a range of new close-to-real-time information that can be combined with the data from more traditional sources (surveys, transport system records and static data) for urban efficient mobility planning and management. When considered in isolation, each of these data sources has gaps/missing observations, so the matching of multiple data sources can facilitate transport analysis, and enable operators to better tune – even on the fly – public transportation within cities with the aim of travelling at lower costs, faster and producing a smaller carbon footprint.


Social Web Information Retrieval for Crowds Mobility Management

Our cities need more efficient and dynamic planning. It has been estimated that by 2010 the cost of traffic congestion in the EU will reach 1% of the GDP. In 2007, congestion caused urban Americans to spend 4.2 billion additional hours on the road, which required an extra 2.8 billion gallons of fuel at the cost of $87.2 billion. These figures represent an increase of more than 50% in overall costs over the previous decade. Special events (strikes, gatherings, shows) represent only a small percentage of total traffic congestion but are responsible for very high and costly disruptions because they cause unexpected delays which neither travelers nor authorities are able to accurately predict.

Transportation planning has traditionally ignored such events focusing on average traffic impacts of land-use developments. Trip generation indicators are used for estimating trip ends for several types of venues, mainly large scale venues such as stadiums or conference centers. But it is impossible to predict event-specific impacts of those uses. Having an adolescent idol playing at a concert hall is not the same as having an orchestra: the number and behavior of the attendees changes radically. InfoCrowds explores the interactions between online information about public events, mobility data and event specific surveys to build explanatory and predictive models of flows of people, and their transportation mode, in the city.


Knowledge Unsupervised Search for populating
Concepts on Ontologies

KUSCO is a system which aims to assign semantic annotations to places. These annotations are automatically extracted by applying natural language processing and information extraction techniques that have been thoroughly applied and tested using the World Wide Web as primary source. This process is formally named Semantic Enrichment of Places. In our case, we are particularly focused on extracting information that allows an interpreter to distinguish a place from other places that are spatially or conceptually close. In other words, the meaning of a place is a function of its most salient features, present in the textual descriptions found in on-line resources about that place. In our case, places correspond to Points Of Interest (POIs), as these are abundant in the Web. By definition, a POI is a place with meaning to someone and, if it is available on-line, it is likely that its interest is shared by many people. In our approach, we first crawl the Web to get a large quantity of POIs and then analyze each of them in order to obtain their individual Semantic Index: the set of words that best define each of them. Besides analyzing POIs, we also propose the application of such approach in several different contexts and we integrate them in a multi-faceted view of place.


Understanding urban land use from digital footprints of crowds

The established view on semantic organization of space is based on the concept of “land use”, which corresponds to an aggregate perspective on the use of an area (e.g. agriculture, residential, business, etc.). The characterization of urban block is built on the human activities that happen there, however a more disaggregated and dynamic view is now possible due to availability of new techniques and technologies. In fact, this should become a more natural way to profile the places.

Understanding population dynamics by type, neighborhood, or region would enable customized services (and advertising), as well as the accurate timing of urban service provisions, such as scheduling transit service based on daily, weekly, or monthly mobility demand. In general, more synchronous management of service infrastructures clearly could play an important role in urban mobility management. Traditionally, urban planning relies on census survey conducted every 5-10 years and has shortcomings both in terms of spatial and temporal scale. The wide deployment of pervasive computing devices (cell phone, smart card, GPS devices and digital cameras) provide unprecedented digital footprints, telling where and when people are. In former projects, we developed a methodology for detecting the presence and movement of crowds through their digital traces (flickr photo, cell phone logs, smart card record and taxi/bus GPS traces).

This fine grained analysis, up to the level of the establishment, makes a big leap in terms of understanding the use of space for the purposes of urban planning and management. In recent work, we have presented several perspectives on extracting semantics of the place from online information. A further step shapes on the intersection of such generic information about space with other digital footprints, such as cell phone usage or taxi demand. An essential scientific contribution of this proposal will be on development of new techniques for land use analysis supported on semantic enriched POIs.


COllaborative System for Mobility Optimization

We are nowadays observing a rapidly growing availability of route planning devices, and it is expectable that they soon become an indispensable driving assistance technology (as happened with ABS, Airbags or ESP). On the other hand, the importance of congestion in cities throughout the world is rising for a number of reasons, especially those linked to carbon emissions and oil prices. A well known issue that consistently leads to congestions is the natural “selfishness” of each driver: each individual is following the “theoretically” fastest route. Even with the highly sophisticated support of systems such as “TomTom IQ routes”, every query for the same route from point A to B at the same time window will lead to the same result. The massive use of such a system will lead, inevitably, to congestion. Different from this extreme scenario, a more realistic expectation is that the majority of the users will only use their route planners when faced with novel origins-destinations. Since less information is used and the same path tends to be repeated, it will even worsen the situation. Thus, solutions need to be sought that compensate the effects of driver selfishness and lack of information.

In this project we propose to look at the city as a Complex System, where each citizen/driver is an agent with a local vision of the environment. The principle is to use heterogeneous information collected on city mobility (GSM, GPS, Road Sensors, Information Services, Historical data) to exercise influence on the individual agent behavior in order to optimize the city efficiency (e.g. energy consumption). This way, when reaching pre-congestion levels of network charge, individual drivers will be lead to collaborate in alternative, and minimally competing, routes. In this scenario, several research challenges are raised:

  • How to predict distributed network load? In order to prevent the appearance of congestions, these situations have to be detected in early phase of their formation, and the individual behavior of the agents should be led to a synchronized collaborative behavior in a way that increases the whole system efficiency.
  • How to fairly synchronize drivers? The system cannot favor one driver over the other more than within reasonable limits. Mutual dependencies will increase considerably the complexity of the choice.
  • How to communicate with individual drivers? Will it be realistic to assume that high quality wireless access will be available in every vehicle? Or would the traditional Variable Message Signs become a proper option? If so, where should these signs be placed?

These challenges will be tackled from the perspective of Complex Systems, Ubiquitous Computing and Intelligent Transport Systems, which are three areas in which the research team already has or is acquiring strong knowledge.

The main purpose of this project is to study these issues and develop a collaborative traffic routing/control system. The system should use the collected information to predict realistic traffic network load and present advice to users, by providing individually tailored network loads, in order for them to have a less selfish behavior. The developed system is to be applied in a controlled micro simulation environment, which will allow the testing and validation of the various aspects of research, as well as the study the behavior of the system according to a number of dimensions, including driver adherence rate, link capacity, driver profiles and synchronism model. The project is divided into three main tasks (not performed necessarily in sequential order, and revisited when necessary):

  • Realistic setting build-up: A traffic micro-simulation platform must be chosen (e.g. MITSIMLab, SUMO), as well as a number of network scenarios. Aside from the academic ones (e.g. grid, spider web), we expect to use the networks of Lisbon, Porto and Coimbra. Realistic Origin-Destination matrices are also needed from these cities, in order to obtain believable predictions.
  • Algorithm design: Starting with traditional and state of the art solutions, the project team will seek for the best solutions both in terms of efficiency and in terms of precision. The long experience of the team in Vehicle Routing, Evolutionary Computation, Map Matching, Geo-referenced applications and Advanced Programming techniques will certainly be precious in this search.
  • Experimentation and tuning: After functional testing of the system, and when it reveals robustness, the experimentation phase will take place focusing on comparing the simulation results with other approaches and with traditional models from Transport Demand Management theory, namely the four steps model of transport forecasting (see literature review).

The team will comprise two experts in Complex Systems with strong experience in Route Planning and Vehicle Routing Problem research (Francisco B. Pereira, ISEC; Jorge Tavares, MIT), one from Ambient Intelligence and Intelligent Transport Systems (Francisco C. Pereira, FCTUC) and one from Artificial Intelligence (F. Penousal Machado, FCTUC).


one.stop.transport – Advanced communication systems
for transportation

The project´s mission involves exploring new, more efficient and comprehensive solutions for urban transportation, through the use of communication and information technologies (CIT) to make it possible to integrate the various available solutions, in an ecological, energy-efficient way with better quality for users, in combination and cooperation with other domestic initiatives.

The mission shall be brought about along 4 lines of action, which shall group the various sub-projects, ad whose objectives, so-called Technical Objectives [TO´s], are listed below:

  • Increasing acceptance and adopting new solutions and technologies for urban transportation [TO1];
  • A more comprehensive urban transportation system providing better access for everyone [TO2];
  • Reducing CO2 emissions, pollution and noise emissions, at least in conformity with E.U. legislation [TO3];
  • Increasing energy efficiency in urban transportation [TO4];
  • Reducing the number of private vehicles in an urban setting [TO5];
  • Exploring synergies and means of cooperating with other CCT’s and their partners [TO6].


TICE.Healthy – Systems of Health and Quality of Life

The TICE.Healthy – Systems of Health and Quality of Life project seeks to develop, integrate and test innovative technological approaches that will serve as a basis for new products and services for markets linked to the aspect of “Health and Quality of Life.” TICE.Healthy’s mission is to being about the presence of Portuguese companies and organizations, and, in particular, those of the CCT TICEs, in global markets in the field of strategy of TICE.PT called “Health and Quality of Life”. The mission shall be brought about along 4 lines of action, which shall group the various sub-projects, ad whose objectives, so-called Technical Objectives [TO´s], are listed below:

  • Creating condition for safety, surveillance and self-control in a hospital environment [TO1];
  • Increasing patients’ autonomy and reducing their stay in a hospital environment [TO2];
  • Developing key technologies, such as biosensors and secure communications and their integration in systems to be worn or implanted, thereby providing both citizens and health-care professionals with an omnipresent management of their health status [TO3];
  • New reliable software tools providing support to health-care professionals so they can immediately make the best possible decision, for prevention, diagnostic and treatment purposes [TO4];
  • Interoperability of eHealth systems (integrated information in terms of both diagnosis and process) [TO5];
  • Developing technologies and products for personalized, continuous treatments, with patients actively participating in prevention and treatment [TO6];
  • Developing remote diagnosis and treatment solutions for specific conditions (cardiovascular diseases, diabetes, kidney and liver ailments, among others) [TO7];
  • Developing IT-based solutions for providing support to people with mental illness and stress [TO8].


The project InovWine aims to increase the overall competitiveness of the wine sector through the development of new products and services to the row of the wine and vineyard.It is intended specifically:

  • Develop a system for genotyping, selection and certification based on molecular methods.
  • Implement a control system and remote monitoring of biotic and abiotic factors associated with the vine which will feed a system of risk detection, warning and prevention of plant diseases.
  • Create a collection of wine yeast adapted to regional conditions and market requirements and develop a device for monitoring their dynamics during fermentation.

It is hoped that this project will maximize the effective transfer of technology between research institutions and business associates, contributing to a better utilization of natural resources in the region and leading to the development of new technologies in the future, will underpin the international competitiveness sector.