Ongoing Challenges

The data itself has no value, the value derives from its use or, more specifically, when through its processing we are able to create information that supports decision making

True urban intelligence will only happen when those who govern the territory are able to establish strategies that lead to the construction of the city as a platform, creating the necessary and sufficient conditions to, taking advantage of information management and data science leveraged in big data, radically change the paradigm of planning and management of our cities and towns.

But the data itself has no value, the value stems from its use or, more specifically, when through its processing we are able to create information that supports decision making and leads to action (information is given in context).

In this sense, on this page, you can consult some of the data analytics and visualization solutions supported in big data that are still under development for the various partners of NOVA Cidade – Urban Analytics Lab and that are open to contributions and participation of interested researchers.

AI Generated News: Unleashing the Power of AI in Local Journalism

This master’s thesis challenge aims to explore the application of generative language modelling techniques in the context of local news generation. The project will focus on developing a framework to generate realistic and coherent local news articles. The research will involve collecting a large corpus of local news data, preprocessing and cleaning the data, training and fine-tuning a generative language model, and evaluating the generated output using metrics such as fluency, coherence, and relevance. The skills required for this challenge include proficiency in Python programming, experience with deep learning frameworks (e.g., PyTorch), and a solid understanding of natural language processing techniques.

Data sources: The challenge can utilize various data sources, such as API, news portals’ web scraping potentially other relevant data sources available through open data initiatives or partnerships with local news companies.

Skills: Natural Language Processing, information retrieval, data preprocessing, web scraping, Python programming, Large Language Models, Pytorch, Promp Engineering

NOVA IMS Assistant: Enhancing Information Access and Campus Engagement through an Intelligent Chatbot

This master’s thesis challenge aims to design and develop an intelligent chatbot tailored specifically to NOVA Information Management School (NOVA IMS). The goal is to create an intuitive community question answering (CQA) platform that facilitates information retrieval and fosters engagement within the NOVA IMS community. The chatbot will leverage natural language processing techniques to understand and respond accurately to queries related to various aspects of the school, including courses, programs, faculty, events, facilities, and administrative procedures. By providing prompt and context-aware answers, the chatbot will enhance information access, streamline campus communication, and promote a seamless user experience for students, faculty, and staff.

Data sources: The challenge can utilize various data sources, including existing FAQs and documentation from NOVA IMS, official school websites, course catalogs, event calendars, faculty profiles, and relevant administrative resources.

Skills: Natural Language Processing, information retrieval, data preprocessing, web scraping, Python programming, Large Language Models, Pytorch, Promp Engineering

Analysis of patterns on the evolution of local accomodation - Powered by OesteCIM

Local accommodation analysis in Portugal offers valuable insights into the changing landscape and trends within the lodging industry. By closely examining the patterns and trends in the development and utilization of local accommodations, stakeholders can gain a comprehensive understanding of the factors shaping this sector’s growth and performance. This analysis involves evaluating factors such as the number of accommodations, occupancy rates, pricing trends, and the impact on tourism demand. By identifying patterns in the evolution of local accommodation, stakeholders can make informed decisions about investment opportunities, market positioning, and the development of strategies to cater to the evolving needs and preferences of travelers. Ultimately, this analysis supports the sustainable development of the local accommodation sector in Portugal, ensuring its competitiveness and contribution to the overall tourism industry.

Data sources: local accomodation registries

Skills: statistical analysis, geographic information systems, data visualization, reporting

Analysis of patterns of business companies performance - Powered by OesteCIM

Patterns of business companies’ performance in the Oeste Region of Portugal yields valuable insights into the economic landscape and competitive dynamics specific to this region. By examining key economic indicators, financial performance metrics, market dynamics, and sector-specific strengths, stakeholders can gain a comprehensive understanding of the factors shaping business success and growth in the area. This analysis enables informed decision-making, resource allocation, and the formulation of tailored strategies to capitalize on emerging opportunities and address challenges within the Oeste Region’s business environment, ultimately fostering sustainable economic growth and development.

Data sources: Companies economic activity indicators

Skills: statistical analysis, geographic information systems, data visualization, reporting

Analysis of pass sales and traffic patterns of public road transport - Powered by OesteCIM

The Portuguese Intermunicipal Community of the West (OesteCIM) is a public entity whose mission is to contribute to the promotion of sustainable development and the improvement of quality of life in its municipalities. Its vision is to be an Intermunicipal Community of national reference for excellence in public management oriented towards quality, innovation, efficiency and effectiveness, optimizing existing resources and structures. 

Through the processing and analysis of data from the operational systems that manage pass and ticket sales, as well as validations and traffic on the road network, the objective of this challenge is to develop analytical models and visualization tools to characterize pass sales. and traffic patterns of public road transport at OesteCIM. 

Analysis of monetary transactions and characterization of consumption - Powered by OesteCIM

The Portuguese Intermunicipal Community of the West (OesteCIM) is a public entity whose mission is to contribute to the promotion of sustainable development and the improvement of quality of life in its municipalities. Its vision is to be an Intermunicipal Community of national reference for excellence in public management oriented towards quality, innovation, efficiency and effectiveness, optimizing existing resources and structures. 

Through the processing and analysis of data from the operational systems of monetary transactions via ATM card, the objective of this challenge is the development of analytical models and visualization tools for the characterization of consumption and the consumer at OesteCIM.

Characterization of commuting movements on the main access routes to the city

Description

The characterization of traffic in the municipality is something fundamental to plan life in the city of Lisbon, particularly with regard to the volume of people entering it daily during the morning (7:30am-10:00pm) and afternoon (5:00pm-7:30pm) rush hours, which generates traffic on the main access roads. For the 11 main entry and exit points of the city there are data that allow us to know the number of mobile devices entering and exiting through each of these points every 15-minute period. The challenge is to try to characterize these daily flows during the two periods mentioned and their relationship to factors such as school calendars and rainfall.

Expected results

Among other results that the participants in the challenge may find interesting, namely by using other data sources, it is intended to know the following:

A. For the morning rush hour period (7:30am-10:00pm)

  • Characterize the total volume of entries and exits from the city during the rush hour period,
  • Characterize the volume of entries and exits from the city during the peak hour period for each of the 11 entry and exit points,
  • Compare with other periods of the day,
  • Relate the previous point with variables such as school calendars and the occurrence of rainfall,
  • Analysis of the zones of origin of those entering the city,
  • Analysis of the destination zones of those leaving the city

B. For the afternoon peak period (5:00pm-7:30pm)

  • Characterize the total volume of entries and exits from the city during the peak hour period,
  • Characterize the volume of entries and exits from the city during the peak hour period for each of the 11 entry and exit points,
  • Compare with other periods of the day,
  • Relate the previous point with variables such as school or vacation periods and the existence of rainfall,
  • Analysis of the destination zones of those leaving the city,
  • Analysis of the zones of origin of those entering the city.

Promotor / Recipient of the found solution

CGIUL – Centro de Gestão e Inteligência Urbana de Lisboa (Lisbon Center for Urban Management and Intelligence)

Data to be made available

  • Number of cell phones entering and exiting the city every 15 minutes on the 11 main entry axes into the city of Lisbon – Axes of the city of Lisbon;
  • Identification of the 11 entry and exit points of Lisbon;
  • Observations from IPMA’s weather stations in Lisbon: Geofísico, Gago Coutinho and Tapada da Ajuda;

Additional information

School calendar

Sentiment Analysis of Tourists' Social Media Data for Urban Mobility in Lisbon

This master’s thesis challenge aims to analyze the sentiment of tourists’ social media posts to gain insights into the perception and experiences related to urban mobility in Lisbon. The challenge involves collecting and preprocessing social media data from platforms like Twitter and Instagram, utilizing APIs or web scraping techniques. The gathered data will be used to train a sentiment analysis model tailored to Lisbon’s context, considering aspects such as traffic congestion, public transportation usage, and popular destinations. The analysis will provide valuable information to improve urban mobility infrastructure and enhance tourists’ experiences in Lisbon.

Data sources: Twitter API, Instagram API, web scraping techniques for social media data retrieval.

Skills: Natural Language Processing, sentiment analysis, data preprocessing, Python, Machine Learning

Chatbot for Lisbon: Enhancing Information Access and Community Engagement

This master’s thesis challenge focuses on designing and developing an intelligent chatbot specifically catered to the needs of residents and visitors in Lisbon. The goal is to create a user-friendly community question answering (CQA) platform that empowers users to seek information and engage with the local community. The chatbot will utilize natural language processing techniques to understand and respond accurately to queries related to various aspects of the city, including local events, transportation, dining options, cultural activities, and more. The platform will provide timely, context-aware answers, facilitating knowledge sharing, and enhancing the overall experience of individuals interacting with the city of Lisbon.

Data sources: The challenge can utilize various data sources, such as existing FAQs, official tourism websites, open data initiatives from Lisbon City Council, local event listings, restaurant directories, and cultural activity databases.

Skills: Natural Language Processing, information retrieval, data preprocessing, web scraping, Python programming, Large Language Models, Pytorch, Promp Engineering

Analysis of docked bike sharing service in the city of Lisbon

The analysis of the docked bike sharing service in the city of Lisbon provides valuable insights into the patterns and impact of this transportation alternative. By closely examining the usage patterns, ridership trends, and infrastructure requirements of the docked bike sharing system, stakeholders can gain a comprehensive understanding of its effectiveness in promoting sustainable urban mobility. This analysis involves evaluating factors such as user adoption rates, trip durations, popular routes, and the integration of bike sharing with existing transportation networks. By understanding the patterns and dynamics of the docked bike sharing service, stakeholders can make informed decisions about expanding the network, optimizing station locations, and improving user experience. Ultimately, this analysis supports the development of evidence-based strategies to enhance the bike sharing service in Lisbon, promoting environmentally friendly transportation options and contributing to the city’s sustainable mobility goals.

Data sources: bike docks occupation ratio from the GIRA service

Skills: statistical analysis, geographic information systems, data visualization, reporting

Analysis of use of recycling rewarding system - Powered by OesteCIM

The use of a recycling rewarding system in the Oeste Region of Portugal provides valuable insights into the effectiveness and impact of incentivizing recycling behaviors. By closely examining the patterns and trends within the implementation of such a system, stakeholders can assess its effectiveness in promoting sustainable waste management practices. This analysis involves evaluating factors such as participation rates, recycling rates, and the overall environmental impact. By understanding the patterns of adoption, engagement, and success of the recycling rewarding system, stakeholders can make informed decisions about optimizing the program, expanding its reach, and identifying potential areas for improvement. Ultimately, this analysis supports the development of evidence-based strategies to encourage and incentivize recycling behaviors, contributing to the region’s environmental sustainability goals.

Data sources: Reverse vending machines collected information (number of users, number of packages recycled, dicscounts)

Skills: statistical analysis, geographic information systems, data visualization, reporting

Analysis of alerts, incidents and traffic patterns - Powered by OesteCIM

The Portuguese Intermunicipal Community of the West (OesteCIM) is a public entity whose mission is to contribute to the promotion of sustainable development and the improvement of quality of life in its municipalities. Its vision is to be an Intermunicipal Community of national reference for excellence in public management oriented towards quality, innovation, efficiency and effectiveness, optimizing existing resources and structures. 

Through the processing and analysis of data from the WAZE application, the objective of this challenge is the development of analytical models and visualization tools for the characterization and prediction of traffic patterns, alerts and incidents at OesteCIM.

Analysis of climate change and carbon neutrality - Powered by OesteCIM

The Portuguese Intermunicipal Community of the West (OesteCIM) is a public entity whose mission is to contribute to the promotion of sustainable development and the improvement of quality of life in its municipalities. Its vision is to be an Intermunicipal Community of national reference for excellence in public management oriented towards quality, innovation, efficiency and effectiveness, optimizing existing resources and structures. 

Through the processing and analysis of data from operational systems to adapt to climate change, the objective of this challenge is to develop analytical models and visualization tools to characterize climate change and carbon neutrality goals at OesteCIM.

Movement of people in nightlife areas

Description

Nightlife areas with strong occupation of public space have a great impact on the life of the city and its management is important in order to respond to the interests of various stakeholders, including merchants, residents and users. In this way, and using data from mobile devices, we intend to know the movement and permanence of people between nightlife areas. Given the economic interest of tourism and the impact of tourists on nightlife areas, this analysis will also include data on roaming mobile devices. It is also of interest to know the effects of these movements of people on the outdoor noise environment, namely to know the evolution of the values of the parameter equivalent continuous sound level (LAeq).

Expected results

In addition to other information that may result from the data analysis, with this challenge it is intended to:

1 – Determine the time period and the grid squares in which the use of public space ceases to be normal and becomes related to nighttime entertainment activities in public spaces (outdoors),

2 – For the grid squares and time periods identified in the previous point (these periods can be variable from zone to zone) characterize, among other aspects, the following variables throughout the period of nightlife fun

  • permanence of residents and tourists,
  • mobility in nightlife areas,
  • assessment of possible transfers of users between nightlife areas,

3 – Relate the movements of people with the noise levels recorded in the environmental sensors located in the study area considered.

Promotor / Recipient of the found solution

CGIUL – Centro de Gestão e Inteligência Urbana de Lisboa / Direção Municipal do Ambiente, Estrutura Verde, Clima e Energia (Lisbon Center for Urban Management and Intelligence / Municipal Department of Environment, Green Structure, Climate and Energy)

Data to be made available

  • Number of cell phones entering, staying and leaving per 200m/200m grid in a 5 minute period – Lisbon city grid;
  • Mapping of Vodafone’s grid cells;
  • Environmental sensors (noise);
  • Location of nightlife establishments.
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