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Financed by ALGARVE 2030, Portugal 2030 and by the European Union, ALGARVE-FEDER-01180500, Ref. 17325
Promotor SPIC - Sonha Pensa Imagina Comunica, Lda., co-promotor University of the Algarve (ISE)
1 Jan. 2025 - 31 dez. 2027
Synopsis
Digital platforms for tourism, cultural experiences, and events, including platforms that connect the population (tourists or locals) to creative and cultural experiences, are increasingly critical. The AI.EVENT project aims to develop an innovative platform that uses artificial intelligence (AI) to track and analyze audience engagement during physical events. The platform will provide event organizers valuable insights into audience engagement and behaviour metrics, allowing them to make data-driven decisions to improve their events' effectiveness and impact. The target audience of this product is agencies, event organisers, and planners. The main message of the product to this audience is to "Elevate your event with AI-powered analytics," and the main key objectives are: Take the guesswork out of the event planning with our AI-based analytics product; Get real-time insights into attendee behaviour metrics and engagement levels; Provide tools to event organizers to optimize the event and create more personalized and engaging experiences for the attendees; Seamless integration with third-party event software.
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Team UAlg
Professors
Research Grants / Collaborators
Marco Lemos Research Grant PhD#1 - 01/05/2025 (WP#1)
Mohamed El Afia Research Grant PhD#2 - 01/07/2025 (WP#2)
Marco Lemos Collaborator MSc#1 (WP#1)
Gilherme António Collaborator MSc#2 (WP#2)
Localization: UAlg, ISE, Visual Computing Lab., Room 163
ACKNOWLEDGES: This work is supported by the project AI.EVENT: Monitor Live Audience with AI (ALGARVE-FEDER-01180500, Ref. 17325) co-financed by ALGARVE 2030, Portugal 2030 and by the European Union.
Publications
Journal
Conferences
Lemos, M., Cardoso, P.J.S., Rodrigues, J.M.F. (2025). Microscopic Binary Engagement Model. In: Lees, M.H., et al. Computational Science – ICCS 2025. ICCS 2025. Lecture Notes in Computer Science, vol 15905. Springer, Cham. https://doi.org/10.1007/978-3-031-97632-2_9
Turner, D., Cardoso, P.J.S., Rodrigues, J.M.F. (2025). Modular Dynamic Neural Network with Swin Transformer and AutoML. In: Antona, M., Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. HCII 2025. Lecture Notes in Computer Science, vol 15780. Springer, Cham. https://doi.org/10.1007/978-3-031-93848-1_26
Rodrigues, J.M.F., Cardoso, P.J.S., Lemos, M., Cherniavska, O.V. & Bica, P. (2025) Engagement Monotorization in Crowded Environments: A Conceptual Framework, in Procs 11th International Conference on Software Development and Technologies for Enhancing Accessibility and Fighting Info-exclusion, Abu Dhabi, UAE. DOI: https://doi.org/10.1145/3696593.3696632
Thesis
PhD#1: Marco Lemos (Mar. 2025 -) Real-time Engagement Framework for Group, PhD in Informatics Engineering, Universidade do Algarve (on-going).
PhD#2: Mohamed El Afia (June 2025) Engagement, Attention and Behaviour Analysis in Crowd Events, PhD in Informatics Engineering, Universidade do Algarve (on-going).
MSc#1: Marco Lemos, (2025) Engagement Models to Monitor Brand Activation, Master's degree in Electrical and Computer Engineering, Instituto Superior de Engenharia, Universidade do Algarve.
MSc#2: Guilherme António (Set. 2024 -) AI-Powered Detection of Abnormal Behaviour in Crowds, Master's degree in Electrical and Computer Engineering, Instituto Superior de Engenharia, Universidade do Algarve (on-going)
Press
RTP (minute 5.30 to 8.00) https://www.rtp.pt/play/p14639/e852706/europa-a-porta (2025/05/25) or https://youtu.be/lMFf7w6BBvI?si=5do5d9RdfpK5arVM
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