Browsing by Author "Mota, David"
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- An Overview on Cloud Services for Human TrackingPublication . Martins, Manuel; Mota, David; Martins, Pedro; Abbasi, Maryam; Caldeira, FilipeThis paper reflects the intention to test the use of public cloud services to assess the presence of humans in a given space, more precisely, multiple stores, with the least effort and in the fastest way. It is also intended to demonstrate that the use of the public cloud can be an instrument of added value in business areas and research areas. In the specific case, the cloud was used to train and use artificial intelligence models.
- Are you lost? Using Facial Recognition to Detect Customer Emotions in Retail StoresPublication . Borges, Valter; P. Duarte, Rui; Cunha, Carlos; Mota, David; ThinkmindThe understanding of consumer behavior is a dynamic field, especially relevant to the success of companies and for consumer satisfaction. It is especially important in the situation of intense competition, currently characteristic for the retail store industry, where companies fight for every individual customer. Moreover, companies do not want customers to enter their system and leave without buying products they intended to buy. This has an impact on user satisfaction and retail stores income. In this paper we present a method that targets customer satisfaction in the aforementioned context using a facial recognition system acting at the emotional level of the customer. Our method is based on cumulative negative emotions that are associated to a sadness level, which triggers events for retail store assistants to help customers. Results show that this method is adequate to measure these emotions and is a useful reference for retail store assistant intervention.
- Behavioral Anomaly Detection of Older People Living IndependentlyPublication . Cunha, Carlos; P. Duarte, Rui; Mota, DavidOlder people living independently represent one significant part of the population nowadays. Most of them have family or friends interested in being informed about changes in their routine. Considering these changes signal some physical or mental problem, they can trigger a contact or action from the interested persons to provide support. This paper presents an approach for non-intrusive monitoring of older people to send alerts after detecting anomalous behaviors. An analysis of seven months of data gathered using PIR sensors in a couple’s living house has shown regularities in their presence in compartments along the day. We validated the adequacy of an outlier detection algorithm to build a model of the persons’ behavior, exhibiting just 3.6% of outliers interpreted as false positives.
- International Conference on Tourism and Social Support TechnologiesPublication . Santos, Fernando Miguel Soares Mamede dos; Café, Afonso Pedro Ribeiro; Carvalho, Ana Branca; Guedes, Anabela; Pereira, Andreia; Oliveira, Ângela; Silva, Carla; Lemos, Carlota; Seabra, Cláudia; Gomes, Cristina Azevedo; Mota, David; Fidalgo, Filipe; Sousa, João; Vidal, João; Pinho, José Carlos; Lousado, José Paulo; Pereira, José; Gambardella, Luca Maria; Pato, Lúcia; Shafik, Mahmoud; Brito, Manuel; Ferrer, María Belén; Martins, Nayra; Dionísio, Nuno; Pinho, Nuno; Santos, Paula; Duarte, Paulo; Rito, Pedro; Rocha, Pedro; Silva, Pedro; Gomes, Raquel; Montemanni, Roberto; Antunes, Sandra; Sotomayor, Silvia Feliu Álvarez de; Chou, Xiaochen