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- An Advertising Real-Time Intelligent and Scalable Framework for Profiling Customers EmotionsPublication . Alves, Leandro; Oliveira, Pedro; Henriques, João; Bernardo, Marco V.; Wanzeller, Cristina; Caldeira, FilipeThe advertising industry is continuously looking up for effective ways to communicate to customers to impact their purchasing. Usually, profiling them is a time-consuming offline activity. Therefore, it becomes necessary to reduce costs and time to address consumers’ needs. This work proposes a scalable framework enabled by a Machine Learning (ML) model to profile customers to identify their emotions to help to drive campaigns. A multi-platform mobile application continuously profiles consumers crossing the front stores. Profiling customers according to their age and hair color, the color of their eyes, and emotions (e.g. happiness, sadness, disgust, fear) will help companies to make the most suitable advertisement (e.g. to predict whether the advertising tones on the front store are the adequate ones). All that data are made available in web portal dashboards, wherein subscribers can take their analysis. Such results from the analysis data help them to identify tendencies regarding the culture and age, and drive companies to fit front stores accordingly (e.g. to discover the right tones for the season). This framework can help to develop new innovative cost-effective business models at scale by driving in real-time the advertisements to a huge number of consumers to maximize their impact and centralizing the data collected from a large number of stores to design future campaigns.
- A Scalable Smart Lighting Framework to Save EnergyPublication . Rebelo, João; Rodrigues, Ricardo; Henriques, João; Gonçalves Cardoso, Filipe; Wanzeller, Cristina; Caldeira, FilipeIn the past few decades, the urbanization area increased significantly, requiring enhanced services and applications to improve the lifestyle of its citizens. Lighting is one of the most relevant infrastructures due to its impact on modern societies, but it is also complex to manage them in cities since it involves a massive number of widespread posts and is costly as the result of the consumption of significant amounts of energy. In that regard, this work proposes a scalable framework to manage a significant huge number of lamp posts. Its purpose is to give support to collecting large amounts of sensor data to help to analyze and efficiently fit the light intensity level to the space the posts are covering. Luminosity sensors are used to optimize the intensity of light needed in the urban areas. The proposed framework explores the concept of smart cities by combining the data collected from sensors plugged into IoT (Internet-ofThings) devices. The proposed framework offers the capability to extend and integrate new services to different domains with each other which enhances the quality and performance of urban services. To demonstrate the feasibility of the framework, a simulation was put in place.
- A Scalable Framework to Predict Bitcoin Price Using Support Vector MachinePublication . Monteiro, Stéphane; Oliveira, Diogo; António, João; Henriques, João; Martins, Pedro; Wanzeller, Cristina; Caldeira, FilipeStock analysts have been predicting other stocks prices in financial markets by understanding their patterns. Bitcoin is an example of cryptocurrency that has grow enormously since 2020 despite being in the market since 2009. However, cryptocurrencies are volatile and sensitive to thousands of factors and consequently is complex for humans to make predictions even more when those predictions should occur in a daily basis, requiring hence a significant effort. Due to this fact, investor profiles prefer long-term investments which can constraint their revenues. To overcome the aforementioned scenario this work proposes a scalable framework relying in Support Vector Machine (SVM) algorithm to predict the price of bitcoin by automatically collecting and cleaning the data directly from the Web to process the dataset as input for training. This framework can also leverage new business models at scale by assisting the investors aiming realize its value in short periods in a continuous fashion.