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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.
- NoSQL Scalability Performance Evaluation over CassandraPublication . Abbasi, Maryam; Sá, Filipe; Albuquerque, Daniel; Wanzeller, Cristina; Caldeira, Filipe; Tomé, P.; Furtado, Pedro; Martins, PedroThe implementation of Smart-Cities is growing all over the world. From big cities to small villages, information able to provide a better and efficient urban management is collected from multiple sources (sensors). Such information has to be stored, queried, analyzed and displayed, aiming to contribute to a better quality of life for citizens and also a more sustainable environment. In this context it is important to choose the right database engine for this scenario. NoSQL databases are now generally accepted by the database community to support application niches. They are known for their scalability, simplicity, and key-indexed data storage, thus, allowing an easy data distribution and balancing over several nodes. In this paper a NoSQL engine is tested, Cassandra, which is one of the most scalable, amongst most NoSQL engines and therefore, a candidate for use in our application scenario. The paper focuses on horizontal scalability, which means that, by adding more nodes, it is possible to respond to more requests with the same or better performance, i.e., more nodes mean reduced execution time. Although, adding more computational resources, does not always result in better performance. This work assesses how each workload (e.g., data volume, simultaneous users) influence scalability performance. An overview of the Cassandra database engine is presented in the paper. Following, it will be tested and evaluated using the benchmark Yahoo Cloud Serving Benchmark (YCSB).
- An Intelligent and Scalable IoT Monitoring Framework for Safety in Civil Construction WorkspacesPublication . Ferreira, Carolina; Correia, Luciano; Lopes, Manuel; Henriques, João; Martins, Pedro; Wanzeller, Cristina; Caldeira, FilipeKeeping civil construction workers safe is an important challenge due to working conditions and low technological support due to the inherent costs. This work surveys the literature and proposes a scalable framework for monitoring workers to minimize the response time with real-time warnings in hazardous situations or safety incidents. From the literature, it was possible to devise a gap in business addressing this problem. To address this problem, this work proposes an IoT scalable framework able to scale to a large number of civil construction companies with a large number of workers in order. The results from this work demonstrate the feasibility of the proposed framework and the low cost of the IoT solution and the scalability of the framework offers the opportunity to leverage new innovative business models capable to leverage their revenues.
- CityMii - An integration and interoperable middleware to manage a Smart CityPublication . Cecílio, José; Caldeira, Filipe; Wanzeller, CristinaModern cities are supported by multiple heterogeneous IT systems deployed and managed by distinct agents. In general, those systems use old, dependent and non-standardized technologies, which make them legacy and incompatible systems. As smart cities are moving toward a fully centralized management approach, the lack of integration among systems raises several problems. Since they are independent, it is not easy to correlate information from different systems and put it together to work in order to achieve application goals. The collaboration among different systems enables an agent to offer new functionalities (services or just information about the city) that cannot be provided by any of these systems working as individual entities. The goal of this paper is to propose an integration middleware to support the management of Smart Cities in a dynamic, transparent and scalable way. The proposed middleware intends to support interoperability among different systems operating in a city.
- 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.
- Analysis and real-time data of meteorologic impact on home solar energy harvestingPublication . Ferreira, João; Lourenço, Ismael; Henriques, João; Pires, Ivan Miguel; Caldeira, Filipe; Wanzeller, CristinaSolar energy production increased in the world from 0 TWh in 1965 to 724.09 TWh in 2019. Solar energy is adopted as a source for residential renewable energy sources because, besides Biomass sources, it’s the only one that can be installed and maintained at home. Operating efficiency is an important consideration when evaluating the application of photovoltaic panels (PV) technology. A real-time system monitoring is required to analyse the current production and understand the impact of the weather conditions on PV production. This paper extends the literature on the residence solar energy harvesting subject, by providing a scalable architecture that can be used as starting point on data analysis on PV panels efficiency and how weather conditions impact energy production. A dataset was collected related to PV panel energy production, the residence energy consumption and that’s reading weather conditions. Wind intensity and direction, temperature, precipitation, humidity, atmospheric pressure and radiation were weather conditions analysed. Moreover, this data was analysed and interpreted in order to evaluate the pros and cons of the architecture as well as how the weather impacted the energy production.
- A Cost-Effective Framework for Monitoring Disaster Recovery InfrastructuresPublication . Rocha, Júlio; Lucas, Marco; Figueiredo, Ricardo; Henriques, João; Bernardo, Marco V.; Wanzeller, Cristina; Caldeira, FilipeKeeping Disaster Recovery Infrastructures (DRI) operational is vital in case of incidents. Notwithstanding, continuously monitoring them keeps a costly activity. Therefore, it is essential to have cost-effective solutions while maintaining a continuous. In that aim, this work proposes a cost-effective framework for monitoring DRI supported by an Internet of Things (IoT) device collecting data from their sensors strategically installed in the facilities to protect. In case of incidents, the framework triggers the alerts. A mobile application presents graphically, in real-time, the collected data from sensors. The physical experimentation and achieved results demonstrate the effectiveness of the framework to protect DRI. The proposed framework enabled by software to the different layers (IoT, middleware, and mobile application), and the hardware with its schematic, can help to develop innovative business models for managing DRI. The prototype of the framework produced a large dataset that can help future research on finding anomalies.
- COVID-19 Next Day Trend ForecastPublication . Costa, Marcelo; Rodrigues, Margarida; Baptista, Pedro; Henriques, João; Pires, Ivan Miguel; Wanzeller, Cristina; Caldeira, FilipeHistorically, weather conditions are depicted as an essential factor to be considered in predicting variation infections due to respiratory diseases, including influenza and Severe Acute Respiratory Syndrome SARS-CoV-2, best known as COVID-19. Predicting the number of cases will contribute to plan human and non-human resources in hospital facilities, including beds, ventilators, and support policy decisions on sanitary population warnings, and help to provision the demand for COVID-19 tests. In this work, an integrated framework predicts the number of cases for the upcoming days by considering the COVID-19 cases and temperature records supported by a kNN algorithm.
- Biometric Data Capture as a Way to Identify Lack of Physical Activity in Daily LifePublication . Marques, Luís; Lopes, Luca; Ferreira, Miguel; Henriques, João; Pires, Ivan Miguel; Caldeira, Filipe; Wanzeller, CristinaGiven the impact of the pandemic era, it is important the effects of physical activity on human beings, physically and mentally. The significant advance in the technology industry of biomedical sensors and mobile devices allowed the arrival of new health monitoring prototypes to improve people’s lives. This work implements a data capture system, using an electrocardiogram (ECG) and accelerometer (ACC) type sensor to collect a large volume of data for further analysis to obtain metrics to assess the activity level during this pandemic phase. Using a BITalino device that allows us to collect a large amount of information from various sensors, we, therefore, chose to use it as a platform to capture data from the sensors mentioned above. In the first phase, we will capture the largest possible amount of data from the subject in the test phase. Then, the collected data will be sent to a web server, where it will be processed. Finally, in a third phase, the data will be presented in a more summarized and graphical way. In this way, we will analyze the impact of movement/inactivity on the test subjects’ daily life with the referred sensors’ biometric data.
- Contacts Manager: A Mobile Web Application Consumer of Web ServicesPublication . Sousa, Artur; Wanzeller, Cristina; P. Duarte, Rui; Batista, Manuel; Soares, António; Fernandes, CarlosWith the constant innovations in the mobile devices domain, the need to make available new forms of applications is growing. We believe that this kind of devices may become large consumers of web services. Therefore, we aim to explore the development of applications for mobile devices based in web services. Our project involves the implementation of an application which allows the WAP access to the Intranet/Extranet of an information technologies company, aiming to obtain the information about its costumers, from anywhere.