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- Smart Campus Parking – Parking Made EasyPublication . Vieira, Amanda; Rosa, Iolanda; Santos, Ivo; Paulo, Tiago; Costa, Nuno; Maximiano, Marisa; Reis, Catarina I.The number of users of the parking lots from the campus of the Polytechnic of Leiria, a higher education institution in Portugal, has been increasing each year. It is becoming a major concern to the organization to address the high demand for a free parking spot on campus. In order to ease this problem, this paper proposes the design of a smart parking system that can help users to easily find a free parking spot, using an integrated system that includes sensors and a mobile application. The system is based on the information about the occupation status of parking lots generated by parking sensors. This information is available in the mobile application that consumes a REST webservice and is presented to end-users, thus contributing to the decrease of time wasted on the quest of finding a free spot. The software architecture consists on a set of decoupled modules that compute and share the information generated by sensors. This architectural approach is noteworthy because it maximizes the system scalability and responsiveness to change. It allows the system to expand with the integration of new applications and perform updates on the existing ones, without an overall impact on the operations of the other system modules.
- Real-Time Low-Cost Active and Assisted Living for the ElderlyPublication . Almeida, António Henrique; Santos, Ivo; Rodrigues, Joel; Frazão, Luis; Ribeiro, José; Silva, Fernando; Pereira, AntónioThe aging of population in recent years and the increase in life expectancy is raising challenges for finding new ways to guarantee healthy and controlled activities for the elderly. Most of them prefer living in their houses than in a community center, even if they live alone or isolated from their family; at home, their normal routine activities and comfort makes them feel well. In this paper, an Active and Assisted Living (AAL) solution to detect irregular situations in everyday life of the elderly living alone is presented. By using low-cost sensors in an Internet of Things (IoT) architecture we aim to gather data in specific areas of an elderly’s house in order to give the system enough input to detect abnormal behavior. These sensors are non-intrusive to the elderly, do not disturb them, and do not force them to wear a device at all times. These sensors can also send information to edge computing devices that analyze the data in real time using machine learning algorithms and alert family or caretakers when an unusual situation arises. The proposed solution provides a system that monitors the main activities performed by the elderly and creates patterns based on that activity to achieve its results and is scalable in terms of sensors and data input.