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Filho G.P.R.,University of Sao Paulo | Ueyama J.,University of Sao Paulo | Villas L.A.,University of Campinas | Pinto A.R.,Sao Paulo State University | And 4 more authors.
Sensors (Switzerland) | Year: 2014

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out. © 2014 by the authors; licensee MDPI, Basel, Switzerland.

Mano L.Y.,University of Sao Paulo | Faical B.S.,University of Sao Paulo | Nakamura L.H.V.,University of Sao Paulo | Nakamura L.H.V.,Federal University of Sao Paulo | And 9 more authors.
Computer Communications | Year: 2016

Currently, there is an increasing number of patients that are treated in-home, mainly in countries such as Japan, USA and Europe. As well as this, the number of elderly people has increased significantly in the last 15 years and these people are often treated in-home and at times enter into a critical situation that may require help (e.g. when facing an accident, or becoming depressed). Advances in ubiquitous computing and the Internet of Things (IoT) have provided efficient and cheap equipments that include wireless communication and cameras, such as smartphones or embedded devices like Raspberry Pi. Embedded computing enables the deployment of Health Smart Homes (HSH) that can enhance in-home medical treatment. The use of camera and image processing on IoT is still an application that has not been fully explored in the literature, especially in the context of HSH. Although use of images has been widely exploited to address issues such as safety and surveillance in the house, they have been little employed to assist patients and/or elderly people as part of the home-care systems. In our view, these images can help nurses or caregivers to assist patients in need of timely help, and the implementation of this application can be extremely easy and cheap when aided by IoT technologies. This article discusses the use of patient images and emotional detection to assist patients and elderly people within an in-home healthcare context. We also discuss the existing literature and show that most of the studies in this area do not make use of images for the purpose of monitoring patients. In addition, there are few studies that take into account the patient's emotional state, which is crucial for them to be able to recover from a disease. Finally, we outline our prototype which runs on multiple computing platforms and show results that demonstrate the feasibility of our approach. © 2016 Elsevier B.V.

Ueyama J.,University of Sao Paulo | Freitas H.,University of Sao Paulo | Filho G.P.R.,University of Sao Paulo | Fini P.,University of Sao Paulo | And 3 more authors.
IEEE Communications Magazine | Year: 2014

A wireless sensor network is liable to suffer faults for several reasons, which include faulty nodes or even the fact that nodes have been destroyed by a natural disaster, such as a flood. These faults can give rise to serious problems if WSNs do not have a reconfiguration mechanism at execution. It should be noted that many WSNs designed to detect natural disasters are deployed in inhospitable places and depend on multihop communication to allow the data to reach a sink node. As a result, a fault in a single node can leave a part of the system inoperable until the node recovers from this failure. In light of this, this article outlines a solution that entails employing unmanned aerial vehicles to reduce the problems arising from faults in a sensor network when monitoring natural disasters like floods and landslides. In the solution put forward, UAVs can be transported to the site of the disaster to mitigate problems caused by faults (e.g., by serving as routers or even acting as a data mule). Experiments conducted with real UAVs and with our WSN-based prototype for flood detection (already deployed in São Carlos, State of São Paulo, Brazil, have proven that this is a viable approach. © 2014 IEEE.

Lopes P.,Vale Institute of Technology ITV | Lana M.,Federal University of Ouro Preto
Mathematical Geosciences | Year: 2016

The calculation of the volumes of rock blocks delimited by discontinuity planes in rock masses is essential for the design of excavations and supports, applied to various engineering activities, like mining and tunneling. Furthermore, the block volumes control the rock mass behavior. If very small blocks are predominant, the rock mass tends to act as a continuum media and exhibit failure through the rock material. In case of prevalence of large blocks the rock mass acts as a discrete block set and failure through discontinuities can occur. There are many analytical methods in technical literature to calculate the volume of rock blocks but most of them are not realistic in relation to data input. In some cases a detailed knowledge of block geometry is required; such condition is rarely available in a field survey. This paper presents an analytical solution for block volume calculation using an easily obtained data in the field. Tetrahedral, tabular or prismatic blocks can be considered. An extension of the solution for polyhedral blocks is also presented. © 2016 International Association for Mathematical Geosciences

Filho G.P.R.,University of Sao Paulo | Ueyama J.,University of Sao Paulo | Faical B.S.,University of Sao Paulo | Pessin G.,Vale Institute of Technology ITV | And 4 more authors.
Proceedings - 2015 IEEE 14th International Symposium on Network Computing and Applications, NCA 2015 | Year: 2015

This work proposes an intelligent decision system for a residential infrastructure based on wireless sensors and actuator networks, called ResiDI. ResiDI is equipped with battery-powered nodes to ensure that they are deployable anywhere in the house without the need for wiring, drilling or any pre-existing infrastructure. The key intelligence of ResiDI is distributed in the decider nodes, which are able to make decisions locally without the need to send traffic from the sensor nodes to the sink. The network intelligence core is based on a neural network that seeks to improve the accuracy of the decision-making, together with a temporal correlation mechanism that is targeted at reducing the energy consumption. When compared with an approach adopted in the literature, the results show that ResiDI is efficient in different scenarios in all evaluations performed. © 2015 IEEE.

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