XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015). 15 to 19, May, 2015, III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.

A Visual Programming Framework for Wireless Sensor Networks in Smart Home Applications

International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2015). 7 to 9, Apr, 2015. Singapure, Singapore.

Bringing Context Awareness to IoT-Based Wireless Sensor Networks

IEEE International Conference on Pervasive Computing and Communications (PerCom). 23 to 26, Mar, 2015, PhD Forum. Saint Louis, U.S.A..

BoaVista – Sensor Dedicado de Visão Artificial Baseado em Hardware (Re)configurável

4º Festival Nacional de Robótica - Actas do Encontro Científico - Proceedings of the Scientific Meeting, Biblioteca Almeida Garrett, Palácio de Cristal – Porto, 23-24 Abril 2004

Towards the Development of XDense, A Sensor Network for Dense Sensing

Poster in 12th European Conference on Wireless Sensor Networks (EWSN 2015). 9 to 11, Feb, 2015, pp 24-25. Porto, Portugal.

Poster/Demo Session Proceedings of the 12th European Conference on Wireless Sensor Networks (EWSN'15) C

Proceedings of the 12th European Conference on Wireless Sensor Networks (EWSN'15), 9-11 Feb 2015, Porto-Portugal.

A Modular Programming Approach for IoTBased Wireless Sensor Networks

Poster presented in 12th European Conference on Wireless Sensor Network (EWSN 2015). 9 to 11, Feb, 2015. Porto, Portugal.

XDense: A Dense Grid Sensor Network for Distributed Feature Extraction

XXXIII Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC 2015), III Workshop de Comunicação em Sistemas Embarcados Críticos. Vitória, Brasil.

On the Sensor Classification Scheme of Robotic Manipulators

This paper analyzes the signals captured during impacts and vibrations of a mechanical manipulator. The Fourier Transform of eighteen different signals are calculated and approximated by trendlines based on a power law formula. A sensor classification scheme based on the frequency spectrum behavior is presented.

Sensor Integration for Smart Cities Using Multi-Hop Networks

Smart Cities are designed to be living systems and turn urban dwellers life more comfortable and interactive by keeping them aware of what surrounds them, while leaving a greener footprint. The Future Cities Project [1] aims to create infrastructures for research in smart cities including a vehicular network, the BusNet, and an environmental sensor platform, the Urban Sense. Vehicles within the BusNet are equipped with On Board Units (OBUs) that offer free Wi-Fi to passengers and devices near the street. The Urban Sense platform is composed by a set of Data Collection Units (DCUs) that include a set of sensors measuring environmental parameters such as air pollution, meteorology and noise. The Urban Sense platform is expanding and receptive to add new sensors to the platform. The parnership with companies like TNL were made and the need to monitor garbage street containers emerged as air pollution prevention. If refuse collection companies know prior to the refuse collection which route is the best to collect the maximum amount of garbage with the shortest path, they can reduce costs and pollution levels are lower, leaving behind a greener footprint. This dissertation work arises in the need to monitor the garbage street containers and integrate these sensors into an Urban Sense DCU. Due to the remote locations of the garbage street containers, a network extension to the vehicular network had to be created. This dissertation work also focus on the Multi-hop network designed to extend the vehicular network coverage area to the remote garbage street containers. In locations where garbage street containers have access to the vehicular network, Roadside Units (RSUs) or Access Points (APs), the Multi-hop network serves has a redundant path to send the data collected from DCUs to the Urban Sense cloud database. To plan this highly dynamic network, the Wi-Fi Planner Tool was developed. This tool allowed taking measurements on the field that led to an optimized location of the Multi-hop network nodes with the use of radio propagation models. This tool also allowed rendering a temperature-map style overlay for Google Earth [2] application. For the DCU for garbage street containers the parner company provided the access to a HUB (device that communicates with the sensor inside the garbage containers). The Future Cities use the Raspberry pi as a platform for the DCUs. To collect the data from the HUB a RS485 to RS232 converter was used at the physical level and the Modbus protocol at the application level. To determine the location and status of the vehicles whinin the vehicular network a TCP Server was developed. This application was developed for the OBUs providing the vehicle Global Positioning System (GPS) location as well as information of when the vehicle is stopped, moving, on idle or even its slope. To implement the Multi-hop network on the field some scripts were developed such as pingLED and “shark”. These scripts helped upon node deployment on the field as well as to perform all the tests on the network. Two setups were implemented on the field, an urban setup was implemented for a Multi-hop network coverage survey and a sub-urban setup was implemented to test the Multi-hop network routing protocols, Optimized Link State Routing Protocol (OLSR) and Babel.

Molecularly imprinted electrochemical sensor for ochratoxin A detection in food samples

A novel electrochemical sensor for ochratoxin A (OTA) detection was fabricated through the modification of a glassy carbon electrode (GCE) with multiwalled carbon nanotubes (MWCNTs) and a molecularly imprinted polymer (MIP). The MWCNTs dramatically promoted the sensitivity of the developed sensor, while polypyrrole (PPy) imprinted with OTA served as the selective recognition element. The imprinted PPy film was prepared by electropolymerization of pyrrole in the presence of OTA as a template molecule via cyclic voltammetry (CV). The electrochemical oxidation of OTA at the developed sensor was investigated by CV and differential pulse voltammetry (DPV). The developed MIP/MWCNT/GCE sensor showed a linear relationship, when using DPV, between peak current intensity and OTA concentration in the range between 0.050 and 1.0 μM, with limits of detection (LOD) and quantification of 0.0041 μM (1.7 μg/L) and 0.014 μM (5.7 μg/L) respectively. With the developed sensor precise results were obtained; relative standard deviations of 4.2% and 7.5% in the evaluation of the repeatability and reproducibility, respectively. The MIP/MWCNT/GCE sensor is simple to fabricate and easy to use and was successfully applied to the determination of OTA in spiked beer and wine samples, with recoveries between 84 and 104%, without the need of a sample pre-treatment step.

“Green Electrodes” Modified with Au Nanoparticles Synthesized in Glycerol, as Electrochemical Nitrite Sensor

A new environmentally friendly Au nanoparticles (Au NPs) synthesis in glycerol by using ultraviolet irradiation and without extra-added stabilizers is described. The synthesis proposed in this work may impact on the non-polluting production of noble nanoparticles with simple chemicals normally found in standard laboratories. These Au NPs were used to modify a carbon paste electrode (CPE) without having to separate them from the reaction medium. This green electrode was used as an electrochemical sensor for the nitrite detection in water. At the optimum conditions the green sensor presented a linear response in the 2.0×10−7–1.5×10−5 M concentration range, a good detection sensitivity (0.268 A L mol−1), and a low detection limit of 2.0×10−7 M of nitrite. The proposed modified green CPE was used to determine nitrite in tap water samples.

Molecularly imprinted sensor for voltammetric detection of norfloxacin

In this work, a norfloxacin selective modified glassy carbon electrode (GCE) based on a molecularly imprinted polymer (MIP) as electrochemical sensor was developed. A suspension of multi-walled carbon nanotubes (MWCNTs) was deposited on the electrode surface. Subsequently, a molecularly imprinted film was prepared by electropolymerization, via cyclic voltammetry of pyrrole (PPy) in the presence of norfloxacin (NFX) as the template molecule. A control electrode (NIP) was also prepared. Scanning electron microscopy (SEM) and cyclic voltammetry in a ferrocyanide solution were performed for morphological and electrochemical characterisation, respectively. Several experimental parameters were studied and optimised. For quantification purposes the MIP/MWCNT/GCE was immersed in NFX solutions for 10 min, and the detection was performed in voltammetric cell by square wave voltammetry. The proposed sensor presented a linear behaviour, between peak current intensity and logarithmic concentration of NFX between 1 × 10−7 and 8 × 10−6 M. The obtained results presented good precision, with a repeatability of 4.3% and reproducibility of 9% and the detection limit was 4.6 × 10−8 M (S/N = 3). The developed sensor displayed good selectivity and operational lifetime, is simple to fabricate and easy to operate and was successfully applied to the analysis of NFX in urine samples.

Impact of sensor nodes scaling and velocity on handover mechanisms for healthcare wireless sensor networks with mobility support

Health promotion in hospital environments can be improved using the most recent information and communication technologies. The Internet connectivity to small sensor nodes carried by patients allows remote access to their bio-signals. To promote these features the healthcare wireless sensor networks (HWSN) are used. In these networks mobility support is a key issue in order to keep patients under realtime monitoring even when they move around. To keep sensors connected to the network, they should change their access points of attachment when patients move to a new coverage area along an infirmary. This process, called handover, is responsible for continuous network connectivity to the sensors. This paper presents a detailed performance evaluation study considering three handover mechanisms for healthcare scenarios (Hand4MAC, RSSI-based, and Backbone-based). The study was performed by simulation using several scenarios with different number of sensors and different moving velocities of sensor nodes. The results show that Hand4MAC is the best solution to guarantee almost continuous connectivity to sensor nodes with less energy consumption.

Quality-of-service aware routing for static and mobile IPv6-based low-power and lossy sensor networks using RPL

The Internet of Things (IoT) has emerged as a paradigm over the last few years as a result of the tight integration of the computing and the physical world. The requirement of remote sensing makes low-power wireless sensor networks one of the key enabling technologies of IoT. These networks encompass several challenges, especially in communication and networking, due to their inherent constraints of low-power features, deployment in harsh and lossy environments, and limited computing and storage resources. The IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) [1] was proposed by the IETF ROLL (Routing Over Low-power Lossy links) working group and is currently adopted as an IETF standard in the RFC 6550 since March 2012. Although RPL greatly satisfied the requirements of low-power and lossy sensor networks, several issues remain open for improvement and specification, in particular with respect to Quality of Service (QoS) guarantees and support for mobility. In this paper, we focus mainly on the RPL routing protocol. We propose some enhancements to the standard specification in order to provide QoS guarantees for static as well as mobile LLNs. For this purpose, we propose OF-FL (Objective Function based on Fuzzy Logic), a new objective function that overcomes the limitations of the standardized objective functions that were designed for RPL by considering important link and node metrics, namely end-to-end delay, number of hops, ETX (Expected transmission count) and LQL (Link Quality Level). In addition, we present the design of Co-RPL, an extension to RPL based on the corona mechanism that supports mobility in order to overcome the problem of slow reactivity to frequent topology changes and thus providing a better quality of service mainly in dynamic networks application. Performance evaluation results show that both OF-FL and Co-RPL allow a great improvement when compared to the standard specification, mainly in terms of packet loss ratio and average network latency. 2015 Elsevier B.V. Al