RFID-based wireless passive sensors utilizing cork materials

This paper presents the design of low-cost, conformal UHF antennas and RFID tags on two types of cork substrates: 1) natural cork and 2) agglomerate cork. Such RFID tags find an application in wine bottle and barrel identification, and in addition, they are suitable for numerous antenna-based sensing applications. This paper includes the high-frequency characterization of the selected cork substrates considering the anisotropic behavior of such materials. In addition, the variation of their permittivity values as a function of the humidity is also verified. As a proof-of-concept demonstration, three conformal RFID tags have been implemented on cork, and their performance has been evaluated using both a commercial Alien ALR8800 reader and an in-house measurement setup. The reading of all tags has been checked, and a satisfactory performance has been verified, with reading ranges spanning from 0.3 to 6 m. In addition, this paper discusses how inkjet printing can be applied to cork surfaces, and an RFID tag printed on cork is used as a humidity sensor. Its performance is tested under different humidity conditions, and a good range in excess of 3 m has been achieved, allied to a good sensitivity obtained with a shift of >5 dB in threshold power of the tag for different humid conditions.

Building a person home behavior model based on data from smart house sensors 2015

Dissertação para a obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia

Humidity passive sensors based on UHF RFID using cork dielectric slabs

In this paper we show the design of passive UHF RFID tag antenna on cork substrate. Due to the cork sensitivity to humidity changes, we can use the developed sensor to sense changes in the relative humidity of the environment, without the need for batteries. The antenna is built using inkjet printing technology, which allows a good accuracy of the design manufacturing. The sensor proved usable for humidity changes detection with a variation of threshold power from 11 to 15 dB between 60 and near 100% humidity levels. Presenting, therefore, reading ranges between 3 to 5 meters. © 2015 EurAAP.

Person Localization Using Sensor Information Fusion

Nowadays the incredible grow of mobile devices market led to the need for location-aware applications. However, sometimes person location is difficult to obtain, since most of these devices only have a GPS (Global Positioning System) chip to retrieve location. In order to suppress this limitation and to provide location everywhere (even where a structured environment doesn’t exist) a wearable inertial navigation system is proposed, which is a convenient way to track people in situations where other localization systems fail. The system combines pedestrian dead reckoning with GPS, using widely available, low-cost and low-power hardware components. The system innovation is the information fusion and the use of probabilistic methods to learn persons gait behavior to correct, in real-time, the drift errors given by the sensors.

Development of a system to monitor surfer’s balance and plantar pressure and surfboard’s movement

O uso da tecnologia tem crescido nas últimas décadas nas mais diversas áreas, seja na indústria ou no dia-a-dia, e é cada vez mais evidente os benefícios que traz. No desporto não é diferente. Cada dia surgem novos desenvolvimentos objetivando a melhoria do desempenho dos praticantes de atividades físicas, possibilitando atingir resultados nunca antes pensados. Além disto, a utilização da tecnologia no desporto permite a obtenção de dados biomecânicos que podem ser utilizados tanto no treinamento quando na melhoria da qualidade de vida dos atletas auxiliando na prevenção de lesões, por exemplo. Deste modo, o presente projeto se aplica na área do desporto, nomeadamente, na modalidade do surfe, onde a ausência de trabalhos científicos ainda é elevada, aliando a tecnologia eletrônica ao desporto para quantificar informações até então desconhecidas. Três fatores básicos de desempenho foram levantados, sendo eles: equilíbrio, posicionamento dos pés e movimentação da prancha de surfe. Estes fatores levaram ao desenvolvimento de um sistema capaz de medi-los dinamicamente através da medição das forças plantares e da rotação da prancha de surfe. Além da medição dos fatores, o sistema é capaz de armazenar os dados adquiridos localmente através de um cartão de memória, para posterior análise; e também enviá-los através de uma comunicação sem fio, permitindo a visualização do centro de pressões plantares; dos ângulos de rotação da prancha de surfe; e da ativação dos sensores; em tempo real. O dispositivo consiste em um sistema eletrônico embarcado composto por um microcontrolador ATMEGA1280; um circuito de aquisição e condicionamento de sinal analógico; uma central inercial; um módulo de comunicação sem fio RN131; e um conjunto de sensores de força Flexiforce. O firmware embarcado foi desenvolvido em linguagem C. O software Matlab foi utilizado para receção de dados e visualização em tempo real. Os testes realizados demostraram que o funcionamento do sistema atende aos requisitos propostos, fornecendo informação acerca do equilíbrio, através do centro de pressões; do posicionamento dos pés, através da distribuição das pressões plantares; e do movimento da prancha nos eixos pitch e roll, através da central inercial. O erro médio de medição de força verificado foi de -0.0012 ± 0.0064 N, enquanto a mínima distância alcançada na transmissão sem fios foi de 100 m. A potência medida do sistema foi de 330 mW.

Host-Tailored Sensors for Leucomalachite Green Potentiometric Measurements

A new biomimetic sensor for leucomalachite green host-guest interactions and potentiometric transduction is presented. The artificial host was imprinted in methacrylic acid or acrylamido-2-methyl-1-propanesulfonic acid-based polymers. Molecularly imprinted particles were dispersed in 2-nitrophenyloctyl ether and trapped in poly(vinyl chloride). The potentiometric sensors exhibited a near-Nernstian response in steady state evaluations, with slopes and detection limits ranging from 45.8 to 81.2 mV and 0.28 to 1.01 , respectively. They were independent from the pH of test solutions within 3 to 5. Good selectivity was observed towards drugs that may contaminate water near fish cultures, such as oxycycline, doxycycline, enrofloxacin, trimethoprim, creatinine, chloramphenicol, and dopamine. The sensors were successfully applied to field monitoring of leucomalachite green in river samples. The method offered the advantages of simplicity, accuracy, applicability to colored and turbid samples, and automation feasibility.

Biomimetic sensors of molecularly-imprinted polymers for chlorpromazine determination

A new man-tailored biomimetic sensor for Chlorpromazine host-guest interactions and potentiometric transduction is presented. The artificial host was imprinted within methacrylic acid, 2-vinyl pyridine and 2-acrylamido-2-methyl-1-propanesulfonic acid based polymers. Molecularly imprinted particles were dispersed in 2-nitrophenyloctyl ether and entrapped in a poly(vinyl chloride) matrix. Slopes and detection limits ranged 51–67 mV/decade and 0.46–3.9 μg/mL, respectively, in steady state conditions. Sensors were independent from the pH of test solutions within 2.0–5.5. Good selectivity was observed towards oxytetracycline, doxytetracycline, ciprofloxacin, enrofloxacin, nalidixic acid, sulfadiazine, trimethoprim, glycine, hydroxylamine, cysteine and creatinine. Analytical features in flowing media were evaluated on a double-channel manifold, with a carrier solution of 5.0 × 10−2 mol/L phosphate buffer. Near-Nernstian response was observed over the concentration range 1.0 × 10−4 to 1.0 × 10−2 mol/L. Average slopes were about 48 mV/decade. The sensors were successfully applied to field monitoring of CPZ in fish samples, offering the advantages of simplicity, accuracy, automation feasibility and applicability to complex samples.

Biomimetic norfloxacin sensors made of molecularly-imprinted materials for potentiometric transduction

A biomimetic sensor for norfloxacin is presented that is based on host-guest interactions and potentiometric transduction. The artificial host was imprinted into polymers made from methacrylic acid and/or 2-vinyl pyridine. The resulting particles were entrapped in a plasticized poly(vinyl chloride) (PVC) matrix. The sensors exhibit near-Nernstian response in steady state evaluations, and detection limits range from 0.40 to 1.0 μg mL−1, respectively, and are independent of pH values at between 2 and 6, and 8 and 11, respectively. Good selectivity was observed over several potential interferents. In flowing media, the sensors exhibit fast response, a sensitivity of 68.2 mV per decade, a linear range from 79 μM to 2.5 mM, a detection limit of 20 μg mL−1, and a stable baseline. The sensors were successfully applied to field monitoring of norfloxacin in fish samples, biological samples, and pharmaceutical products.

Carnitine tailored Sensors on Surface Molecular Imprinting based on Graphene layers

III Jornadas de Electroquímica e Inovação (Electroquímica e Nanomateriais), na Universidade de Trás-os-Montes e Alto Douro, Vila Real, 16 a 17 de Setembro de 2013

Host-Tailored Sensors for Carnitine Potentiometric Measurements based on Surface Molecular Imprinting

Graduate Student Symposium on Molecular Imprinting 2013, na Queen’s University, Belfast, United Kingdom, 15 a 17 de Agosto de 2013

A framework for using real data with distributed low cost sensors

Currently, due to the widespread use of computers and the internet, students are trading libraries for the World Wide Web and laboratories with simulation programs. In most courses, simulators are made available to students and can be used to proof theoretical results or to test a developing hardware/product. Although this is an interesting solution: low cost, easy and fast way to perform some courses work, it has indeed major disadvantages. As everything is currently being done with/in a computer, the students are loosing the “feel” of the real values of the magnitudes. For instance in engineering studies, and mainly in the first years, students need to learn electronics, algorithmic, mathematics and physics. All of these areas can use numerical analysis software, simulation software or spreadsheets and in the majority of the cases data used is either simulated or random numbers, but real data could be used instead. For example, if a course uses numerical analysis software and needs a dataset, the students can learn to manipulate arrays. Also, when using the spreadsheets to build graphics, instead of using a random table, students could use a real dataset based, for instance, in the room temperature and its variation across the day. In this work we present a framework which uses a simple interface allowing it to be used by different courses where the computers are the teaching/learning process in order to give a more realistic feeling to students by using real data. A framework is proposed based on a set of low cost sensors for different physical magnitudes, e.g. temperature, light, wind speed, which are connected to a central server, that the students have access with an Ethernet protocol or are connected directly to the student computer/laptop. These sensors use the communication ports available such as: serial ports, parallel ports, Ethernet or Universal Serial Bus (USB). Since a central server is used, the students are encouraged to use sensor values results in their different courses and consequently in different types of software such as: numerical analysis tools, spreadsheets or simply inside any programming language when a dataset is needed. In order to do this, small pieces of hardware were developed containing at least one sensor using different types of computer communication. As long as the sensors are attached in a server connected to the internet, these tools can also be shared between different schools. This allows sensors that aren't available in a determined school to be used by getting the values from other places that are sharing them. Another remark is that students in the more advanced years and (theoretically) more know how, can use the courses that have some affinities with electronic development to build new sensor pieces and expand the framework further. The final solution provided is very interesting, low cost, simple to develop, allowing flexibility of resources by using the same materials in several courses bringing real world data into the students computer works.

Environmental modeling with precision navigation using ROAZ autonomous surface vehicle

The use of robotic vehicles for environmental modeling is discussed. This paper presents diverse results in autonomous marine missions with the ROAZ autonomous surface vehicle. The vehicle can perform autonomous missions while gathering marine data with high inertial and positioning precision. The underwater world is an, economical and environmental, asset that need new tools to study and preserve it. ROAZ is used in marine environment missions since it can sense and monitor the surface and underwater scenarios. Is equipped with a diverse set of sensors, cameras and underwater sonars that generate 3D environmental models. It is used for study the marine life and possible underwater wrecks that can pollute or be a danger to marine navigation. The 3D model and integration of multibeam and sidescan sonars represent a challenge in nowadays. Adding that it is important that robots can explore an area and make decisions based on their surroundings and goals. Regard that, autonomous robotic systems can relieve human beings of repetitive and dangerous tasks.

Application of Visual-Inertial SLAM for 3D Mapping of Underground Environments

The underground scenarios are one of the most challenging environments for accurate and precise 3d mapping where hostile conditions like absence of Global Positioning Systems, extreme lighting variations and geometrically smooth surfaces may be expected. So far, the state-of-the-art methods in underground modelling remain restricted to environments in which pronounced geometric features are abundant. This limitation is a consequence of the scan matching algorithms used to solve the localization and registration problems. This paper contributes to the expansion of the modelling capabilities to structures characterized by uniform geometry and smooth surfaces, as is the case of road and train tunnels. To achieve that, we combine some state of the art techniques from mobile robotics, and propose a method for 6DOF platform positioning in such scenarios, that is latter used for the environment modelling. A visual monocular Simultaneous Localization and Mapping (MonoSLAM) approach based on the Extended Kalman Filter (EKF), complemented by the introduction of inertial measurements in the prediction step, allows our system to localize himself over long distances, using exclusively sensors carried on board a mobile platform. By feeding the Extended Kalman Filter with inertial data we were able to overcome the major problem related with MonoSLAM implementations, known as scale factor ambiguity. Despite extreme lighting variations, reliable visual features were extracted through the SIFT algorithm, and inserted directly in the EKF mechanism according to the Inverse Depth Parametrization. Through the 1-Point RANSAC (Random Sample Consensus) wrong frame-to-frame feature matches were rejected. The developed method was tested based on a dataset acquired inside a road tunnel and the navigation results compared with a ground truth obtained by post-processing a high grade Inertial Navigation System and L1/L2 RTK-GPS measurements acquired outside the tunnel. Results from the localization strategy are presented and analyzed.

Development of an Unmanned Capsule for large-scale maritime search and rescue

This paper describes the development and testing of a robotic capsule for search and rescue operations at sea. This capsule is able to operate autonomously or remotely controlled, is transported and deployed by a larger USV into a determined disaster area and is used to carry a life raft and inflate it close to survivors in large-scale maritime disasters. The ultimate goal of this development is to endow search and rescue teams with tools that extend their operational capability in scenarios with adverse atmospheric or maritime conditions.

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.