During machining processes, a large amount of heat is generated due to plastic deformation, in a very small area of the cutting tool. This high temperature strongly influences chip formation mechanisms, tool wear, tool life, and workpiece surface integrity and quality. In this sense, knowing the temperature at various points of tool, chip, and workpiece during machining processes is of utmost importance to effectively optimize cutting parameters, improve machinability and product quality, reduce machining costs, and increase tool life and productivity. This paper presents a review of the various methods for temperature measurement and prediction in machining processes, being the different methods discussed and evaluated regarding its merits and demerits. The most suitable method for a given application depends on several aspects, such as cost, size, shape, accuracy, response time, and temperature range. Lastly, some future perspectives for real-time cutting temperature monitoring in the scope of Industry 4.0 and 5.0 are outlined, as well as being presented a new field of tools capable of measuring and controlling cutting temperature, called smart cutting tools.

In the project a monitoring system where a study or analysis of the quantity, availability and performance of the primary energy resource is made, for which a monitoring system of primary energy resources developed in the General campus Guillermo Rodriguez Lara is implemented of the Universidad de las Fuerzas Armadas - ESPE, for which sophisticated equipment that capture the signals of environmental variables is used, the objective is to develop a software-based open source handling such information application, and allows obtaining and storing environmental data, to conduct an analysis of them favoring decision-making, incorporating them into a web platform, the application also calculates the energy produced the day before, thus achieving construct an assessment tool parameters for future projects, which serve the information obtained in the feasibility analysis to implement projects related to renewable energy, thus contributing to energy development.

While the traditional Internet of Things (IoT) relies on electronic sensors/actuators, today’s IoT involves a variety of sensors, comprising not only physical, electronic-based devices but also virtual and even human social sensors/actuators. In this context, how can we efficiently and effectively manage different types of IoT data sources? In this article, we propose a solution to manage different types of sensors/actuators and analyze which management protocols are best in terms of performance. The proposal is based on open and broadly adopted technologies in IoT, with emphasis on the FIWARE middleware. We showed that the management of the heterogeneity of the sensing/actuating IoT devices is feasible, by presenting functionalities related to real use cases. We took advantage of the implemented prototype to compare the performances of lightweight machine to machine (LwM2M) and ultralight device management services in FIWARE. In addition to demonstrating the viability of the proposed approach, the obtained results point to mixed advantages/disadvantages of one protocol over the other.

Smart environments are physical places that are richly and invisibly populated with sensors, actuators and computational elements. The objective of such environments is to adapt themselves to its users in order to increase their comfort and usefulness. This paper proposes a platform, named APOLLO, capable of inferring behaviour rules from a smart environment and apply them to provide an intelligent space. The APOLLO platform is built upon a Service Oriented Architecture (SOA), in which collected context information is used to infer behaviour rules though statistical and machine learning techniques. The proposed platform is to be deployed in a home automation scenario.

This work focuses basically on the design and analysis of simple and low cost hardware systems efficiency for temperature measurement in agricultural area. The main objective is to prove quantitatively, through statistical data analysis, to what extent a simple hardware designed with inexpensive components can be used safely in the indoor temperature measurement in farm buildings, such as greenhouses, warehouse or silos. To verify the of simple hardware efficiency, its data were compared with data from measurements with a high performance LabVIEW platform. This work proved that a simple hardware based on a microcontroller and the LM35 sensor can perform well. It presented a good accuracy but a relatively low precision that can be improved when performed some consecutive signal sampling and then used its average value. Although there are many papers that explain these components, this work has the distinction of presenting a data analysis in numerical form and using high performance systems to ensure critical data comparison.

A eletrocirurgia é uma técnica amplamente utilizada pela medicina em todos os tipos e estilos de cirurgia. Apesar de quase centenária(MASSARWEH; COSGRIFF; SLAKEY, 2006), diversas questões que permeiam essa técnica permanecem sem resposta. Esse trabalho representa um passo em direção ao melhor entendimento da relação entre a energia consumida pela eletrocirurgia e a energia útil utilizada nos processos físico-químicos. Um dos fenômenos que participam da faísca é a elevação da temperatura do tecido. Para otimizar a transferência de energia e diminuir a parcela convertida em calor faz-se necessário medir a temperatura(GRANDE, 2014) do tecido orgânico após a aplicação da faísca eletrocirúrgica. Assim um hardware foi desenvolvido de modo a suprir essa necessidade. O sistema desenvolvido constitui-se de uma unidade de controle e processamento. Nessa prova de conceito foi utilizada a plataforma de desenvolvimento Arduíno para captar e processar as medidas, em conjunto com uma malha sensora para temperatura, e um software para receber as informações no computador e mostrar ao usuário. A metodologia para a medição da temperatura no tecido consiste em se executar uma incisão no local em que se deseja fazer a medição. Em cada incisão foi introduzido um elemento da matriz, tornando possível medir a temperatura local do tecido após a aplicação da faísca eletrocirúrgica. A resposta obtida é demostrada em uma curva de temperatura versus tempo para cada elemento sensor da matriz. Estes resultados possibilitam inferir o gradiente temporal da distribuição de calor no tecido, possibilitando o estudo da energia dissipada no tecido pela aplicação da faísca eletrocirúrgica.

Agradecimentos: This work was partially supported by a bi-national cooperation project, CAPES-FCT Brazil/Portugal and by project AQUA-MONITOR no FCOMP-01-0124-FEDER-013911 (Ref. PTDC/AAC-AMB/112424/2009). Carlos Gouveia would like to acknowledge the financial support of FCT (SFRH/BD/63758/2009)

Um sensor capaz de medir taxa de radiação proveniente de uma fonte de calor, via balanço energético, foi desenvolvido. A taxa de calor é utilizada como parâmetro de entrada para um modelo matemático, o qual é capaz de estabelecer a temperatura da superfície da fonte de calor, sendo esse o principal objetivo do trabalho. A discrepância nos resultados, quando comparados a um pirômetro comercial, é inferior a 5%, dentro de limites de distanciamentos entre fonte e sensor de 100 a 250 mm. A constante de tempo do sensor é de 20 minutos.

This study investigated the use of distributed optical fiber sensing to measure temperature and strain during thermomechanical processes in printed circuit board (PCB) manufacturing. An optical fiber (OF) was bonded to a PCB for simultaneous measurement of temperature and strain. Optical frequency-domain reflectometry was used to interrogate the fiber optic sensor. As the optical fiber is sensitive to both temperature and strain, a demodulation technique is required to separate both effects. Several demodulation techniques were compared to find the best one, highlighting their main limitations. The importance of good estimations of the temperature sensitivity coefficient of the OF and the coefficient of thermal expansion of the PCB was highlighted for accurate results. Furthermore, the temperature sensitivity of the bonded OF should not be neglected for accurate estimations of strains. The two-sensor combination model provided the best results, with a 2.3% error of temperature values and expected strain values. Based on this decoupling model, a methodology for measuring strain and temperature variations in PCB thermomechanical processes using a single and simple OF was developed and tested, and then applied to a trial in an industrial environment using a dynamic oven with similar characteristics to those of a reflow oven. This approach allows the measurement of the temperature profile on the PCB during oven travel and its strain state (warpage).