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The purpose of this study is to reduce energy consumption in bakeries. Due to fulfill this demand, quite a few parameters such as energy and exergy efficiency, energy waste and fuel consumption by different traditional flatbreads bakeries (Sangak, Barbari, Taftun and Lavash should be monitored and their roles should not be neglected.

In the present study, experimental measurements and mathematical modeling are used to scrutinize and investigate the effects of the aforementioned parameters on energy consumption by bakeries.

The results show that by doing reported methods in this paper, the wasted energy of the walls can be decreased by about 65 per cent; and also, by controlling the combustion reaction to perform with 5 per cent excess air, the wasted energy of excess air declines by about 90 per cent. And finally, the energy and exergy efficiency of bakeries is increased, and as a result, the annual energy consumption of Sangak, Barbari, Taftun and Lavash bakeries diminish about 71, 59, 57 and 40 per cent, respectively.

As evidenced by the literature review, it can be observed that neither numerical studies nor experimental investigations have been conducted about energy and exergy analyses of Iranian machinery traditional flatbread bakeries. It is clear that due to a high preference of Iranians to use the traditional bread and also the popularity of baking this kind of bread in Iran, if it is possible to enhance the traditional oven conditions to decrease the loss of natural gas instead of industrializing the bread baking, the energy consumption in the country can be optimized.

Infrared sensors are the fastest growing segment of a $1 billion a year temperature sensor market. Matt Guerreiri of Raytek explains why.

A guide to the various technologies available for measuring and monitoring temperature in the power generation industry. Outlines the parameters to be considered when choosing a measurement system: budgets, location, operating environment. Describes the various technologies of thermocouples, resistance thermometers, infrared thermometry and fibre‐optic temperature sensors and discusses the applications for which each is best suited.

The goal of this review paper is to provide information on several commonly used thermography techniques in semiconductor and micro‐device industry and research today.

The temperature imaging or mapping techniques include thin coating methods such as liquid crystal thermography and fluorescence microthermography, contact mechanical methods such as scanning thermal microscopy, and optical techniques such as infrared microscopy and thermoreflectance. Their principles, characteristics and applications are discussed.

Thermal issues play an important part in optimizing the performance and reliability of high‐frequency and high‐packing density electronic circuits. To improve the performance and reliability of microelectronic devices and also to validate thermal models, accurate knowledge of local temperatures and thermal properties is required.

The paper provides readers, especially technical engineers in industry, a general knowledge of several commonly used thermography techniques in the semiconductor and micro‐device industries.

The current and on-going coronavirus (COVID-19) has disrupted many human lives all over the world and seems very difficult to confront this global crisis as the infection is transmitted by physical contact. As no vaccine or medical treatment made available till date, the only solution is to detect the COVID-19 cases, block the transmission, isolate the infected and protect the susceptible population. In this scenario, the pervasive computing becomes essential, as it is environment-centric and data acquisition via smart devices provides better way for analysing diseases with various parameters.

For data collection, Infrared Thermometer, Hikvision’s Thermographic Camera and Acoustic device are deployed. Data-imputation is carried out by principal component analysis. A mathematical model susceptible, infected and recovered (SIR) is implemented for classifying COVID-19 cases. The recurrent neural network (RNN) with long-term short memory is enacted to predict the COVID-19 disease.

Machine learning models are very efficient in predicting diseases. In the proposed research work, besides contribution of smart devices, Artificial Intelligence detector is deployed to reduce false alarms. A mathematical model SIR is integrated with machine learning techniques for better classification. Implementation of RNN with Long Short Term Memory (LSTM) model furnishes better prediction holding the previous history.

The proposed research collected COVID −19 data using three types of sensors for temperature sensing and detecting the respiratory rate. After pre-processing, 300 instances are taken for experimental results considering the demographic features: Sex, Patient Age, Temperature, Finding and Clinical Trials. Classification is performed using SIR mode and finally predicted 188 confirmed cases using RNN with LSTM model.

Values of parameters such as temperature, humidity, number of plastic products and the location of plastic injection moulds are required to determine the efficiency of plastic injection moulds with a view to improving the quality of the outputs. This article determined the appropriate sensors for the measurement of these essential parameters in the most suitable form of representation of the data to aid a proficient analysis of the data.

The outputs of these sensors were obtained by connecting the sensors to the general-purpose input/output (GPIO) pins of a Raspberry Pi and writing a Python programme for the connected GPIO pins. The values of the outputs of these sensors were represented in a graphical form. The connection of the Raspberry Pi and the sensors were done with a full-sized breadboard and jumper wires. A computer-aided design (CAD) of the connections was produced using Fritzing software.

The appropriate sensors determined are MLX90614 infrared thermometer sensor, DHT11 humidity sensor, pixy2 vision sensor and Neo-6m GPS sensor. This study proposed that the sensors analytic system be applied on an industrial plastic injection mould to measure and display the various parameters of the injection moulds for the purpose of understanding and improving the performance of the injection mould

An electronic system that provides the continuous values of essential parameters of a plastic injection mould in operation.

A ‘no‐wire’ infrared thermometer from Land Infrared has been designed for use in ‘unsafe’ environments.