Control System for Indoor Safety Measures Using a Faster R-CNN Architecture

This paper presents a control system for indoor safety measures using a Faster R-CNN (Region-based Convolutional Neural Network) architecture. The proposed system aims to ensure the safety of occupants in indoor environments by detecting and recognizing potential safety hazards in real time, such as capacity control, social distancing, or mask use. Using deep learning techniques, the system detects these situations to be controlled, notifying the person in charge of the company if any of these are violated. The proposed system was tested in a real teaching environment at Rey Juan Carlos University, using Raspberry Pi 4 as a hardware platform together with an Intel Neural Stick board and a pair of PiCamera RGB (Red Green Blue) cameras to capture images of the environment and a Faster R-CNN architecture to detect and classify objects within the images. To evaluate the performance of the system, a dataset of indoor images was collected and annotated for object detection and classification. The system was trained using this dataset, and its performance was evaluated based on precision, recall, and F1 score. The results show that the proposed system achieved a high level of accuracy in detecting and classifying potential safety hazards in indoor environments. The proposed system includes an efficiently implemented software infrastructure to be launched on a low-cost hardware platform, which is affordable for any company, regardless of size or revenue, and it has the potential to be integrated into existing safety systems in indoor environments such as hospitals, warehouses, and factories, to provide real-time monitoring and alerts for safety hazards. Future work will focus on enhancing the system's robustness and scalability to larger indoor environments with more complex safety hazards.

The Importance of Low-Cost Live Feed Culture Technology to the Marine Shrimp Industry during COVID-19

The importance of live feed as a beginning diet in marine shrimp (Penaeus sp.) is largely dependent on careful management during the early stages of larval growth. The COVID-19 pandemic has a significant impact on Malaysian aquaculture, which is critical for seafood supply and security. Cladocerans are an alternative live feed species that outperform Artemia nauplii in terms of nutritional value, economic value, availability, and reproduction rate. In terms of supplying live feed for commercial aquaculture, cladoceran culture and cultivation can therefore be an economically viable, sustainable, and desirable live feed species. The purpose of this study is to collect information on low-cost live feed for marine shrimp used in aquaculture and how COVID-19 affects the sector. Thus, a survey was conducted at a private hatchery and farm in Pekan and Badong, Pahang, Malaysia to investigate the importance of low-cost live feed culture technology to the marine shrimp industry during COVID-19. A total of 20 respondents took part in the survey. During the COVID-19 period in Malaysia, data were gathered using a questionnaire that was planned to be completed via an online form from August 2020 through December 2020. The software utilised was a Google application (Google Form). The data gathered revealed the importance of utilising live feed for maintaining shrimp larvae production in the sector. The current data are critical for developing policy actions to support seafood industries affected by the pandemic at both the national and international levels. Copyright©2023 by authors, all rights reserved.

Newton's law of cooling with a low-cost thermoscope: physics in the time of covid-19

The necessity to teach experimental physics in the pandemic period motivated the development of practices in which students may take measurements with instruments constructed by themselves. In this article, we present an experimental practice to approach Newton's law of cooling with a thermoscope (the earliest device for detecting changes in temperature, forerunner of the thermometer) constructed with household materials. Although the use of a non-calibrated thermoscope, the instrument presented several advantages, visual appeal, ease of handling, ease of data acquisition and good reproducibility. The students can take data, plot graphs, and verify if the Newton's law of cooling holds on the tested circumstances.

Determinants of Attitude and the Intention to Stay of Employees in Low-Cost Carriers: Using Justice Theory

The purpose of this research is to examine the influential attributes of employees' attitudes and intentions to stay in the domain of human resources management in a low-cost carrier business. Using justice theory as a theoretical underpinning, financial compensation, nonfinancial compensation, coworker relationships, and procedural fairness were derived. The explained attributes of this research were attitude and intention to stay. This study used a survey and collected data on 233 employees in low-cost carriers as survey participants. To test the hypotheses, this study employed structural equation modeling. The results showed that attitude was positively impacted by financial compensation, nonfinancial compensation, coworker relationships, and procedural fairness. The results also revealed the positive effect of coworker relationships and attitudes on the intention to stay. This study sheds light on the literature by ensuring the explanatory power of justice theory in the area of low-cost carrier business.

Methodology to carry out medical meeting online, based on low-cost solutions

One of the effects of the COVID-19 pandemic is the adaptation of most of the activities remotely or virtually, in the case of medical appointments, in the different specialties other than emergencies produced by COVID-19. Most of them continued in the format through online appointments. One of the important processes in medical evaluations is related to the so-called specialist boards, where special cases are evaluated, for which several physicians must be connected online, in addition to being able to make reports jointly. In this paper we develop a methodology to perform medical meetings of specialists, using a platform dedicated to the use in video games, through the DISCORD tool interconnectivity from various devices is performed, the results demonstrate the interactivity and applicability of the methodology, so it can be applied in different processes where interconnectivity between different devices and the concurrence of several users is required. We present a methodology to configure virtual appointment rooms, the results allow us to verify that the methodology can be replicated and scaled according to the needs. © 2022 ACM.

Methodology for Monitoring Vital Signs in Virtual Classes Using Low-cost Sensors in Online Classes

The effects of the COVID-19 pandemic have led to certain patterns in the different actions people take. One of the areas in which this pandemic has impacted most strongly is related to educational activities and children were the most affected. They went from studying in their schools where they have all the conditions, to a physical space at home. This strong change in the environment added to the high levels of contagion, have caused students to present certain manifestations such as the level of stress which can be manifested by many factors such as the main vital signs such as oxygen saturation and heart rate. In this paper we present a methodology to perform these measurements in order to evaluate these measurements when students are attending classes from home. © 2022 ACM.

Comparing nasopharyngeal apnoeic oxygenation at 18 l/min to preoxygenation alone in obese patients - A randomised controlled study.

STUDY OBJECTIVE: Investigate a low-cost, nasopharyngeal apnoeic oxygenation technique, establish its efficacy, and compare it to preoxygenation only in an obese population. The study's hypothesis was that nasopharyngeal apnoeic oxygenation at 18 l.min-1 would significantly prolong safe apnoea time compared to preoxygenation alone. DESIGN: Randomised controlled study. SETTING: Theatre complex of a resource constrained hospital. PATIENTS: 30 adult, obese (BMI ≥ 35 kg.m-2) patients presenting for elective surgery. Patients with limiting cardio-respiratory disease, suspected difficult airway, risk of aspiration, and that were pregnant, were excluded. Patients were allocated by block randomisation in a 1:2 ratio to a preoxygenation-only (No-AO) and an intervention group (NPA-O2). INTERVENTIONS: All patients were preoxygenated to an Et-O2 > 80%, followed by a standardised induction. The intervention group received oxygen at 18 l.min-1 via the nasopharyngeal catheter intervention. The desaturation process was documented until an SpO2 of 92% or 600 s was reached. MEASUREMENTS: Baseline demographic and clinical characteristics were collected. The primary outcome was safe apnoea time, defined as the time taken to desaturate to an SpO2 of 92%. Secondary outcomes were rate of carbon dioxide accumulation and factors affecting the risk of desaturation. MAIN RESULTS: The study was conducted in a morbidly obese population (NoAO = 41,1 kg.m-2; NPA-O2 = 42,5 kg.m-2). The risk of desaturation was signifantly lower in the intervention group (Hazzard Ratio = 0,072, 95% CI[0,019-0,283]) (Log-Rank test, p < 0.001). The median safe apnoea time was significantly longer in the intervention group (NoAO = 262 s [IQR 190-316]; NPA-O2 = 600 s [IQR 600-600]) (Mann-Whitney-U test, p < 0.001). The mean rate of CO2 accumalation was significantly slower in the intervention group (NoAO = 0,47 ± 0,14 kPa.min-1; NPA-O2 = 0,3 ± 0,09 kPa.min-1) (t-test, p = 0.003). There were no statistically significant risk factors associated with an increased risk of desaturation found. CONCLUSIONS: Nasopharyngeal apnoeic oxygenation at 18 l/min prolongs safe apnoea time, compared to preoxygenation alone, and reduces the risk of desaturation in morbidly obese patients. CLINICAL TRIAL REGISTRATION: PACTR202202665252087; WC/202004/007.

Managing indoor air quality in nursery and primary schools with low-cost solutions

This study aimed to evaluate the feasibility of using low-cost solutions to monitor and mitigate PM2.5 and PM10 concentrations in nursery and primary schools in Porto (Portugal). Three periods were considered: i) early 2020 (before COVID-19 pandemic), ii) early 2021 (during COVID-19 pandemic, with mitigation measures to prevent SARS-CoV-2 spread);and iii) in the middle of 2021 (additionally using a low-cost portable air cleaner). PM2.5 and PM10 were continuously monitored with a low-cost sensing device for at least two consecutive days in five classrooms. In general, the lowest PM concentrations were observed in the third period. Concentrations reduced up to 63% from the second to the third period. The application of low-cost solutions for monitoring and mitigating PM levels seems to be an effective tool for managing indoor air in schools. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Classification of Respiratory Syncytial Virus and Sendai Virus Using Portable Near-Infrared Spectroscopy and Chemometrics

There is evidence that it may be possible to detect viruses and viral infection optically using techniques such as Raman and infrared (IR) spectroscopy and hence open the possibility of rapid identification of infected patients. However, high-resolution Raman and IR spectroscopy instruments are laboratory-based and require skilled operators. The use of low-cost portable or field-deployable instruments employing similar optical approaches would be highly advantageous. In this work, we use chemometrics applied to low-resolution near-IR (NIR) reflectance/absorbance spectra to investigate the potential for simple low-cost virus detection suitable for widespread societal deployment. We present the combination of near-IR spectroscopy (NIRS) and chemometrics to distinguish two respiratory viruses, respiratory syncytial virus (RSV), the principal cause of severe lower respiratory tract infections in infants worldwide, and Sendai virus (SeV), a prototypic paramyxovirus. Using a low-cost and portable spectrometer, three sets of RSV and SeV spectra, dispersed in phosphate-buffered saline (PBS) medium or Dulbecco's modified eagle medium (DMEM), were collected in long- and short-term experiments. The spectra were preprocessed and analyzed by partial least-squares discriminant analysis (PLS-DA) for virus type and concentration classification. Moreover, the virus type/concentration separability was visualized in a low-dimensional space through data projection. The highest virus-type classification accuracy obtained in PBS and DMEM is 85.8% and 99.7%, respectively. The results demonstrate the feasibility of using portable NIR spectroscopy as a valuable tool for rapid, on- site, and low-cost virus prescreening for RSV and SeV with the further possibility of extending this to other respiratory viruses such as SARS-CoV-2.

Design and Development of Toroidal Core Winding Machine with Digital Interface

The small size and inherent superior electrical characteristics of a toroid has made it the first choice for many Original Equipment Manufacturers (OEMs). However, the lack of knowledge regarding the toroidal coil winding equipment is still hampering the growth of toroid as the first choice for transformers, inductors and other electrical applications. Additionally, due to Covid-19 pandemic and lockdown situation, small scale companies are lacking skilled manpower for the high precision task of toroidal core winding and taping. Although the machine is readily available in the market, the cost is still very high. Toroidal core winding machine is an equipment used for the purpose of winding toroidal cores which is used in various electrical machines such as current transformers, power transformers, isolation transformers, inductors and chokes, auto transformers, etc. This project aims to develop a low-cost toroidal winding machine with a user-friendly digital interface for selection of winding parameters as per the user input. The winding machine developed in this project is efficient and reliable with high-speed performance and negligible error. © 2022 IEEE.

Understanding Airline Passengers during Covid-19 Outbreak to Improve Service Quality: Topic Modeling Approach to Complaints with Latent Dirichlet Allocation Algorithm.

The COVID-19 pandemic has deeply affected the airline industry, as it has many sectors, and has created tremendous financial pressure on companies. Flight bans, new regulations, and restrictions increase consumer complaints and are emerging as a big problem for airline companies. Understanding the main reasons triggering complaints and eliminating service failures in the airline industry will be a vital strategic priority for businesses, while reviewing the dimensions of service quality during the COVID-19 pandemic provides an excellent opportunity for academic literature. In this study, 10,594 complaints against two major airlines that offer full-service and low-cost options were analyzed with the Latent Dirichlet Allocation algorithm to categorize them by essential topics. Results provide valuable information for both. Furthermore, this study fills the gap in the existing literature by proposing a decision support system to identify significant service failures through passenger complaints in the airline industry utilizing e-complaints during an unusual situation such as the COVID-19 pandemic.

Nanomaterials and Biosensing Technology for the SARS-CoV-2 Detection

The outbreak of corona virus disease 2019 (COVID-19) has aroused great attention around the world. SARS-CoV-2 possesses characteristics of faster transmission, immune escape, and occult transmission by many mutation, which caused still grim situation of prevention and control. Early detection and isolation of patients are still the most effective measures at present. So, there is an urgent need for new rapid and highly sensitive testing tools to quickly identify infected patients as soon as possible. This review briefly introduces general characteristics of SARS-CoV-2, and provides recentl overview and analysis based on different detection methods for nucleic acids, antibodies, antigens as detection target. Novel nano-biosensors for SARS-CoV-2 detection are analyzed based on optics, electricity, magnetism, and visualization. In view of the advantages of nanotechnology in improving detection sensitivity, specificity and accuracy, the research progress of new nano-biosensors is introduced in detail, including SERS-based biosensors, electrochemical biosensors, magnetic nano-biosensors and colorimetric biosensors. Functions and challenges of nano-materials in construction of new nano-biosensors are discussed, which provides ideas for the development of various coronavirus biosensing technologies for nanomaterial researchers.

Evaluating the Performance of Low-cost PM Sensors over Multiple COALESCE Network Sites

Air quality is a global concern, with particulate matter receiving considerable attention due to its impact on human health and climate change. Recent advances in low-cost sensors allow their deployment in large number to measure spatio-temporal and real-time air quality data. Low-cost sensors need careful evaluation with both regulatory approved methods and other data sets to understand their efficacy. In this work, PM concentrations measured by deploying low-cost sensors at four regional sites are evaluated through comparison with satellite-based model MERRA-2 and the SASS reference instrument. Daily PM2.5 mass concentration variation was analyzed at four regional sites of India from January 2020 to July 2020, including pre-lockdown and six different lockdown periods. Higher PM2.5 concentration was observed at Rohtak (119 mu g m-3) compared to Mahabaleshwar (33 mu g m-3), Bhopal (45 mu g m-3) and Kashmir sites during the pre-lock down period. During the lockdown period, the PM2.5 mass concentration was reduced significantly compared to the pre-lockdown period at every location, although the PM2.5 concentration was different at each location. The air quality trend was quite similar in both the measurements, however, MERRA-2 reconstructed PM2.5 was significantly lower in the pre-lockdown period compared to the lockdown periods. Significant differences were observed between low-cost sensor measurements and MERRA-2 reanalysis data. These are attributed to the MERRA-2 modelling analysis that measures less PM2.5 concentration as compared to ground-based measurements, whereas low-cost sensor are and biases.

The big three EU Low Cost Carriers before and during the Covid-19 pandemic: Network overlaps and airfare effects

This study uses a large dataset to consider the network change of the three largest European Low Cost Carriers (LCCs) easyJet, Ryanair and Wizz Air during the pre-Covid-19 period and the Covid-19 pandemic period. Network changes are characterized in terms of airport pairs, city pairs, numbers of flights and network overlaps. The results show that European LCCs increasingly expanded their networks into markets that had already been served by incumbent LCCs, which indicates that LCCs increasingly compete head-to-head among themselves. Difference-in-differences regressions estimate that network overlaps among these LCCs lead to airfare reductions of approximately six Euros, ten percent.

Assessing the Risk of Spreading COVID-19 in the Room Utilizing Low-Cost Monitoring System

High hygiene standards were established during the COVID-19 epidemic, and their adherence was closely monitored. They included the need to regularly wash one's hands and the requirement to cover person's upper airways or keep at least a two-meter space between individuals. The ITS (Information Technology Systems) community made a big contribution to this by developing methods and applications for the ongoing observation of people and the environment. Our major objective was to create a low-cost, straightforward system for tracking and assessing the danger of spreading COVID-19 in a space.The proposed system collects data from various low-cost environmental sensors such as temperature, humidity, CO2, the number of people, the dynamics of speech, and the cleanliness of the environment with a significant connection to elements of wearable electronics and then evaluate the level of contamination and possible risks and, in the event of a high level of risk, alerts the person to take actions that can reduce or eliminate favourable conditions for the spread of the virus. The system was created at the Laboratory of industrial control systems of the University of Žilina, Slovakia. The experiment demonstrates the ability and feasibility to control the number of people in a space depending on particular symptoms like fever, coughing, and hand hygiene. On the other hand, the laboratory's temperature, humidity, and air quality should be controlled to reduce the spread of illness.

Overcoming Chip Shortages: Low-Cost Open-Source Parametric 3-D Printable Solderless SOIC to DIP Breakout Adapters

The COVID-19 pandemic exposed the vulnerability of global supply chains of many products. One area that requires improved supply chain resilience and that is of particular importance to electronic designers is the shortage of basic dual in-line package (DIP) electronic components commonly used for prototyping. This anecdotal observation was investigated as a case study of using additive manufacturing to enforce contact between premade, off-the-shelf conductors to allow for electrical continuity between two arbitrary points by examining data relating to the stock quantity of electronic components, extracted from Digi-Key Electronics. This study applies this concept using an open hardware approach for the design, testing, and use of a simple, parametric, 3-D printable invention that allows for small outline integrated circuit (SOIC) components to be used in DIP package circuits (i.e., breadboards, protoboards, etc.). The additive manufacture breakout board (AMBB) design was developed using two different open-source modelers, OpenSCAD and FreeCAD, to provide reliable and consistent electrical contact between the component and the rest of the circuit and was demonstrated with reusable 8-SOIC to DIP breakout adapters. The three-part design was optimized for manufacturing with RepRap-class fused filament 3-D printers, making the AMBB a prime candidate for use in distributed manufacturing models. The AMBB offers increased flexibility during circuit prototyping by allowing arbitrary connections between the component and prototyping interface as well as superior organization through the ability to color-code different component types. The cost of the AMBB is CAD $0.066/unit, which is a 94% saving compared to conventional PCB-based breakout boards. Use of the AMBB device can provide electronics designers with an increased selection of components for through-hole use by more than a factor of seven. Future development of AMBB devices to allow for low-cost conversion between arbitrary package types provides a path towards more accessible and inclusive electronics design as well as faster prototyping and technical innovation.

The Integral Role of Intelligent IoT System, Cloud Computing, Artificial Intelligence, and 5G in the User-Level Self-Monitoring of COVID-19

This study presents internet of things (IOT) and artificial intelligence technologies that are critical in reducing the harmful effects of this illness and assisting its recovery. It explores COVID-19's economic impacts before learning about new technologies and potential solutions. The research objective was to propose a solution for self-diagnosis, self-monitoring, and self-management of COVID-19 with personal mobiles and personal data using cloud solutions and mobile applications with the help of an intelligent IoT system, artificial intelligence, machine learning, and 5G technologies. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics by using handsets only is an innovative approach. Since the COVID-19 outbreak, the global social, economic, religious, and cultural frameworks and schedules have been affected adversely. The fear and panic associated with the new disease, which the world barely knew anything about, amplified the situation. Scientists and epidemiologists have traced the first outbreak of COVID-19 at Wuhan, China. A close examination of the genetic makeup of the virus showed that the virus is zoonotic, meaning that the virus changed hosts from animals to humans. The uncertainty associated with the above features and characteristics of the virus, as well as the high mortality rates witnessed in many parts of the globe, significantly contributed to the widespread global panic that brought the world to a standstill. Different authorities and agencies associated with securing the public have implemented different means and methods to try and mitigate the transmission of the infection as scientists and medical practitioners work on remedies to curb the spread of COVID-19. Owing to different demographics, different parts of the globe have attempted to effectively implement locally available resources to efficiently fight and mitigate the adverse effects of the COVID-19 pandemic. The general framework provided by the World Health Organization (WHO) has been implemented or enhanced in different parts of the globe by locally available resources and expertise to effectively mitigate the impact of COVID-19. There is currently no effective vaccine for COVID-19, but new technology can be available within weeks to reduce the spread of the disease;current approaches such as contact tracing and testing are not secure, and the cost of testing is high for end users. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics functions by using an intelligent internet of things (IOT) system for collecting sensors data and processing them with artificial intelligence to improve efficiency and reduce the spread of COVID-19.

Moderating effect of government policy on the relationship between low-cost housing demand-supply gap and COVID-19 impact

Purpose: The COVID-19 impact across major sectors did not exempt the low-cost housing (LCH) sub-sector. This may have increased the existing LCH demand-supply gap, especially in developing countries such as Malaysia. Studies showed that government policy (GP) aids in mitigating COVID-19 impact on goods and services, including housing-related issues. However, there is an academic literature scarcity regarding GP on LCH demand-supply gap during the COVID-19 crisis in Malaysia. Hence, this study aims to investigate the moderating effect of GP on the relationship between LCH demand-supply gap and COVID-19 impact in Malaysia. Design/methodology/approach: The research utilised a quantitative method in collating the data from four major cities in Malaysia. SmartPLS was utilised to analyse the usable 305 questionnaires retrieved from respondents. Structuralist Theory supported the developed framework. Findings: Findings show that GP moderates the relationships between the LCH demand-supply gap and COVID-19 impact on Malaysia's low-income groups' (LIGs) homeownership delivery. It implies that the study's findings provide more understanding of issues influencing LCH demand-supply gap in the COVID-19 era via applying GP to mitigate the gap and improve homeownership for the disadvantaged. Practical implications: The study intends to stir policymakers toward formulating policies and programmes that will mitigate LCH demand-supply gap during the present and future pandemics. Originality/value: Besides the theoretical value of the developed model, policymakers can use the study's recommendations to mitigate future LCH demand-supply gaps during pandemics in developing countries using Malaysia as a case study. © 2023, Emerald Publishing Limited.

Conceptual Design of a UVC-LED Air Purifier to Reduce Airborne Pathogen Transmission—A Feasibility Study

Existing indoor closed ultraviolet-C (UVC) air purifiers (UVC in a box) have faced technological challenges during the COVID-19 breakout, owing to demands of low energy consumption, high flow rates, and high kill rates at the same time. A new conceptual design of a novel UVC-LED (light-emitting diode) air purifier for a low-cost solution to mitigate airborne diseases is proposed. The concept focuses on performance and robustness. It contains a dust-filter assembly, an innovative UVC chamber, and a fan. The low-cost dust filter aims to suppress dust accumulation in the UVC chamber to ensure durability and is conceptually shown to be easily replaced while mitigating any possible contamination. The chamber includes novel turbulence-generating grids and a novel LED arrangement. The turbulent generator promotes air mixing, while the LEDs inactivate the pathogens at a high flow rate and sufficient kill rate. The conceptual design is portable and can fit into ventilation ducts. Computational fluid dynamics and UVC ray methods were used for analysis. The design produces a kill rate above 97% for COVID and tuberculosis and above 92% for influenza A at a flow rate of 100 L/s and power consumption of less than 300 W. An analysis of the dust-filter performance yields the irradiation and flow fields.

Stress detection and monitoring based on low-cost mobile thermography.

The high level of stress in modern life is one of the huge problems of the 21st century society, especially in the context of the Covid-19 pandemic. With the pandemic, the need for inexpensive, portable and easy-to-use health monitoring tools (mental and physical) has increased. Of particular importance here is mobile (smartphone) thermography, as it enables the initial detection and self-control of stress, which being intensified nowadays, is the cause of many diseases, depression and health problems. The smartphone thermal imaging camera responds to the strict sanitary guidelines, offering contact-free, painless and non-invasive operation. Additionally, it is included in the group of low-cost solutions available for home use. It is an alternative to commonly used (often expensive and unavailable to everyone): EMG, ECG, EEG, GSR or other high-cost stress detection tools. Thermal imaging by analyzing abnormalities or temperature changes allows for detection application. Therefore, the aim of this work is to determine the possibilities of a low-budget mobile thermal imaging camera in detecting stress, detecting and analyzing stress by identifying the characteristics of psychophysiological signals with the individual characteristics of the participants, along with the correlation. The participants' reactions to the film introducing stress tension up to the climax of the action were recorded thermographically. Data was processed in OpenCV. In the usual observation, stress often remained unnoticed. However, the thermographic analysis provided detailed information on the impact of the film's stressful situation on the participants, with the possibility of distinguishing the stages of stress. The results of the preliminary pilot study were presented, which indicated the variability of temperature and heart rate as important indicators of stress - with the simultaneous significance of individual characteristics of the participant. Smartphone stress thermography is a promising method of monitoring human stress, especially at home.